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## FIFRA SCIENTIFIC ADVISORY PANEL (SAP) 1



## OPEN MEETING 2

3



## REEVALUATION OF 4



## THE HUMAN HEALTH EFFECTS OF ATRAZINE: 5



## REVIEW OF NON

- CANCER EFFECTS AND 6



## DRINKING WATER MONITORING FREQUENCY 7



## AND CANCER EPIDEMIOLOGY 8

9



## DOCKET NUMBER: EPA

- HQ

- OPP

- 2011

- 0399 10



## FIFRA SAP WEB SITE h ttp://www.epa.gov/scipoly/sap/ 11



## OPP Docket Telephone: (703) 305

- 5805 12

13



## UNITED STATES ENVIRONMENTAL 14



## PROTECTION AGENCY 15



## CONFERENCE CENTER LOBBY LEVEL 16



## ONE POTOMAC YARD (SOUTH BUILDING) 17



## 2777 SOUTH CRYSTAL DRIVE 18



## ARLINGTON, VIRGINIA 22202 19



## JULY 26

- 28, 2011 20

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## July 2 6, 2011

- 8:30 a.m. Day 1 2

3



### JOSEPH BAILEY : Hello, I'm Joseph Bailey, and I want to welcome 4



### everyone this morning to the FIFRA Scientific Advisory 5



### Panel Meeting. This meeting is a re

- evaluation of the 6



### human health effects of Atrazine, review of non

- cancer 7



### effects, drinking water monitoring frequency and cancer 8



### epidemiology. 9

10



### I just want to take a few minutes and go over our standard 11



### comments before the meeting. This is a Federal Advisory 12



### Committee Act meeting, meaning that it is a public 13



### meeting, and pa rt of my responsibility is to make sure 14



### that all the requirements of the Federal Advisory 15



### Committee Act is met. 16

17



### The Committee provides advice to the panel. All final 18



### decisions and regulatory decisions are left up to the 19



### agency, but they seek advice from the panel in a peer 20



### review capacity and consider the advice the panel gives in 21



### reaching their regulatory decisions. 22

23



### Part of our responsibility is to make sure that all of the 24



### ethics requirements are met for panel members. And to do 25



### that, we have asked the panel members to fill out 26



### disclosure information for us to review to make sure that 27



### there are no financial conflicts of interest or bias on 28



### behalf of any of the panel members. 29

30



### We have agendas out on the table so you can take a look at 31



### it. It is a pr etty full agenda. It does provide an 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### opportunity for public comment. The public comment 1



### opportunity is scheduled to begin this afternoon. 2

3



### Hopefully we'll be on schedule but the agenda is floating. 4



### Things can shift a little bit, but we will begin the 5



### public comment opportunity this morning and wrap it up 6



### tomorrow morning, at which time when that ends we will go 7



### into the charge questions with the panel discussions. 8

9



### If anyone has not let me know ahead of time they wish to 10



### present public comments, we have a little bit of time left 11



### in the agenda slot for that opportunity. Either let me 12



### know or any of the other people in the Scientific Advisory 13



### Panel staff know. And if you have not made prior 14



### arrangements, we ask that you limit your comment period to 15



### f ive minutes time. 16

17



### As usual, we have a public docket established. All the 18



### material that has been provided to the panel so far is in 19



### that docket. It is available electronically unless it is 20



### sensitive in any manner. And those documents that are 21



### sensitiv e can be accessed at the docket by visiting on the 22



### 4th floor in this building. 23

24



### EPA's presentations are in the docket. They should be 25



### available at some time today. And any public comments 26



### that are made, we will also put those in the docket if 27



### they are not already there. The docket number should be 28



### listed on the agenda. And as I mentioned, all of that 29



### information should be publically available unless it is 30



### sensitive information. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### At this point, I want to introduce Dr. Daniel Schlenk , who 1



### is the Chair for this session of the SAP. And again, I 2



### want to welcome the public here and EPA, as well as the 3



### panel. We have some new panel members and some returning 4



### members here, so I want to thank you all. Thank you. 5

6



### DR. DANIEL SCHLENK : Thanks, Joe. Good mo rning, everyone. My 7



### name is Daniel Schlenk. I am a professor of environmental 8



### toxicology from the University of California, Riverside. 9



### I will be serving as the session chair today, but in place 10



### of my esteemed colleague, Dr. Portier, who has been able 11



### to turn his attentions to some of the questions that have 12



### been asked, particularly with regard to statistics. 13

14



### What I would like to do right now is

-- we've got a fairly 15



### large panel

-- I would like to go around to each panel 16



### member and have them introduce themselves, where they are 17



### from and state briefly what their area of expertise is so 18



### that you guys can get a feel for what we have throughout 19



### this week. So Ken, you want to go ahead? 20

21



### DR. KENNETH PORTIER : Good morning. I am Dr. Kenneth Portier

. 22



### I am Ma naging Director of the Statistics and Evaluation 23



### Center at the American Cancer Society, national office in 24



### Atlanta. I am a biostatistician and the expertise I bring 25



### today is statistics in some of the environmental modeling 26



### hydrology. 27

28



### I should mention Dr . Chambers is going to be here a little 29



### later this morning. She is the third permanent panel 30



### member to make up our core for our meeting. She was 31



### delayed in Atlanta due to weather last night. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. STEPHEN KLAINE: I am Steve Klaine. I'm a permanent membe r 2



### of the panel and I am a Professor of Ecotoxicology at 3



### Clemson University. 4

5



### DR. ELLEN GOLD : I am Ellen Gold and I am professor and chair 6



### of the Department of Public Health Sciences at the 7



### University of California, Davis and an Epidemiologist. 8

9



### DR. FRANK BOVE : I am Frank Bove. I am with the Agency for 10



### Toxic Substances and Disease Registry in Atlanta. I am a 11



### Senior Epidemiologist in the Division of Health Studies. 12

13



### DR. HEATHER YOUNG : Hi. I am Heather Young from George 14



### Washington University, Department of Epidemiology. I am a 15



### cancer epidemiologist and also focus on reproductive 16



### outcomes. 17

18



### DR. NELSON HORSEMAN : Nelson Horseman. I am at the University 19



### of Cincinnati. I am a physiologist and endocrinologist, 20



### and my research areas of interest currently are in mammary 21



### gland development, lactation and breast cancer. 22

23



### DR. JAMES MCMANAMAN : I am Jim McManaman. I am at the 24



### University of Colorado. I am Professor and Chief of the 25



### Division of Reproductive Sciences and my interests are 26



### mammary gland biology and re productive mechanisms. 27

28



### DR. DANIEL GRIFFITH : I am Daniel Griffith from University of 29



### Texas at Dallas. I am an Ashbel Smith Professor of 30



### Geospatial Information Sciences. My area of expertise is 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### spatial statistics and I am working on the monitoring part 1



### o f the project. 2

3



### DR. HERBERT LEE : My name is Herbie Lee. I am a professor of 4



### statistics at University of California, Santa Cruz where I 5



### am also the Vice Provost for Academic Affairs. And my 6



### research areas include spatial statistics and computer 7



### simulatio n modeling. 8

9



### DR. ROBERT GILLIOM: Bob Gilliom, U.S. Geological Survey, and I 10



### direct our national studies of pesticides as part of the 11



### National Water Quality Assessment program, and I am here 12



### for the monitoring aspects, primarily. 13

14



### DR. SUSAN AKANA : I am S usan Akana. I am in my second career 15



### as an instructor at City College of San Francisco. I am 16



### late of UCSF where I had a career in stress and its 17



### interaction with energy balance in rodent models. 18

19



### DR. KEVIN O'BYRNE : My name is Kevin O'Byrne and I am from 20



### King's College London. I am a professor of reproductive 21



### neuroendocrinology and my research areas span the neurone 22



### control of reproduction; that is what I do. 23

24



### DR. KATHERINE ROBY : Kathy Roby from the University of Kansas 25



### Medical Center and my expertise i s reproductive 26



### endocrinology. 27

28



### DR. BARRY TIMMS : Barry Timms, professor in the Division of 29



### Basic Biomedical Sciences, Sanford School of Medicine, 30



### University of South Dakota. My area of specialty is in 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### developmental biology of the prostate glands with a 1



### s econdary interest in endocrine disruption. 2

3



### DR. TRAVIS JERDE : My name is Travis Jerde, Indiana University 4



### School of Medicine, Department of Pharmacology and 5



### Toxicology, and my area of expertise is prostate biology 6



### with an emphasis on prostatic inflammatio n and resulting 7



### adult disease. 8

9



### DR. PENELOPE FENNER

- CRISP: My name is Penny Fenner

- Crisp. I 10



### am a private consultant from Charlottesville, Virginia and 11



### a member of the Commonwealth of Virginia's Pesticide 12



### Control Board. My area of expertise is toxicology and 13



### human health risk

- assessment. 14

15



### DR. BETTE MEEK : And my name is Bett e Meek. I am Associate 16



### Director of Chemical Risk

- Assessment at the McLaughlin 17



### Center, University of Ottawa. I have a background in 18



### toxicology and spent most of my career in regulator y risk

19



### assessment at Health Canada. 20

21



### DR. RICHARD GREENWOOD : I am Richard Greenwood. I am an 22



### Emeritus Professor at the University of Portsmouth, and I 23



### am here for my expertise in the area of pharmacokinetics 24



### and toxicology. 25

26



### DR. WILLIAM HAYTON : I am Wi lliam Hayton, a Professor Emeritus 27



### College of Pharmacy, Ohio State University, and my area of 28



### expertise is pharmacokinetics. 29

30



### DR. DANIEL SCHLENK : Thanks, everyone. Just a point of 31



### administrative comment

, Dr. Barry Delclos will not be 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### joining us. He is l isted as a panel member. He could not 1



### make it today due to a family emergency, so he will not be 2



### providing comments today, for those of you that are 3



### interested in that. 4

5



### Welcome, everybody. At this point in time, as we begin 6



### our agenda, it is our stand ard practice to introduce Dr. 7



### Steven Bradbury, who is the Director of the Office of 8



### Pesticide Programs, and he is going to give us our opening 9



### remarks. Dr. Bradbury? 10

11



### DR. STEVEN BRADBURY: Thanks. I would like to welcome the 12



### panel to this week's meeting. I appreciate you all 13



### volunteering to help us as we explore the scientific 14



### issues before us this week. 15

16



### The role of the Scientific Advisory Panel for the 17



### Pesticide Program is very important in the work that we 18



### do. We use this peer review body to help u s evaluate both 19



### new methodologies that we want to bring to bear in our 20



### pesticide risk

- assessment process, as well as bringing to 21



### the panel specific questions sometimes around specific 22



### chemicals to help inform our regulatory decisions. 23

24



### The scientific fou ndation to the decision

- making process 25



### we make in the pesticide program is really fundamental to 26



### everything we do in our work at EPA, and not just for the 27



### pesticide program but for the agency as a whole, and the 28



### administrators. 29

30



### We emphasized that numero us times, since she has been 31



### running EPA, the importance of the best peer reviewed 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### available science to inform our decision

- making process. 1



### What's also very important in our decision

- making process 2



### is that it's open and transparent and that the public can 3



### participate in the process that we go through. So, not 4



### only having you all here and providing your scientific 5



### expertise, but also ensuring that the public has an 6



### opportunity to comment and the public has an opportunity 7



### to see all the documents that are c oming before you and 8



### ultimately see your report, and see your report in a 9



### context of the deliberations we will be having during the 10



### course of the week. 11

12



### So we are very much indebted to your time and service not 13



### only to us in the pesticide program, but mor e broadly to 14



### all the U.S. citizens, in terms of the kinds of decisions 15



### that we have to make, in terms of insuring pesticides that 16



### are affective for food and fiber production are also safe 17



### for human health and the environment. So your role is 18



### very instrume ntal in what we do. 19

20



### I also want to thank the public as we embark on this 21



### week's activity for the comments they have already 22



### provided and the comments you will hear during the public 23



### comment period, and that input is very important for the 24



### deliberations that you will be making. 25

26



### I also want to thank the Science Advisory Panel staff for 27



### helping us organize this meeting and the work it takes to 28



### reach out to all of you, and get you all lined up with all 29



### your paperwork so that you can be part of the panel an d 30



### all the work it takes to put a meeting like this on and 31



### work towards the final report that will come out in the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### coming months. So thanks, again, for all the effort that 1



### you have already done in getting ready for the meeting and 2



### the intense time you will have here, and then the intense 3



### time you will have in writing the report. We greatly 4



### appreciate it. 5

6



### I thought it might be helpful if I could just spend a few 7



### minutes maybe reviewing where we have been, with regard to 8



### atrazine and what we are going to try to accomplish this 9



### week. And in that quick summary also try to weave in some 10



### of the broader issues and opportunities that we are 11



### looking at in terms of advancing our risk

- assessment 12



### methodology in the pesticide program as we take a look at 13



### some of the new technologies and different approaches, 14



### evolving approaches as we go into the 21st Century. 15

16



### So, I will talk a little bit about atrazine and try to 17



### weave in some of the other techniques and approaches that 18



### are coming to bear in the atrazine risk

- as sessment. So, 19



### as you probably recall from some of the background 20



### documents you got, that in 2003 we re

- evaluated atrazine, 21



### and that was part of an effort that was ongoing for a 22



### number of years in which every pesticide that was 23



### registered before 1984 had t o be re

- registered, in other 24



### words, re

- evaluated to ensure that it met human health 25



### protection standard as well as environmental standards. 26

27



### And atrazine was re

- evaluated in 2003, and in 2006 it was 28



### looked at again with other triazine herbicides to ens ure 29



### that that group of herbicides together still met the 30



### safety standard associated with the Food Quality 31



### Protection Act, so looking at cumulative effects and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### ensuring protection for the population in general, as well 1



### as looking as sensitive sub

- population s, in particular, 2



### looking at children in terms of our safety finding. 3

4



### The current re

- evaluation program that we have that is 5



### dictated by statute is called registration review. And 6



### registration review requires that every pesticide be re

7



### evaluated every 15 years. And so atrazine, like every 8



### other chemical, is on its schedule and it is set to be re

9



### evaluated in 2013. But, just because a chemical is 10



### scheduled at a certain time in its re

- evaluation schedule 11



### does not mean we have to wait before we take a lo ok at a 12



### chemical if new information comes to bear that suggests we 13



### need to take a look, and just ensure that we are still 14



### meeting our safety findings. 15

16



### In the case of atrazine, probably one of the most 17



### intensively studied chemicals in the scientific lite rature 18



### -- probably not the most, but among pesticides, probably 19



### one of the most heavily studied pesticides

-- since 2003, 20



### there has probably been 150 or so papers that have been 21



### published with regard to atrazine. In addition, the 22



### registrant has submitted additional information over the 23



### course of the years as a part of the conditions of re

24



### registration, and there has been a lot of water monitoring 25



### going on, both in drinking water sources as well as in 26



### headwater streams in terms of taking a look at potential 27



### ecological exposure and effects. 28

29



### In 2009 the agency felt that, given the significant amount 30



### of information that has been published over the course of 31



### the last six to seven years, and the information coming in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### through the monitoring program as a conditi on of re

1



### registration

-- which you can get detailed information on 2



### atrazine concentration and drinking water sources

-- it 3



### made sense to sit back and take a look at the new 4



### information, take a look at that information in light of 5



### the monitoring data that w e had received. 6

7



### It was not suggesting any areas of concern in terms of our 8



### risk

- assessment in 2003, but take a look at new 9



### information since 2003 and reaffirm or make adjustments if 10



### necessary, based on the new science that was coming in. 11



### So, the end of 2009 we had a consultation with the Science 12



### Advisory Panel just laying out the peer review plan that 13



### we were going to ultimately execute in 2010 and here in 14



### 2011. 15

16



### And during 2010, we had three scientific advisory panels; 17



### one in February, one in April a nd then one in September. 18



### The February 2010 SAP was actually one that we had 19



### scheduled for some time and used that as an opportunity to 20



### look at atrazine as a case study, along with some other 21



### compounds. 22

23



### And the major emphasis of the February SAP, Scie nce 24



### Advisory Panel Review, was actually to take a look at a 25



### framework, a framework that was embracing the concepts 26



### that were coming out of the National Research Council's 27



### 2007 Report on toxicology testing in the 21st Century, and 28



### beginning to think about w ays to integrate experimental 29



### toxicology data as well as epidemiology data in a risk

30



### assessment process. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And also, looking at that NRC report in the context of 2



### what the NRC report called toxicity pathways, what we in 3



### the agency have been starting to cal l adverse outcome 4



### pathways, in which of more focused effort of looking at 5



### initiating events and thinking about the chain of events 6



### that happened in biological systems, as a way of 7



### organizing your thoughts and integrating information 8



### around the linkage betw een adverse outcomes and the 9



### various processes that could lead to adverse outcomes. 10

11



### And how do you look at experimental toxicology data along 12



### with epidemiology data to try to integrate that 13



### information, and essentially, how you pull together a 14



### coherent story about what the potential of a chemical may 15



### be in terms of its effects, its exposure and ultimately 16



### how that can help inform a risk

- assessment. 17

18



### And so in that SAP of February 20 10, trying to get some 19



### feedback on how to be thinking about these issu es, which 20



### is not just toxicodynamics, but also toxicokinetics; how 21



### do we better understand what happens at one level of 22



### biological organization in terms of the magnitude of the 23



### effect, the duration of effect and how much of that has to 24



### happen in order to h ave another event happen further down 25



### or along the biological chain of events. 26

27



### If you look at the NRC report, it talks about the fact 28



### that as we use these approaches, we will see perturbations 29



### in biological systems. Part of the challenge will be how 30



### muc h of a perturbation is necessary to elicit an adverse 31



### outcome, say a frank effect in the intact organism. And 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### so that February SAP was getting at some of the 1



### approaches, some of the things to think about as we go 2



### forward, and not just for atrazine, but m ore generally as 3



### we go forward with new risk

- assessment methods. 4

5



### But we also included in that SAP some case studies on 6



### epidemiology studies, ecological epidemiology study 7



### designs, primarily but not totally, and used that SAP to 8



### begin getting some feedba ck from you all on how to be 9



### looking at different kinds of epidemiology studies in 10



### terms of their design and their attributes, and how 11



### different types of epidemiology studies should be 12



### contemplated as you start to think about integrating 13



### epidemiology data with experimental toxicology data. 14

15



### The studies that may be helpful in terms of formulating 16



### hypothesis versus the kinds of studies that may be very 17



### powerful in terms of establishing causation from an 18



### epidemiological perspective, and how to integrate that 19



### with toxicological information. So that really helped us 20



### to sort of get our framework together and get some of our 21



### thoughts together about how to approach this risk

22



### assessment, as well as some initial thoughts on how to be 23



### taking a look at epidemiology s tudies. As you know, there 24



### are a lot of epidemiology studies associated with 25



### atrazine. 26

27



### The April 2010 SAP then primarily focused on experimental 28



### toxicology data, looking at both in vitro information as 29



### well as in vivo information, and again, getting so me 30



### feedback on the studies themselves and how to be thinking 31



### about those studies, and what are those studies telling us 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### in terms of what we knew in 2003, to the extent that there 1



### were some new insights coming since 2003. 2

3



### That gave us some good feedbac k in terms of the 4



### reproductive and developmental outcomes that have been the 5



### focus of 2003 in the context of LH surge suppression being 6



### sort of a key event that could lead to changes in 7



### reproductive or developmental outcomes, and how that 8



### related to an oth er kinds of experimental toxicology data 9



### that had come out in the previous years in terms of 10



### immunological effects or neurological effects. 11

12



### We also used that SAP to get some initial feedback on 13



### sensitivity across different life stages and things that 14



### we should be thinking about in that regard. We also had 15



### some discussions around dosimetry and how to take a look 16



### at what could be happening at a sub

- organismal level and 17



### be thinking about oral uptake of atrazine in drinking 18



### water, and steady

- state exposures versus pulse exposures 19



### and versus the kinds of patterns we would see in drinking 20



### water systems. 21

22



### So that SAP also gave us some initial feedback on how to 23



### take a look at the monitoring data that already existed 24



### and how do you extrapolate across time an d space, in terms 25



### of interpreting potential human exposure to atrazine. 26

27



### The September SAP then had a heavy focus on noncancer 28



### effects, looking at both the experimental toxicology data 29



### as well as the epidemiological data that was available for 30



### noncancer e ffects, and again, also looking at drinking 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### water issues, in terms of monitoring designs, sampling 1



### frequency. 2

3



### Because, one of the challenges with this risk

- assessment

- 4



### - it is a challenge for this risk

- assessment, but through 5



### this risk

- assessment, wil l give us insights for the future 6



### -- is that, as we understand what is happening in terms of 7



### the toxicodynamics and toxicokinetics clearly duration of 8



### exposure, timing of exposure is critical and it is highly 9



### variable in the real world. 10

11



### We have nice ste ady

- state exposures in the laboratories, 12



### typically, but that is not how real world exposures 13



### happen. And so, what is going on inside the organism in 14



### terms of differential exposure in time, and in the 15



### duration of those exposures, is really critical 16



### interpr eting whether or not there is a perturbation in a 17



### biological system, and to extent those perturbations could 18



### be significant, in terms of eliciting adverse outcomes. 19

20



### What is also challenging in the world of watersheds and 21



### the world out there in terms of the variability in timing 22



### of chemicals reaching drinking water sources. So the time 23



### and space in terms of chemicals being used in the 24



### environment, run off, getting into a drinking water system 25



### and realizing that in the real world, pesticide typically 26



### are not associated with nice quasi steady

- state 27



### concentrations that you have seen from the reports; 28



### a trazine used in the spring, when there is a runoff event, 29



### it is usually happening after a rainfall event, not too 30



### far after it was applied. And so, we see ver y spiky, 31



### typically spiky exposures of atrazine, which may be in a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### drinking water system for two, three, four, five, six days 1



### maybe, from beginning to end of a "spike". 2

3



### And then you may not see any atrazine for days, weeks, 4



### months, maybe not for the rest of the growing season and 5



### into the next spring, or you may seen some periodic lower 6



### level spikes. 7

8



### So how do we interpret those kinds of exposures in 9



### drinking water systems, relate that to human consumption 10



### and then get back to the experimental toxicolo gy data, 11



### which probably had a different dosing regime than what we 12



### are seeing in the real world? And so, the toxicokinetics 13



### and the linkage of this in time and space is a critical 14



### part of the risk

- assessment that we are doing. And you 15



### have all been exper iencing it, some of you over the last 16



### year. 17

18



### And as we come to this week's Science Advisory Panel, we 19



### hope to bring together many of these different threads 20



### that have been getting woven together over the course of 21



### the last year. So getting feedback agai n on the non

22



### cancer effects in terms of the role of LH surge 23



### suppression, how that fits into an adverse outcome pathway 24



### interpretation; what's a dosimetry? Both a dose and 25



### duration of exposure that is important to consider in 26



### terms of perturbations and pe rturbations that may be 27



### significant enough to cause adverse outcomes , w hich leads 28



### us to the toxicokinetics and how to be thinking about how 29



### we deal with the factor's variable exposure to interpret 30



### those effects. And then how does that link into the 31



### drinki ng water monitoring designs, and how do we interpret 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### that information so it's toxicologically relevant to the 1



### risk

- assessment that we need to do. 2

3



### And the final, really important, part of this peer review 4



### is taking a look at the potential cancer affects 5



### a ssociated with atrazine. As you know, as the scheduling 6



### was playing out, we were working with our colleagues in 7



### the National Cancer Institute and the worker health study 8



### cancer, a very intensive prospective epidemiology study. 9

10



### The work associated wit h atrazine was finished a few 11



### months ago, so we will be able to bring the results of 12



### those studies to the table and take a look at the cancer 13



### issue then with that final epidemiological study 14



### completed; along with the other epidemiological studies as 15



### well a s any experimental toxicology data and get your 16



### feedback on atrazine's potential with regard to cancer. 17



### Which today, has been concluded that it is not likely to 18



### be a human carcinogen, but we want to revisit that and see 19



### if that conclusion still holds, bas ed on the most current 20



### information. 21

22



### So my apologies for running a little long, but given the 23



### year and a half we have been working on this, I felt it 24



### probably made sense to spend a little bit of time just 25



### kind of reviewing where we have been, where we ar e, where 26



### we are heading, both in terms of atrazine and some of the 27



### underlying methods that we are hoping to bring to bear, 28



### not only for atrazine but for other risk

- assessments in 29



### the future. 30

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### So with that, I will pause and just turn it over to Jack 1



### Fowle here in a second, if it is okay, and thank all the 2



### scientists and OPP. They have been working on this as 3



### well as our colleagues in the EPA's office, research and 4



### development, and the NCI for their assistance as well, as 5



### we have been putting this informat ion together. Let us 6



### turn back to the Chair and thank you for your indulgence. 7

8



### DR. DANIEL SCHLENK : Thank you, Dr. Bradbury, for that 9



### oversight and background. It is very useful for us, I 10



### think. Our next speaker is Jack Fowle. He is the Deputy 11



### Directo r of the Health Effects Division from OPP. Jack? 12

13



### DR. JACK FOWLE: Thank you, Dr. Schlenk, and thank you 14



### distinguished members of the Science Advisory Panel. I 15



### would like to echo Dr. Bradbury's comments in terms of 16



### thanking the panel for all your hard wo rk. We have a few 17



### new members here today; welcome, too. And for the folks 18



### that have been here over the last year and a half, we 19



### really do appreciate all that you have done to help us 20



### focus and winnow down our efforts. 21

22



### Over the past year and a half, as you have heard Steve 23



### say, we have come to the panel on several occasions; three 24



### full

- blown atrazine review panels and two meetings, one to 25



### sort of set the stage and one in the context of a case 26



### study for our epidemiology framework. 27

28



### Because we are hea lth protective with the Environmental 29



### Protection Agency, our mission is to ensure that, here in 30



### the pesticides program, pesticides use according to label, 31



### they are safe for human health and the environment. We 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### feel it is very important to take due diligen ce, and in 1



### essence, look at everything. So over the past year and a 2



### half, the topics we have come to have run the gamut from 3



### neuroendocrine mode of action to immunotoxicity, 4



### epidemiology, pharmacokinetics and various approaches for 5



### how we might analyze an d integrate this information into 6



### drinking water monitoring data. 7

8



### This meeting, in some ways, from a public health 9



### perspective

-- not ecological effects, but from a human 10



### health effect

-- is in some ways sort of an epilogue. We 11



### are trying to winnow thi ngs down and we are trying to 12



### bring things to a conclusion at this particular point in 13



### time. 14

15



### So, basically what we will be presenting too, is sort of 16



### how we have built on your recommendations and how we have 17



### built on the guidance from the National Acade my of 18



### Sciences and their report

-- in particular, a 2007 report, 19



### Toxicity Testing at 21st Century

-- to focus on what we 20



### understand about the adverse outcome pathway of atrazine 21



### and which of the biological changes that we are observing 22



### are leading to an ad verse outcome, potentially, and which 23



### maybe are just bumps in the road due to normal homeostatic 24



### processes, would get us back to normal function. 25

26



### So based on that, we are now focusing on suppression of LH 27



### surge and potential impacts on reproduction, and that‟s 28



### consistent with the report from your April Science 29



### Advisory Panel. You will hear that theme being woven in 30



### throughout the presentations today. 31

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### Having said that, as Steve pointed out, that atrazine is a 2



### major chemical from the pesticides program and we do 3



### continuously monitor new data, new information that come 4



### in on our pesticide products, and we will continue to do 5



### that as we go into the future. 6

7



### At this particular point in time, I would also like to 8



### note that we are not really giving a risk

- assessment at 9



### this particular point in time, but sharing with you our 10



### understanding of the potential impacts of atrazine on 11



### human health up to this state of the science, as we 12



### understand at this particular point in time, and also the 13



### impacts and implicatio ns for drinking water monitoring. 14

15



### We will be, as Dr. Bradbury noted, coming back to you with 16



### a review of our understanding of the potential ecological 17



### impacts of atrazine in 2012, and the actual risk

18



### assessment of atrazine will be conducted in 2013 when we 19



### conduct our registration review of the compound at that 20



### point in time. 21

22



### There have been a few changes on the staff, at least for a 23



### temporary basis. You may recall in past meetings that Dr. 24



### Anna Lowitt has been leading the effort in terms of 25



### atrazine review. She, as you know, had a child that was 26



### born April 12th. She is on maternity leave and she may be 27



### coming today and perhaps

-- oh, she is here. Oh, hi, 28



### Anna. I did not even know she was here. Welcome. She 29



### has a son. We miss her very much. 30

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### But in her absence, Dr. Elizabeth Mendez has stepped up to 1



### the plate and taken the lead for the effort, and she has 2



### just done an absolutely magnificent job in terms of 3



### leading the scientific team and all the various scientific 4



### challenges down to the nitt y

- gritty. You may note that 5



### you got the report a few days later. It is a 673, or 6



### whatever, page report, and it far exceeded the capacities 7



### of wonderful Bill Gates and his Microsoft products. 8

9



### So, Liz led the team through two days, 17 hours going line 10



### by line on the report

-- quality controlling it

-- to get 11



### it into shape so we could mail it to you. So she has left 12



### no stone unturned. Liz, I just cannot thank you enough 13



### for what you have done in this. 14

15



### I would like to thank the team that has conducte d the 16



### analysis and pulled together the material that is 17



### presented on this topic for the past several years and 18



### also today. I will not mention by name because there are 19



### roughly 17 from the pesticide programs, about 13 from ORD 20



### and roughly a handful from th e National Cancer Institute; 21



### but we really appreciate their help. And I will turn it 22



### back to you, Dr. Schlenk. 23

24



### DR. DANIEL SCHLENK : Thank you, Dr. Fowle. Before we move on 25



### to Dr. Mendez, I would like to introduce Jan Chambers who 26



### is one of our permanent panel members who just arrived. 27



### Jan, if you could just introduce yourself? 28

29



### DR. JANICE CHAMBERS: Thank you. Let me assure you I did not 30



### oversleep. I have actually been up since 3:30 after 31



### several hours of indecision. Last evening, Delta 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### cancelled m y flight and I spent the night in Atlanta and 1



### just got in on a flight this morning. 2

3



### I am Jan Chambers with the College of Veterinary Medicine 4



### at Mississippi State University. I am a pesticide 5



### toxicologist, specializing mostly in metabolism and 6



### neurotoxi city. 7

8



### DR. DANIEL SCHLENK : Thanks, Jan. So with that, we will turn 9



### the microphone over to Dr. Mendez, if you could get us 10



### going and give us some intro and some status report here. 11



### Thank you. 12

13



### DR. ELIZABETH MENDEZ : Good morning. Before I start with my 14



### presentation I want to reiterate what Dr. Fowle and Dr. 15



### Bradbury said before. As a member of the team, your input 16



### over the past year and a half has been absolutely 17



### invaluable to us as we move forward, and we really do 18



### appreciate your guidance throughout this process. 19

20



### So, today's talk s are going to be reflecting how we have 21



### gone about incorporating some of the recommendations into 22



### our evaluation that were feasible under the current 23



### timeline. But they are also built upon the previous 24



### atrazine evaluations , going back to the 1980s. 25

26



### So, let's take a little trip down memory lane. In 1988 27



### the agency sought the panel's input on the mammary gland 28



### tumors seen in the rat. At that point, the panel noted 29



### that a hormonal influence might be an important 30



### considera tion in the development of these mammary gland 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### tumors in the adult rats, and so they guided us to look 1



### into that aspect of the tumor genesis that we were seeing. 2

3



### So we returned to the SAP in 2000 for advice on atrazine's 4



### mode of action leading to the m ammary gland tumors, the 5



### reproductive and developmental effects in the rats, as 6



### well as the human relevance of these findings. 7

8



### The SAP agreed with the agency's proposal for atrazine's 9



### neuroendocrine mode of action and they concluded that it 10



### was highly un likely that the mechanism by which atrazine 11



### induces mammary tumor in the adult female Sprague

- Dawley 12



### rats could be operational in humans. 13

14



### Based on the 2000 SAP guidance, the EPA reconsidered its 15



### position in atrazine and reclassified it from a possible 16



### ca rcinogen to not likely to be carcinogenic to humans. 17



### But another thing that the SAP did tell us at that point 18



### was that it was not unreasonable to expect that atrazine 19



### might cause adverse effects on the HPG axis if it was 20



### perturbed enough and that the effe cts that that could lead 21



### to in development and reproduction could indeed be 22



### relevant to human. 23

24



### So, although it was not relevant for the mammary tumors, 25



### it was likely that it was relevant for other adverse 26



### outcomes. And that has sort of been the impetus of our 27



### research since, at that point. We sort of narrowed it 28



### down to that. 29

30



### In 2003 we came back to the SAP, and that time was for the 31



### evaluation of the prostate cancer. There were a number of 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### studies, particularly one in an atrazine manufacturing 1



### plan t, the St. Gabriel Atrazine Manufacturing Plant, and 2



### we wanted to look at what was happening there because 3



### there appeared to be an increase in the prostate cancer 4



### cases that we were seeing. 5

6



### When we came back to the SAP, the conclusions of the 7



### panel, to a certain extent, was that those increases 8



### could, in part, be explained by PSA screening being more 9



### readily available to the staff at the plant, but that it 10



### could not entirely dismiss other contributing factors to 11



### the increase. 12

13



### And their feedback to us was to maintain vigilant, keep 14



### looking at the data and look for the agricultural health 15



### study that was looking at the prostate cancer, as well. 16



### And that sort of brings us where we are today and why we 17



### have come back. 18

19



### The goal of this re

- evaluation is t o determine if the 20



### risk

- assessment for atrazine should be revised. And the 21



### basis and the genesis for that, as Dr. Bradbury and Fowle 22



### mentioned is, over the past seven years, since the 2003 23



### IRED, the atrazine researchers have been a rather prolific 24



### group a nd have produced over 100 articles that we wanted 25



### to take a look at and make sure that we brought the state 26



### of the science to bear on this risk

- assessment. 27

28



### We wanted to evaluate that experimental toxicology data, 29



### both non

- cancer and cancer effects. We have evaluated 30



### epidemiology data. There have been a few dozen 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### epidemiology studies that have been put forth since the 1



### 2003 IRED. 2

3



### And the other thing that we wanted to do, which we had not 4



### done very clearly before was try to integrate the 5



### experimental toxicology and the Epi data, and that is what 6



### the February SAP was all about, how we were going to go 7



### about doing this in a systematic way. Another thing that 8



### we wanted to do was ascertain if the critical life

- stages 9



### are adequately assessed. 10

11



### Now, tal king about a neuroendocrine mode of action, of 12



### course, makes us think about what is happening in the 13



### neuroendocrine system across different life

- stages. So, 14



### we wanted to be very cognizant of the differences in the 15



### hormonal malaria at different life

- stages and how it may 16



### be impacted by the atrazine exposure, also ascertain if 17



### the durations of exposure assessed are the most 18



### appropriate. 19

20



### So in the case of atrazine, it is not only the life

- stage 21



### that is important, but also how long during that life

22



### stage th e exposure occurs and trying to understand if what 23



### we were doing in terms of monitoring would help us get a 24



### good grip on that information. So, that brings us to 25



### identifying methods for analyzing the uncertainty in 26



### drinking water monitoring data. 27

28



### So, I mean, ideally, we want to have the ideal dataset

-- 29



### sometimes we do, sometimes we do not

-- and we have to 30



### then understand and get a good handle on what those 31



### uncertainties may be and how we can address them in our 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### efforts to continue to produce a risk

- a ssessment that is 1



### health protective. 2

3



### So, I am just going to go over these very, very quickly 4



### because these are the atrazine 2010 SAPs. Some of you 5



### have been with us throughout this entire process and I can 6



### only imagine how very glad you are to hear us say that 7



### this may be the last one for human health. 8

9



### In February 2010, the draft framework was brought to you 10



### incorporating the epidemiology studies and human health 11



### incident data in risk

- assessment. That was actually 12



### intended to be a framework in gener al, not an atrazine

13



### specific meeting, but we had two atrazine case studies as 14



### part of that and that helped to sort of set the stage, 15



### give us some ideas on what the panel was thinking so that 16



### we could start doing that as we came back for atrazine 17



### itself. 18

19



### In April 2010 we had our preliminary evaluation of in 20



### vitro and in vivo lab studies, and at that point we 21



### concentrated on the non

- cancer data. As I mentioned 22



### earlier, we have well over 100 studies that have been 23



### published in 2003, so we found ourselves i n a situation of 24



### trying to apportion this in manageable sizes so that we 25



### could wrap our arms around it and not overwhelm you with 26



### 600

- page documents, although it did happened at the end. 27



### And we also came back and talked to you about the 28



### frequency of atraz ine monitoring in drinking water sources 29



### and there was a proposal for some approaches as to how we 30



### were thinking about going about doing that. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### The September SAP in 2010 was the one that based on 1



### epidemiology studies; non

- cancer, and was our first 2



### attemp t to really start integrating the Epi and 3



### experimental Tox data into the hazard characterization for 4



### non

- cancer. Based on some of the feedback that we got 5



### from the panel in April, we also had an update and 6



### analyses of the frequency of atrazine monitoring in 7



### drinking water sources. 8

9



### So, those were the things that we brought to the panel and 10



### this is some of the feedback that we got from the panel. 11



### Obviously, the reports are rather extensive and lengthy so 12



### I have just sort of captured the highlights at thi s point. 13

14



### But in February, SAP in general, the panel concurred with 15



### the agency's proposed approach for evaluating the Epi 16



### data. They told us to consider the likely contribution of 17



### human data and the scoping and problem formulation 18



### process, consider the tox and epidemiological databases to 19



### identify uncertainties and critical data gaps and consider 20



### overall quality of the Epi data; quality of exposure 21



### assessment, sample size, statistical power, careful 22



### definition of outcomes, source bias, et cetera. 23

24



### Then in April when we came with a non

- cancer data, from 25



### the experimental side we looked at the cancer data that 26



### had been generated since 2003. And the panel reaffirmed 27



### the conclusions of the previous SAP regarding the 28



### classification for atrazine; it is not li kely to be 29



### carcinogenic to humans. 30

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### It concurred with the agency's conclusions that atrazine

1



### induced effects on the neuroendocrine function remain as 2



### the most sensitive vaccine to date. And an important 3



### recommendation that they made to us was they start ed 4



### shifting our thinking from external dosimetry to internal 5



### dosimetry. 6

7



### We had some PK data that would allow us to do that, which 8



### we do not often have in a lot of our chemicals. So, in 9



### this instance, let's make use of all the information that 10



### we have to the best of our abilities. And they also noted 11



### something that I just mentioned, that the toxicological 12



### duration of concern is key to determining the sampling 13



### frequency. 14

15



### So for an effect that

-- maybe a critical window of 16



### exposure may be two days, y ou may need more frequent 17



### sampling than if the critical window of exposure is, say, 18



### 90 days or 30 days; and sort of got us thinking about how 19



### we would integrate those two aspects. 20

21



### The September SAP, we brought in for the first time the 22



### mammary gland dev elopment data. There were some 23



### discrepancies between some studies and we wanted to get 24



### the panel's input on that. They agreed that, at this 25



### point in time the mammary gland development is not 26



### sufficiently robust, the dataset, for us to move in that 27



### direct ion. But again, we brought in our use of internal 28



### dosimetry and asked for your input on, were we on the 29



### right track; did we need to be redirected somehow? The 30



### panel concurred with us that the LH suppression is 31



### protective of the other effects and the use of Dr. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Cooper's data from 2010 to establish the point of 1



### departure. 2

3



### One of the other critical things that we heard from the 4



### panel at that time was that, based on the available data 5



### that we have to date, there was no evidence of a higher 6



### sensitivity of t he young relative to the adults. That is 7



### to say that when we are looking at LH suppression in the 8



### adult females, the point of departure for that is lower 9



### than any of the developmental reproductive effects that we 10



### see across different life

- stages. 11

12



### The n on

- cancer Epi findings were also brought at that time 13



### and we saw that they were helping us in certain terms of 14



### qualitatively ground

- truthing our experimental findings 15



### because there was some consistency. And so, although we 16



### could not use it in terms of a q uantitative assessment, we 17



### could use it as part of our weight of the evidence 18



### analyses. 19

20



### And finally, there was a recommendation of a combination 21



### of statistical and modeling methods to quantify the 22



### uncertainty in exposure estimates from the monitoring 23



### dat a, which has been one of the things that we have been 24



### struggling mightily with over the past few years. 25

26



### So what are we going to do over the next four days? We 27



### are going to review new experimental toxicology studies. 28

29



### Since July of last year, whic h was when we closed the 30



### submissions to us for being included in the September SAP 31



### paper, up until April 29th of this year, there have been 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### approximately a dozen new experimental tox studies. Those 1



### studies have come in from industry from our own labs down 2



### in the park, as well as the open literature. 3

4



### We are going to be looking at the species extrapolation 5



### from the rat to human and the duration of exposure and 6



### life

- stage sensitivity analysis, approaches for analyzing 7



### monitoring data in the drinking water. 8

9



### And one of the things that we wanted to bring to you

-- 10



### and we are not going to be asking you questions or having 11



### a presentation on it

-- is an update on the exposure 12



### assessment collaborative project with the AHS. It is part 13



### of your packet. We just wa nted to give you an update on 14



### that but we have not, at this point in time, reached any 15



### conclusions in that project. So we felt that, given the 16



### voluminous amounts of data that we have to go through in 17



### other areas, we would just give you an update on paper. 18

19



### The epidemiology studies; we are going to concentrate on 20



### cancer this time. And finally, we are going to try to 21



### integrate the weight of our evidence with Epi and 22



### experimental toxicology. 23

24



### So in his opening remarks, Dr. Bradbury mentioned that we 25



### are t rying to look at all of this in the context of the 26



### NRC's toxicity testing in the 21st century and how we go 27



### about this. So we have our compound; we have our 28



### metabolites. Dr. Cooper is going to be talking about the 29



### mode of action. And we are going to be assessing the 30



### biological perturbations, which is the GnRH pulsatile, 31



### pulse generator, the effected pathway which is the HPG 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### axis, and the dose response analyses for the perturbations 1



### of toxicity pathways. 2

3



### This part is actually going to be a talk by Dr. Chester 4



### Rodriguez, so there is a little bit of an overlap there. 5



### Dr. Christensen is going to be talking about the 6



### epidemiology. The human exposure is going to be addressed 7



### by Nelson Thurman. And the human dosimetry and internal 8



### dosimetry is also going t o be addressed by Dr. Chester. 9

10



### Somewhere in here, although it is not explicitly here, we 11



### are going to start talking about the life

- stage 12



### sensitivities, as well as the integration of the 13



### epidemiology and the toxicology data. So with that, I am 14



### just goin g to give you a brief run

- down of the 15



### presentations. Dr. Cooper will be coming right after me 16



### talking about the adverse outcomes and mode of action. 17

18



### Dr. Christensen will be reviewing the atrazine cancer 19



### epidemiology data. Then I am going to come back and talk 20



### about the integration of epidemiology and tox data into 21



### the health risk

- assessment. A trazine updates to the dose 22



### response assessment will be addressed by Dr. Rodriguez. 23

24



### Mr. Nelson will be talking about the drinking water 25



### monitoring data. I w ill then come back, yet again, to 26



### talk about the potential sensitivity of infants and 27



### children, so that‟s the life

- stage sensitivity. And 28



### finally, we are going to wrap up with a case study that 29



### attempts to overlay the water monitoring data and the 30



### water e xposure with our dosimetry approach to try and 31



### bring it all together. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So, as you can see, we have a full agenda. The hope here 2



### is that, with this four days, we are going to wrap 3



### everything that we have gone through from February, April 4



### and September in to a coherent story of what is atrazine 5



### doing. And with that, if there are any questions? 6

7



### DR. DANIEL SCHLENK : Thanks, Dr. Mendez. What I would like to 8



### do is hold all our questions to perhaps after Dr. Cooper's 9



### presentation, if that is okay, just to kee p this on time 10



### here. So with that, I would like to introduce Dr. Ralph 11



### Cooper who is with the National Health and Environmental 12



### Effects Research Laboratory, Office of Research and 13



### Development EPA. Dr. Cooper? 14

15



### DR. RALPH COOPER : Thank you. And I would l ike to echo the 16



### remarks of my colleagues here at the front table about how 17



### much we appreciate the input that we have received from 18



### the panel on this arduous task of pulling all this stuff 19



### with atrazine together. 20

21



### My presentation today really focuses on th ree things. A 22



### lot of it will reiterate what Liz just mentioned about the 23



### mode of action and why LH was selected as the key event or 24



### one of the key events in the evaluation of atrazine 25



### toxicity. 26

27



### And then, there is two sort of related but separate 28



### comp onents of the presentation where we are trying to 29



### respond to some of the earlier comments that this panel 30



### has made concerning some analysis of the mammary gland 31



### work that has been done, the development work that has 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### been done, and some presentation and dat a that was 1



### recently published by ORD, and then also talk a bit about 2



### one of the requests from the September panel about getting 3



### a better handle on exactly what happens with short

- term 4



### dosing and this whole question about 1

- day, 2

- day, 3

- day 5



### kind of thing. 6

7



### So with that said, historically, as Liz Mentioned, the 8



### mode of action and hazard assessment of atrazine was 9



### focused around the fact that atrazine was found to cause 10



### premature development of mammary gland tumors in the 11



### female rat. 12

13



### And to make a long s tory short and to avoid using a lot of 14



### slides, what was shown essentially is that these tumors 15



### develop earlier. There does not appear to be necessarily 16



### more of them later in life, but they come on earlier in 17



### life. And because of the nature of reproductiv e aging in 18



### the rat, the fact that when the rats go through an estro

19



### pause or stops the normal reproductive cycle, the pattern 20



### of hormone secretion that develops in the aging female is 21



### just one of high estrogen and unopposed estrogen and 22



### prolactin secretion , and therefore, that is conducive to 23



### the growth of the tumors. 24

25



### At the same time, the literature is pretty solid on the 26



### argument that one of the key moving factors in 27



### reproductive aging in the rodent is the disruption of the 28



### regulation of the gonadotrop in, in particular, LH. 29

30



### With advancing age, there is essentially a little bit of 31



### slippage in timing of the occurrence of the surge and the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### amplitude gets progressively lower to the point where it 1



### can no longer sustain ovulation. The ovaries then devel op 2



### persistent follicles, which secrete the estrogen and 3



### feedback onto the pituitary to increase prolactin 4



### secretion, as I just mentioned. 5

6



### So with that background, it led to the studies where 7



### investigators looked more directly at the regulation of 8



### lutein izing hormone and what the dose response 9



### characteristics would be, and duration of exposure for the 10



### effects of atrazine on LH, and that was where they were 11



### almost at the 2000 SAP where, when that literature and 12



### that data was reviewed, they agreed that atra zine induced 13



### alterations of the secretion of LH. 14

15



### Specifically, the ovulary surge of LH was the key event in 16



### the development of mammary gland tumors. It occurred 17



### earlier in the atrazine

- exposed animals. 18

19



### They presented essentially a toxicity path way of sorts 20



### then. Some of it has been upheld. Some of the more 21



### molecular events have not been upheld. But essentially, 22



### it says that the brain, particularly the hypothalamus, 23



### seems to be a target site for this herbicide, and that 24



### through the effects on the brain, the regulation of the 25



### pulsatile release of gonadotropin releasing hormone out of 26



### the brain is disturbed. Therefore, the amplitude or the 27



### secretion of LH is altered. 28

29



### Once that happens, you get the persistent estrous, as I 30



### said, the persistent secretion of estradiol and prolactin, 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and these induce the proliferative effects on the mammary 1



### glands themselves. 2

3



### Liz mentioned, and again I will reiterate

-- and since I 4



### just mentioned the reproductive aging in the rat is driven 5



### by changes in the bra in, or that is what is believed

-- 6



### there are still some descending view points. But the 7



### primary changes take place in LH, and that is quite clear, 8



### but that is not the same thing that happens in humans. 9

10



### When humans age it is the depletion of the follicl es from 11



### the ovary that seems to be the driving factor. The 12



### hormonal environment present in the post

- reproductive 13



### woman is quite different than that in the post

14



### reproductive rat, and therefore, there was the basis for 15



### the conclusion that it would be highly unlikely that 16



### atrazine would have the same outcomes in humans. 17

18



### At the same time, there were data available at that SAP 19



### that said, "Well, if you are going to look at LH and you 20



### are going to look at the regulation of this hormone and 21



### what the other physi ological roles of this hormone plays 22



### in the male and female, what is happening there and is 23



### that relevant to the risk

- assessment of atrazine?" And 24



### there were a number of studies that were done looking at 25



### the impact of changing LH secretion at different li fe

26



### stages and in different sexes. What I have up there

-- 27



### the first three bullets in black are outcomes that appear 28



### to be dependent upon alteration of the LH. 29

30



### It is a regulation of luteinizing hormone, either during 31



### development where there were two s tudies from ORD

-- and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### they were replicated by other investigators

-- that showed 1



### that this chemical will delay puberty in both the male and 2



### the female rat. 3

4



### The data that I put there

-- this is to add some numbers 5



### and to help get where I'm going in a sl ide or two

-- is, 6



### the data I put there are the LOAELs for the adverse 7



### affect, that is the delays wherein the male 12 and a half 8



### milligrams per kilogram and the female 30 , t hat the 9



### disruption of ovarian cyclicity which, again, appeared to 10



### be dependent on ch anges in LH, came in at about 75 11



### milligrams per kilogram for a 21

- day study. 12

13



### There was a longer

- term study where somewhere around 22 14



### milligrams was the LOAEL. The lowest LOAEL up here is one 15



### that showed that the disruption of regular cycling in the 16



### fem ale, the early reproductive senescence came in at about 17



### 3.65 milligrams per kilograms after a six

- month exposure. 18

19



### And then there was a study looking at comparing different 20



### strains of animals during pregnancy. Rat pregnancy has an 21



### LH

- dependent phase. A nd in this study, the investigator 22



### dosed only during that stage of pregnancy and showed that 23



### there was a differential sensitivity cross

- strains; the 24



### most sensitive strain being the Fischer 344, that when you 25



### dose with atrazine during that period it lowered the LH 26



### and you got full

- litter resorption; that‟s what FLR stands 27



### for. 28

29



### There have been two other adverse outcome types of studies 30



### that have been conducted that do not appear to be relevant 31



### to or dependent upon some change in luteinizing hormone, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### per se . That was the work done by Dr. Tammy Stoker 1



### looking at the development of prostatitis after the dam 2



### was treated early in life, presumably was shown to knock 3



### down prolactin in the dam. And when you knock down 4



### prolactin in the dam, that impacts, based on the studies 5



### in the basic literature, the development of certain 6



### dopaminergic neurons in the brain which then alter, when 7



### that animal grows up, its ability to regulate prolactin 8



### and bad things happened in this case to the prostate where 9



### you saw prostate inf lammation around the 120 days of age. 10

11



### And there has been some similar work done following up 12



### with looking at the prostate where the animals were dosed 13



### during gestation. And then the last bullet up there, the 14



### altered memory gland development was one of the focuses of 15



### the September SAP. And mechanistically, or how that 16



### relates to LH, I am not clear if it does at all. 17

18



### Let me just back up one minute. With the prostatitis, the 19



### LOAEL for that was 25 milligrams per kilograms. As I 20



### mentioned, full

- litter resorptions came in at 50. And the 21



### mammary gland data, I don't have a number there. The 22



### majority of studies used 100 milligram per kilogram, but 23



### the work of Dr. Fenton, she has publications that shows 24



### that that dose could be run down considerably and yo u 25



### would see changes there. And again, we feel that might 26



### need to bear repeating before we can actually put 27



### something on those numbers. 28

29



### What I show in this next slide though is

-- and this is 30



### getting at the rationale why the agency feels that if we 31



### look at luteinizing hormone itself that we can actually

-- 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### since we are seeing changes in the physiology of animals 1



### that are dosed with atrazine at higher levels than the 2



### changes that we see in luteinizing hormone, that using 3



### this measure could be protective, or could be considered a 4



### centennial measure for the adverse outcomes. 5

6



### What I have there is the top two lines show the studies 7



### looking at the pulsatile release of GnRH out of the brain 8



### using a surrogate measure that is luteinizing hormone 9



### pulses themselve s in experimental models. Those have come 10



### in at 25 and 50 milligrams per kilogram. The duration of 11



### dosing there is four days. 12

13



### And down, the next bigger block there, pituitary 14



### attenuation of LH surge. If you look on the left

- hand 15



### side you will see t he different durations and the doses 16



### that were considered LOAELs and NOAELs, and I highlighted 17



### the ones that seemed to come in at the lowest dose 18



### necessary to produce a change. 19

20



### We had some one

- day studies that demonstrated that you 21



### could identify a LOAE L, at least in the Long Evans 22



### animals, but it was a very high dose; 300 milligrams per 23



### kilograms. I will discuss in a moment some new data that 24



### we have taken a somewhat different approach, experimental 25



### design to look at the potential adverse effects or 26



### po tential changes in LH secretion after one day of 27



### exposure; work by Jerome Goldman. 28

29



### You have the data. You will see the study that he is 30



### conducting. There have been studies where the animals 31



### were exposed for three days. Prior to the SAP in 2010 was 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### a paper by Cooper et al. in 2007 where there was a LOAEL 1



### of 6.25 milligrams per kilogram after exposing the animals 2



### for four days. 3

4



### And these are cycling animals, so they were dosed 5



### throughout one estrous cycle. That was discussed 6



### extensively in the Sept ember report or the panel meeting. 7



### And we came back upon request from OPP and finished out 8



### that dose response, and they performed a benchmark dose 9



### and found that the significant change occurred at 2.56 10



### milligrams per kilogram per day. That is a 4

- day 11



### exp osure. 12

13



### That is not too far different than the LOAEL that was 14



### reported or derived from the Morseth where she dosed for 15



### 28 weeks. And that study was also the one where the

-- I 16



### mentioned the estrous cyclicity was effected. So in that 17



### one there was an ef fect that the same level as there was 18



### for LH. 19

20



### And then the other ones there

-- we have already mentioned 21



### the higher levels or higher concentrations that were 22



### required to perturb estrous cyclicity in the shorter 23



### durations; the one, the four and the 21

- day exposures. 24

25



### So again, the point being that if you want your most 26



### sensitive measure for perturbations of LH

- dependent 27



### outcomes, look at LH, and look at it under the right 28



### circumstances and you will find those doses. 29

30



### And again, this just going bac k to the rationale for that 31



### -- and I highlighted it in green

-- that we see the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### adverse outcomes are consistent with the LH or alter GnRH 1



### mode of action, and therefore, the proposed mode of action 2



### for development effects shares considerable overlap of the 3



### proposed mode of action for carcinogenicity. 4

5



### Now that was to say that, okay, you saw your mammary 6



### glands that were dependent on LH. You see these other 7



### adverse outcomes. And that these neuroendocrin actions of 8



### atrazine are probably the dominant mech anism by which 9



### atrazine exerts its reproductive and developmental 10



### affects. 11

12



### So again, if you protect for effects on the hormone itself 13



### you should be protecting for the effects of the chemical 14



### on the reproductive and development physiology. 15

16



### I cannot get away without showing the slide of some LH 17



### data. These are the typical kinds of results that you 18



### see. This is actually a study from Fredis et al. where 19



### they had measured not only the parent compound, or looked 20



### at the effects of the parent compound an d the dose 21



### response, but looked at also the different metabolites. 22



### And I put in there DIA as one of the ones, and we naively 23



### thought we could dose equimolar doses of atrazine and DIA 24



### based on what we applied. But the point is that, when you 25



### do that you d o see dose responses that are not that 26



### different, where you see a suppression of the peak. 27

28



### And again, this was coming in at about

-- I think in that 29



### study our lowest dose was 6.25 or something

-- but these 30



### were coming in about 12.5 for atrazine as bein g 31



### significant at the peak and then the equimolar dose of the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### intermediate metabolite DIA came in at 10 milligrams per 1



### kilogram. 2

3



### And then, to get back at the toxicity pathway and the mode 4



### of action

-- but again, where we are with this, I think, 5



### after 15 years of looking at the effects of atrazine and 6



### how it influences the neuroendocrine function, it is sort 7



### of disappointing from the standpoint that, as you go 8



### across that adverse outcome pathway from where the 9



### toxicant interacts with the cells and disturbs or binds to 10



### a receptor or alters DNA or some protein and you see 11



### changes in activation of the genes or the production of 12



### different protein, we are really limited in our knowledge. 13



### There have been a number of papers, and that April SAP 14



### showed that there h ave been a number of papers that have 15



### been published, but there are no clear linkages and story 16



### that I think can be told. 17

18



### There is somewhat of a consistency in that atrazine 19



### somehow disrupts the cyclic AMP

- dependent cascade, but 20



### that‟s pretty diffuse eff ects that you can see. And to be 21



### able to link that to the particular alterations in the 22



### pulsatile release of GnRH; I think that is the key there, 23



### is that if you got back to the primary molecular or 24



### cellular change that is consistently seen in these studie s 25



### by different labs, is that those GnRH neurons do not seem 26



### to be as active under atrazine as they are compared to the 27



### controls. 28

29



### There is work done by Foradori where they looked at the 30



### cFOS staining and activity of those neurones, and you see 31



### it is down and it can be correlated roughly with the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### decrease in pulse events as well as the decrease in LH. 1



### Where we have the stronger evidence though is highlighted 2



### in yellow. In my mind, the altered signalling is the GnRH 3



### pulses. 4

5



### We have a lot of evidence tha t supports the altered 6



### physiology, the disruption of homeostasis tissue, changes 7



### in tissue development, as I mentioned

-- not necessarily 8



### always with LH that prostatitis was that one study that 9



### was done and the other outcome. 10

11



### So, still LH seems to be the key event for the majority of 12



### the adverse outcomes. It is quite strongly linked to some 13



### change in neural signaling coming out of the brain, but 14



### what is really taking place prior to that, we have limited 15



### knowledge. 16

17



### Now I am going to switch a little b it and address one of 18



### the requests from the September 2010 SAP. And if I seem a 19



### little uncomfortable in this it is because this is really 20



### a little bit outside my life space mammary gland

-- tumor 21



### evaluations

-- but my colleague Jerome Goldman is here if 22



### q uestions come up for it. 23

24



### There is a difference. The Fenton study shows 25



### consistently that there appears to be some type of 26



### developmental delay in the mammary glands of rats when the 27



### mother is treated gestationally, and you will look at the 28



### offspring. 29

30



### In attempt to replicate the Fenton work

-- that is the 31



### Rayner/Enoch papers up there

-- Hovey did a rather 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### extensive study looking at the same strain of animals and 1



### used more objective techniques or quantitative techniques 2



### to evaluate development. He pr esented that data here in 3



### September and could find no difference across the 4



### different life

- stages measured or doses that were used. 5



### Okay? You guys are very familiar with that. 6

7



### One of the questions that came up was is it a technique 8



### issue. Is it the m easurement issue as opposed to what you 9



### are seeing issue? So OPP requested that

-- we were at the 10



### time running a gestational study where we were dosing dams 11



### with atrazine at different doses from 1 to 100 milligrams 12



### per kilogram, gestation day 14 to 21. A nd those animals

- 13



### - we did it for a totally different purpose, but some of 14



### the offspring were available for looking at mammary glands 15



### and Jerome Goldman

-- I want to say he agreed to, in his 16



### lab, evaluate those and try to use both the quantitative 17



### and qual itative measures that have been published. 18

19



### So the animals that were available to him

-- and this was 20



### an important note in even Sprague

- Dawley rats

-- the 21



### animals that were available to him were 45 days of age. 22



### The animals were available to him just bef ore 45 days of 23



### age, and that happened to be the age at which the workshop 24



### on mammary gland tumors suggest it would be the best time 25



### where they were getting the most consistent data feedback 26



### when they did the round

- robin evaluation of different 27



### ages. 28

29



### So Jerome Goldman just said, "Yeah. I'll go ahead and 30



### look at those animals at postnatal day 45 using both the 31



### quantitative and the qualitative measures." And he worked 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### with different individuals to make sure that the Fenton 1



### data subjective scale that she u sed was the same scale 2



### that she used, with working with some of her former 3



### technical staff. 4

5



### And also, with getting information on different sources on 6



### how the quantitative measures were to be made. And so he 7



### did that study and that study was published by Lori Davis. 8



### I think it jut came out about a month ago. 9

10



### I just want to show the summary of the two different 11



### techniques so that you can see what is going on here, at 12



### least on postnatal day 45 in the Sprague

- Dawley females. 13



### These are the quantitati ve evaluations. What Jerry 14



### looked at was the branching in a particular segment of the 15



### mammary gland 3 by a 3 millimeter square of the slide. 16

17



### He looked at the number of terminal ends buds present in 18



### the animals and he looked at the distance from the ly mph 19



### node to the most distal portion of the gland. These 20



### measures are familiar to some of you guys. I have seen 21



### them and they seem relatively straight

- forward. But the 22



### important point here is he has his number of animals 23



### evaluated noted there in white in those bars

-- and there 24



### does not seem to be a difference, or he could not find a 25



### difference in any of those measures across that wide range 26



### of dosing. 27

28



### Now, if you notice up there, these are animals that were 29



### dosed twice a day

-- but we also did animals that were 30



### dosed once a day; a higher dose hitting them up to a 31



### hundred

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### The subjective or the qualitative scale measures that were 2



### made are shown here, comparing just 100 doses in this case 3



### against the controls . And again, this is both for the one 4



### dose a day on your left and the two doses a day on your 5



### right. And again, they could not identify any difference. 6

7



### And Jerry can go into the details of this study, but the 8



### way this study was run is there were three individuals who 9



### went through the scoring techniques, then they went 10



### through the same way to develop the range of scores that 11



### they could see. Once they agreed on that, they came back 12



### and blindly and independently looked at all the slides and 13



### then came bac k and broke the code and also looked at 14



### integrator reliability and those kinds of things, and they 15



### are all in the paper. 16

17



### So, the bottom line here is that, again, this is a limited 18



### answer to your question. It is postnatal day 45. They 19



### are Sprague

- Dawle y rats, so these are some issues that may 20



### or may not be important. But in this kind of attempt to 21



### get at the question of whether or not there is a 22



### difference, no difference could be found with either or 23



### any of those type measures. 24

25



### So to summarize, t he reproductive and developmental 26



### effects in the rat, like we were looking at delayed 27



### puberty, ovarian cycling, full

- litter resorption; they are 28



### all consistent with a primary mode of action of atrazine 29



### on the HPG and on LH secretion. And the alterations i n 30



### serum LH provide the lowest LOAELs and NOAELs available. 31



### And these serum hormone measures serve as a sentinel for 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### two of the three adverse outcomes identified; that is 1



### puberty and ovarian function. 2

3



### We are not a hundred percent certain about the FLR b ecause 4



### of the limited number of doses that we chose and things, 5



### but I am pretty confident that we could say that also 6



### about the full

- litter resorptions. 7

8



### And although the proposed mode of action for prostatitis 9



### is quite different than the LOAELs and NOAE Ls for that 10



### effect, are below those that we see when we look at 11



### adverse outcomes or the actual measurements of luteinizing 12



### hormones. So, by default, the argument is, is that we are 13



### protecting against prostatitis, as well, if we use the LH 14



### measures as our point of departure. 15

16



### Now, this is the final section of my presentation, and 17



### again, it is to go over some work that has been done to 18



### address one of the questions that was posed in the 19



### September SAP where the panel was struggling with the 20



### dosing duration s and what is going on and how long you 21



### have to dose. 22

23



### We had, if you will, limited data. At the time, four days 24



### was the shortest day that we had to complete dataset. And 25



### there was questions about what one single dose would do 26



### and what two doses or

-- is do you need four doses and you 27



### were not seeing anything with one dose and those kinds of 28



### things. 29

30



### So this is drawn right out of their comments. It says 31



### that it is clear that identifying that greater than one 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### pulse of exposure to atrazine is necessar y for attenuation 1



### of the LH surge. For example, single doses of over 100 2



### administered on the morning of proestrus did not alter the 3



### characteristics of the LH surge occurring the same day. 4



### And I will show you that dataset in a moment because it is 5



### kind o f curious the way it happened, but it is true; there 6



### was no effect with single high dose in the study that we 7



### did in 2000. 8

9



### Additionally, data clearly demonstrate a once daily dose 10



### for four days and beginning of the day of estrus can 11



### induce a significant inhibition of the LH surge peak, and 12



### that was the data that was scrutinized and scrutinized in 13



### September, and so, there is a big difference between no 14



### effect and four days later of LOAEL of about

-- whatever 15



### that benchmark does was

-- 2 point something. 16

17



### In this instance, a dose response is observed. However, 18



### what is not clear

-- and this is the key

-- however, what 19



### is not clear is, if less than four days, but greater than 20



### one days' exposure is sufficient to alter the LH surge. 21



### Further complicating the matter, it is not clear if a four 22



### day exposure, beginning on a different day of the estrus 23



### cycle, and you start to note all these permutations could 24



### lead to differences. 25

26



### So understanding the relationship between the duration of 27



### exposure in the phase of the cycle will be key in 28



### translating rodent data for humans for the risk

- assessment 29



### purpose. So actually, there is a tremendous amount of 30



### work behind that paragraph, if you tried to answer all 31



### those questions in that paragraph. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And, again, we tried to address some of those issues, and 2



### in doing so, tried to incorporate some of the information 3



### that we had reviewed in the April SAP about the potential 4



### effects of atrazine on the adrenal access where we saw, 5



### and others have reported a significant increase in 6



### adrenal, progesterone and corticosterone after a single or 7



### three or four doses. 8

9



### So, what we did is design a study where

-- we did not do 10



### it in intact animals, again, because we had enough 11



### headaches just dealing with some of the changes in the 12



### ovaria n hormone. So knowing that atrazine also 13



### increases progesterone from the adrenals, we decide what 14



### we would do is evaluate one, two and four days of exposure 15



### to atrazine in animals that were treated with estradiol or 16



### not. And the rationale behind this st udy is to understand 17



### the very, very basic observation about the role of 18



### estradiol and progesterone on regulation of LH. 19

20



### An animals that is primed with estradiol first, you will 21



### see an LH surge three or four days later, but it is a very 22



### modest one. Th at is what is shown in blue in this figure 23



### here, and that is usually about six to 10 nanograms per 24



### mil at the peak. What I am showing here is a plot the way 25



### that

-- you are going to see the data where you are 26



### looking at the peak on the fourth day of expos ure, and the 27



### peaks are aligned based on the highest value that w see 28



### for LH. So zero is the peak and the surge curves on 29



### either side. And you can look at the area that it curve 30



### and do some other analyses with this. 31

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### If you give that animal three days o f estradiol and on the 1



### fourth day you dose it with progesterone

-- in this case, 2



### subcutaneously, you see it facilitates the LH surge or 3



### dramatically increases the amount of luteinizing hormone 4



### that is released. 5

6



### Estradiol prepares the hypothalamic pituit ary tissues. 7



### Estradiol produces progesterone receptors. Progesterone 8



### receptors are there and, boom; you get one of the only 9



### examples that I know of synergy, if you will, where you 10



### see this tremendous increase over estrogen alone if you 11



### add progesterone. 12

13



### If you flip that order

-- and this is where timing gets to 14



### be important

-- where you put progesterone in the animal 15



### first, or concomitantly with estradiol then you are not 16



### going to have those preparatory changes take place in the 17



### hypothalamic and pituit ary. And you will get nothing on 18



### the fourth day and that is what the green line is supposed 19



### to represent, where you hit P+E or progesterone followed 20



### by E. 21

22



### So the hypothesis was this; that if we are going to 23



### evaluate the role of atrazine

-- these one

- day, two

- day, 24



### three

- day kinds of exposures

-- we should take into 25



### account what it is doing not only to LH, per se, but also 26



### the other hormones that are involved in this. Even if we 27



### have ovariectomized animal, you had the adrenal hormones. 28

29



### And our hyp othesis was that atrazine should work like 30



### progesterone because one dose, we know, increases 31



### progesterone from the adrenals. And if we dosed once in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### an estrogen

- primed animal we should facilitate the surge; 1



### not knock it down; increase it. And if we dose 2



### consistently for three days with atrazine, and if it does 3



### induce that progesterone each day, then it should start to 4



### attenuate the surge. So that was sort of not really what 5



### you would glean from the literature, but we went back and 6



### we looked at our 2000 s tudy

-- actually OPP went back and 7



### looked at our 2000 study and said, "You didn't get any 8



### effects in one day but

-- " 9

10



### When we did, this is actually what we had. And if you 11



### look at it

-- this study was done where we dosed the 12



### animals with estradiol for the preceding three days and 13



### then gave atrazine once. And we killed the animals by 14



### decapitation. So we could not get area under the curve, 15



### we could not line up the peak heights and all that kind of 16



### thing. 17

18



### And animals do not always have the same exact, precisely, 19



### the same peaks. But I was surprised, what is circled 20



### there is a tendency for there to be an increase as we 21



### increase the dose of atrazine, so that was curious. So 22



### maybe one day, if you did the study right you might see 23



### that a single dose does do something. 24

25



### And this is the data that Jerry Goldman and his colleagues 26



### collected where they dosed animals with estradiol. They 27



### ovariectomized them and put the silicon estrogen

28



### containing capsule subcutaneously for three days. On the 29



### fourth day, in stead of dosing with progesterone, they 30



### dosed with atrazine at 12:00, 1:00, 1300, and low and 31



### behold, you see there was a significant increase in the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### peak height and the area under the curve for LH, which 1



### tells us now that this is a single dose. We are ha ving an 2



### effect on regulation of LH and that it is consistent with 3



### our prediction that this might have something to do with 4



### adrenal progesterone. 5

6



### If you dose for two days, however

-- and this is

-- again, 7



### all these data are in the docket. We use zero and 100. 8



### These data were using zero and 100 milligrams per 9



### kilogram. The point is that there is no difference when 10



### you dose for two days. We saw no effect. There was a 11



### slight decrease in the area under the curve, but if you 12



### look on the right hand panel th ere, it is down 77 percent 13



### after 24 hours. After six hours it was up 181 percent, 14



### the amount of LH secretes. 15

16



### So there is a big difference between day one and day two, 17



### but just the way we analyzed it did not really demonstrate 18



### that. And then again, if you dose for the four days, as 19



### we have in the past, you see that there is the suppression 20



### of the surge or the peak as well as a decrease in the area 21



### under the curve. 22

23



### I do not know whether we are going to help answer that 24



### question about how long to d ose and what the different 25



### durations would be, but you can see that there is nothing 26



### magical about that 4

- day. The closer we get to 27



### understanding the basic physiology or interaction of the 28



### steroid hormones with this system, that maybe you can get 29



### at what is going on a little more clearly. So, we do have 30



### data now on one, two and four doses that there is a 31



### significant increase after one; two does of atrazine 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### revealed no real change in the LH from controlled animals, 1



### and four doses had the previously describ ed decrease in 2



### LH. 3

4



### Again, all changes in this case where we are substituting 5



### atrazine with changes in what might be imagined, if you 6



### will, from the changes that we see in adrenal 7



### progesterone. And it is important that we note at this 8



### point that these c hanges just speak to the duration of 9



### dosing. I do not think they really tell us anything or 10



### imply anything about the adverse effects of increased 11



### luteinizing hormone in these animals. 12

13



### So back to our mode of action and toxicity pathway data. 14



### I think th ere is a wealth of data that talks about 15



### alterations and

-- I think there has got to be, now, at 16



### least 20 studies looking at changes in LH after exposure 17



### to atrazine under a variety of different conditions and 18



### they all come from the ORD lab. Several diffe rent labs 19



### around the country have worked on this. 20

21



### It is clear that you can see changes in reproduction and 22



### development. The linkage is back to the toxicity pathway, 23



### however, are still challenging and we do not really know 24



### what is taking place back ther e. But, again, the data 25



### that we have to date really, I think, supports the 26



### argument that if you use the LH measures that exist, and 27



### that they exist under, and the rationale that they are 28



### precursory changes to the changes in the physiology that 29



### using LH as the sentinel or the marker for the point of 30



### departure in the risk

- assessment, it should be on safe 31



### grounds. Thank you. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Thank you, Dr. Cooper. At this point, I 2



### would like to sort of group or questions or clarifications 3



### together for doctors Bradbury, Fowle, Mendez and Cooper, 4



### if you would. So anybody have any questions or 5



### clarification? 6

7



### DR. DANIEL GRIFFITH : Numbers that you showed in the charts 8



### with the percentage changes, are they a factor of the 9



### smallness of the numbers or are th ey actually meaningful 10



### percentage changes? 11

12



### DR. RALPH COOPER : Which slide? 13

14



### DR. DANIEL GRIFFITH : The ones at the very end; these ones. So 15



### those percentage changes that you are showing, are they 16



### more a function of relatively small numbers or are they 17



### the meaningful percentage changes? 18

19



### DR. RALPH COOPER : Well, it is just the percent. The number of 20



### animals is quite large. I think there were 10 animals in 21



### each one of those groups. So you have got a good dataset 22



### there. That percentage is just the percent

-- you have 23



### the controls, and then what was the percentage of LH that 24



### was produced in the treated animals. 25

26



### DR. NELSON HORSEMAN : I just have one question for 27



### clarification. The peak levels in the three LH 28



### experiments you showed us, in the controls, wh ich are the 29



### blue bars, are a little different from experiment to 30



### experiment. Could you comment on whether those are 31



### meaningful? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. RALPH COOPER : One thing that is important, and we looked 2



### at this so the answer is no. But it is important. And 3



### this spe aks to the way that you measure the hormone and 4



### what your control values look like. I just ran through 5



### them real quickly, but we are looking at about four and a 6



### half

-- the question is whether or not our controlled 7



### animals varied in the different groups. We had the 8



### different days, okay? And they varied in this case, after 9



### four days of dosing they were approximately four and a 10



### half nanograms per mil at the peak. And then in this one 11



### they were up to six, which is

-- these are typical 12



### numbers. I have seen as low as three in the published 13



### literature. They are usually less than 10. And in this 14



### case you, again, were at four and a half, so I do not put 15



### much stock in that. And as a matter of fact, if you 16



### compare those statistically, there was not a differenc e. 17

18



### DR. NELSON HORSEMAN : These are not dose; these are control 19



### animals right? 20

21



### DR. RALPH COOPER : Well they get the vehicle. 22

23



### DR. NELSON HORSEMAN : The vehicle. The reason I ask is, 24



### because in the two

- day exposure the treated animals are 25



### significantly lo wer, but they are not different from the 26



### controls in the other two experiments, so it is a question 27



### of whether

-- 28

29



### DR. RALPH COOPER : No. The two days was not statistically 30



### significant. 31

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### DR. NELSON HORSEMAN : Oh, it is not statistically significant, 1



### it i s just the difference between the 77 and 180? 2

3



### DR. RALPH COOPER : Right. No, that is not significant either

, 4



### n either one of those. I am sorry. The point I tried to 5



### make of that was not

-- no. Two days was not different. 6



### If you did that study and kille d the next day, you would 7



### say, "Oh, there is no effect at all of atrazine on the 8



### surge." What I pointed out there was

-- I was struck, and 9



### it might just be my own weird way of thinking was that I 10



### was struck by a six

- hour exposure having that much LH 11



### relea sed, 181 percent of control and a peak height up to 12



### 10

-- that is pretty high for an estrogen

- only treated 13



### animal

-- and then dropping down within 24 hours to just 14



### the 77 percent. That is the only thing I pointed out. 15



### It's only statistically significant

-- we did not do a 16



### three

- day. The 4

- day was down. 17

18



### DR. KEVIN O'BYRNE : A very simple point of clarification. On 19



### the four days, you were giving atrazine on four days, 20



### starting from the time of the estradiol implant; is that 21



### correct? 22

23



### DR. RALPH COOPER : Co rrect; one o'clock. It was rat time, 1:00 24



### p.m. from the day of

-- and that is what we typically did. 25

26



### DR. KEVIN O'BYRNE : So on the two

- day treatment, was that two 27



### days into that treatment? So is it two days relative to 28



### the peak of the surge? Okay. Th ank you. 29

30



### DR. RALPH COOPER : The day before
, 20 whatever hours earlier. 31

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### DR. KEVIN O'BYRNE : 24 hours? 1

2



### DR. RALPH COOPER : No, not 24

-- 3

4



### DR. KEVIN O'BYRNE : 48. 5

6



### DR. RALPH COOPER :

-- 28 hours, 28 or 30 or something like 7



### that. 8

9



### DR. KEVIN O'BYRNE : Starti ng at 1300 hours. 10

11



### DR. RALPH COOPER : Yeah. 12

13



### DR. JAMES MCMANAMAN : Yes; just a point of clarification. 14



### There was some discussion in the September meeting about 15



### stress

-- this is for the mammary gland, slide 11

-- 16



### having an effect on the outcome. And I am just wondering 17



### did you consult with Dr. Fenton's group? Because she made 18



### a big point about the way these animals are handled can 19



### affect the outcome. And since stress could affect the 20



### hypothalamus, I am just wondering is there any kind of 21



### connection and was that controlled for at all? 22

23



### DR. RALPH COOPER : This study was run in four blocks, and one 24



### of the underlying reasons for running this study was to 25



### evaluate the role that gestational exposure to the dam may 26



### have on her pituitary adrenal access, and then what 27



### outcome that may have on the offspring. So in terms of 28



### stress, we were really quite fastidious, if you will, 29



### about the way we handled the animals. As a matter of 30



### fact, there was a lot of discussion about weighing them, 31



### even if we should weigh them , because we were concerned 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### whether or not that might compromise the potential effects 1



### that we were looking at from the gestational exposure. 2

3



### So we took a lot of care in making sure that we did not 4



### have any stress, and we did not have the cannibal

-- and 5



### these were Spragues. The cannibalism that was discussed 6



### there seems to be unique, I think

-- this is my opinion

-- 7



### to the Long

- Evans rats. A lot of times the Long

- Evans are 8



### just a little more fussier than the Spragues in terms of 9



### handling them during the perinatal period. 10

11



### DR. DANIEL SCHLENK : All right. Any other questions on adverse 12



### outcomes or mode of action? Okay. At this point, we will 13



### go ahead and take a 15

- minute break. We have lost our 14



### standard clock up here on the door here, so I am going to 15



### relegate to my watch, which I have 11 after. So let us 16



### come back at

-- let's say 25 after 10. Look on your cell 17



### phones; I guess that is the best way. 18

19



### DR. DANIEL SCHLENK : All right. Let ' s go ahead and get 20



### started, please. Our next presentation wi ll be the 21



### review of atrazine cancer epidemiology, and it will be 22



### presented by Dr. Carol Christensen who is from HED/OPP. 23



### Dr. Christensen? 24

25



### DR. CAROL CHRISTENSEN : Yes. Thank you and good morning. My 26



### name is Carol Christensen. I'm an epidemiologist with the 27



### pesticide program office. And over the next several 28



### slides I will be happy to review with you our assessment 29



### of the Atrazine Cancer Epidemiology literature. 30

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### So, as Dr. Mendez mentioned, EPA has presented its review 1



### of this database at two previous SAP panel sessions. In 2



### June of 2000, although other issues were discussed, EPA 3



### presented its assessment of epidemiological studies 4



### relating to breast cancer, ovarian cancer, prostate tumors 5



### as well as Hodgkin Lymphoma. 6

7



### As other EPA presenters have menti oned, in July of 2003, 8



### the agency convened an SAP panel to discuss prostate 9



### cancer specifically, primarily studies among an 10



### occupational exposed cohort of Triazine manufacturing 11



### plant workers. 12

13



### So, as a result of those external evaluations as well as 14



### othe r external evaluations and internal assessments, in 15



### October of 2003, EPA preliminarily concluded that the 16



### agency does not find any results among the available 17



### studies that would lead us to conclude that potential 18



### cancer risk is likely from exposure to atra zine. 19

20



### However, the agency committed to revisit this issue when 21



### additional epidemiology studies became available, 22



### particularly those from the agricultural health study. As 23



### Dr. Bradbury noted earlier, within the last several 24



### months, researched with the Ag

- Health Study have published 25



### an updated evaluation of the carcinogenic potential of 26



### atrazine in the human population. Those data are 27



### integrated within this presentation. 28

29



### And I will just note for your information that Dr. Laura 30



### Beane

- Freeman who is a co

- principal investigator with that 31



### study with the National Cancer Institute, is here today 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and available to address any clarifying questions you 1



### might have on the content of that research. 2

3



### So, given that new information is available, the current 4



### evaluati on updates in extents our assessment of the 5



### atrazine cancer epidemiology database. 6

7



### So, what contrasts this review, perhaps, from previous EPA 8



### evaluations is our use of the draft framework for 9



### incorporating epidemiology into risk

- assessment. As 10



### state d earlier, this framework was discussed with the SAP 11



### panel in February of last year. So using this draft 12



### framework, EPA described its methodology for identifying 13



### studies evaluating potential atrazine cancer risk in the 14



### human population. When looking at i ndividual 15



### investigations, we evaluated the strengths and 16



### limitations, considering factors such as the consistent 17



### application of inclusion and exclusion criteria, use of 18



### valid and reliable exposure assessment methodologies, 19



### outcome ascertainment and so on, as well as an evaluation 20



### of the potential for systematic error or bias in the 21



### study. These factors are, again, reflected within our 22



### draft framework for incorporated epi into risk

- assessment. 23

24



### Looking across the cancer epidemiology database and moving 25



### to integrating with the experimental toxicology database, 26



### EPA utilized the framework considering the postulated mode 27



### of action, key events, as well as the, for example, 28



### observation of exposure response relations across the 29



### suite of epidemiology studies avail able on a particular 30



### cancer site, the strength of the measured association and 31



### the consistency of that association across the studies, in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### addition to scientific judgments. So bringing together 1



### the experimental toxicology data and the observational 2



### epidemi ology data
, using the general principles described 3



### in this framework, today we are presenting our preliminary 4



### conclusions regarding atrazine cancer epidemiology 5



### literature. 6

7



### So, EPA performed a comprehensive literature review 8



### purposely broad in nature. We search major biomedical 9



### databases, Pubmed, Web of Science, utilizing a search 10



### string developed with the aid of an EPA referenced 11



### librarian, for example. Our inclusion criteria, again, 12



### were broad. We considered studies that measured either 13



### atrazine or triazines in relation to any cancer outcome. 14

15



### We did however exclude investigations for which no full 16



### text manuscript was available. Some of the initially 17



### identified investigations were exposure only. We excluded 18



### those that were editorial in nature. 19

20



### So, having identified a suite of studies potentially 21



### meeting our inclusion and exclusion criteria, several EPA 22



### scientists from across the agency met to qualitatively 23



### adjudicate the relevance of those studies to the question 24



### of atrazine carcinogenicity among humans. 25

26



### So, overall, we've identified 40 studies in the current 27



### epidemiology lit review. That span in publication date 28



### between the mid

- 1980s through the very recently published 29



### Atrazine cohort analysis by researchers with the Ag

- Health 30



### Study. So these 40 studies are generally grouped in the 31



### following broad categories, several investigations of 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### endocrine and reproductive system. Tumors were evaluated, 1



### breast cancer, ovarian, prostate cancer and thyroid 2



### tumors. 3

4



### In addition, several investigation s of the potential 5



### relation between atrazine or triazines with multiple 6



### myeloma, non

- Hodgkin lymphoma and other sub

- types of 7



### lymphohematopoietic cancers, which is particularly 8



### relevant because it's understood that different sub

- types 9



### may indeed have differ ent etiologies. 10

11



### In addition, we identified a few studies looking at other 12



### anatomical cancer sites, two studies on glioma published 13



### by researchers with NIOSH, and two on cancers in the 14



### paediatric population. And again, because research from 15



### the Ag

- Healt h Study was deemed to be particularly 16



### important and relevant to the question of atrazine 17



### carcinogenicity in the human population, given the 18



### strength of the design and methods of that government

19



### sponsored study, for the sake of completeness, we've 20



### delineate d each of the atrazine cancer risk estimates made 21



### available over time since 2003, in either the two cohort 22



### evaluations, which we will discuss, and the sixth Nested 23



### case control evaluations on specific cancer outcomes. So 24



### these are also briefly summarized. 25

26



### Regarding prostate cancer, as Dr. Mendez briefly alluded 27



### to, EPA had previously reviewed studies of an occupational 28



### cohort of Triazine manufacturing plant workers whereas 29



### there was an initial observation of an increased incidence 30



### of prostate cancer amo ng men who were actively employed in 31



### this triazine manufacturing plant. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Additional analyses, including presentation to the SAP in 2



### July of 2003 concluded that the provision of a prostate 3



### cancer screening program, or the availability of the 4



### prostate speci fic antigen or PSA test among two men 5



### employed at this plant, was likely, at least, a partial 6



### explanation for this initial observation of an increased 7



### risk for prostate cancer. I n fact, follow

- up studies 8



### published subsequent to the last SAP review

-- and that‟s 9



### the case control analysis within this occupational cohort 10



### in which authors were able to measure individual exposure 11



### levels

-- seemed to support that conclusion when 12



### stratifying among men who received at least one PSA test 13



### over the course of their em ployment. No evidence of an 14



### association was observed between triazine and prostate 15



### cancer. There are other factors that support this 16



### conclusion delineated in the written material. 17

18



### So moving on using data from the California State Cancer 19



### Registry, pest icide use information also reported to that 20



### state

-- researchers reported evidence of a correlation 21



### between atrazine and prostate cancer among black men. 22



### This is based in an ecologic study in which atrazine 23



### exposure was measured at the group level, so it lacked 24



### individual exposure measures. 25

26



### Using similar data sources, and that‟s the case control 27



### study among men who were part of a farm worker labor 28



### union, authors reported moderately elevated risk of 29



### prostate cancer in association with cyanazine. And I w ill 30



### just briefly note that this is the only study included in 31



### our review that did not actually meet our inclusion 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### criteria. It is the only one. We reflected it here 1



### because this study was brought to the SAP in 2003, and so 2



### its presented here for the sake of completeness. 3

4



### So, within the Ag

- Health Study, there are three point 5



### estimates to consider, or three evaluations, I suppose, to 6



### consider. In 2003, a preliminary case control study did 7



### not observe an association between ever use of atrazine 8



### over the lifetime in prostate cancer. 9

10



### Similarly, in a preliminary, and in a very recent follow

11



### up cohort analysis within that study, researchers did not 12



### observe evidence of an association with prostate cancer. 13



### Looking at quartiles and quintiles of atrazine expos ure, 14



### the risk estimates do not significantly differ from the 15



### null , nor, obviously, was there a suggestion of a trend. 16

17



### So, considering these available studies, those were the 18



### stronger design in methods, particularly the Ag

- Health 19



### Study, I do not seem to suggest a positive association in 20



### those population studied. So this statement is supported 21



### by the fact that there is relatively consistent 22



### observation of essentially no association across study 23



### design and across target population, when you consider the 24



### ro le of detection bias in that early observation of an 25



### association. And I will note as well that both a 26



### preliminary cohort analysis published in 2004, as well as 27



### the resent follow

- up study from the Ag

- Health Cohort were 28



### performed with sufficient statistical power to detect a 29



### relationship with atrazine if one exists. 30

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### However, looking across this database, there are 1



### relatively few studies, 10 included, many of which the 2



### earlier ones reflect an aggregate exposure assessment 3



### methodology. The latter ones with stronger exposure 4



### assessment methods are primarily conducted among Caucasian 5



### male population. And we know that the initial 6



### correlation, noted in the ecologic study published in 7



### 1998, has not yet been replicated in other populations or 8



### in that population. 9

10



### So, considering the breast cancer epidemiology database in 11



### relation to atrazine exposure, three ecologic studies 12



### provides some weak and somewhat inconsistent evidence of a 13



### possible relation, on initial study observed a significant 14



### 10 to 20 percent incr eased risk, however, this was not 15



### replicated in follow

- up. Researchers attempted to use the 16



### same study design and the same population with very 17



### similar methods and did not repeat that initial finding. 18



### More recently, in an ecologic study in England, 19



### resea rchers observed potential association in only one of 20



### two of the geographic studies that‟s included in that 21



### study, so therefore, internally somewhat inconsistent. 22

23



### And again, utilizing data reported to the California 24



### Cancer Registry, authors did not obser ve an association 25



### between atrazine and breast cancer among California 26



### Latinos, which is a target population. The study also 27



### utilized an ecologic

- type exposure assessment method where 28



### atrazine was determined at a group level and assigned to 29



### individuals. 30

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### In a population

- based case control study in the state of 1



### Wisconsin, authors measured atrazine in drinking water, 2



### actually in well water among residents in rural areas. 3



### These authors utilized a relatively robust exposure 4



### assessment method. They used a n arcGIS method to 5



### interpolate atrazine exposure over time and across 6



### sampling sites. However, the range of exposure was 7



### somewhat narrow. So in this study, again, no observation 8



### evidence association was reported. 9

10



### And within the Ag

- Health Study, there are two 11



### investigations to consider. Among female spouses of 12



### enrolled pesticides applicators, authors did not observe 13



### evidence of a relation between atrazine and prostate 14



### cancer, and this is only using the ever/never metrics. So 15



### it has a woman ever been indirectly exposed to atrazine 16



### within this cohort. 17

18



### And then, in the recent updated evaluation, authors were 19



### able to look at 36 cases of breast cancer among women who 20



### were directly exposed or who actually were licensed 21



### pesticide applicators. In this stud y authors, again, did 22



### you observe evidence of an association with breast cancer. 23

24



### So across these data, although somewhat limit, they 25



### indicate that a strong positive association is unlikely. 26



### Consistent results; we observe consistent results across 27



### the a vailable analytic studies which were performed in 28



### high use areas, which is the strength of the database. 29



### Each of these studies was able to measure and utilize 30



### breast cancer risk factor variables and its assessment of 31



### the association. And the range of exp osure assessment 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### methods were significant in that, that one study utilizing 1



### the ArcGIS method for interpolation, and the measurement 2



### of both direct and indirect exposure in the Ag

- Health 3



### Study is a strength of this database. 4

5



### However, the limitations of exposure include the 6



### relatively narrow range reflected in the population

- based 7



### study in Wisconsin in addition to the use of the 8



### ever/never metric and the ecologic exposure assessments in 9



### several of the available studies, in addition to a small 10



### number of ex posed cases ; s o overall, strengths and 11



### limitations of this database. 12

13



### Concerning ovarian cancer, two ecologic studies are not 14



### supportive of an association when observed an inverse 15



### risk; the latter observed no evidence of an association. 16

17



### In a populati on

- based study performed a couple of decades 18



### ago, authors observed three

- fold elevated odds of ovarian 19



### cancer in relation to triazine exposure. This is a study 20



### previously reviewed by EPA and brought to the panel in 21



### June of 2000. 22

23



### Critiques at that tim e included the lack of adjustment for 24



### other pesticides and the relatively small sample included 25



### in this study. Again, more recently utilizing information 26



### reported to the California State Cancer Registry and 27



### Pesticide Use Data supplemented by self

- administ ered 28



### questionnaire, authors reported limited evidence of an 29



### association between triazine and ovarian cancer and little 30



### evidence of an association between atrazine and ovarian 31



### cancer. However, as noted, these assessments were based 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### upon a small number of a trazine or triazine

- exposed 1



### ovarian cancer cases. Authors noted that fewer than 10 2



### percent of that sample reported use of triazines. 3

4



### And within the Ag

- Health Study, again, the recent 5



### evaluation made available within the last several months 6



### observed t hree

- fold elevated odds of ovarian cancer in 7



### relation to ever use of atrazine. So again, this is among 8



### women who are licensed pesticide applicators. However, 9



### due to the fact that there were only nine cases of ovarian 10



### cancer available for analysis, four o f which were exposed 11



### to atrazine, authors were only able to evaluate the 12



### ever/never exposure metric in this study. 13

14



### So, although available epidemiology database is limited, 15



### we note that positive associations were observed across 16



### these studies. However, at this time, alternative 17



### explanations may likely exist and cannot be excluded. 18

19



### Strengths of this database include the observation of 20



### positive associations in high quality analytic studies, 21



### including the Ag

- Health Study. A few of these 22



### investigations w ere hypothesis testing in nature and were 23



### conducted in a highly occupational exposed population of 24



### women. However, the small number of studies and the small 25



### number of exposed cases must be noted as a limitation. 26

27



### So again, the recent Ag

- Health evaluatio n was actually 28



### among the only point estimates that we identified in the 29



### database, looking at a potential association between 30



### atrazine and thyroid cancer. Within that study, authors 31



### observed evidence of a four

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### cancer in the m iddle and upper exposure range trend 1



### significant at the point (0.10) level. The Ag

- Health 2



### Study, as I've alluded to over the course of this 3



### presentation, is a large scale prospective study with many 4



### strengths and design and methodology. 5

6



### Authors, with r espect to the thyroid cancer finding, note 7



### that there was only one case of thyroid cancer among women 8



### enrolled in the study, so therefore, this evaluation is 9



### among men only. Authors were able to adjust four body 10



### mass index, or BMI, which has quite recent ly been shown to 11



### be a risk factor for thyroid cancer. However, a 12



### limitation noted by EPA is the grouping of thyroid cancers 13



### together, and different sub

- types of this tumor type may 14



### indeed have different etiologies. 15

16



### So, based upon only one epidemiologi c study or results in 17



### which a positive association was observed, the data are 18



### somewhat inclusive at this time and replication in other 19



### populations, perhaps with a larger number of exposed 20



### cases, is required before we can determine this causal 21



### nature of thi s potential association. 22

23



### Strengths of the study are

-- again, it is based within an 24



### epidemiology study that has relatively strong design and 25



### methods in which an exposure response was evaluated. But 26



### it is only one point estimate available at this time i n 27



### which thyroid cancer sub

- types were grouped together. 28

29



### So there were actually a number of studies to consider 30



### regarding the potential association between atrazine or 31



### triazine and lymphohematopoietic cancers; leukemias, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### lymphomas, multiple myeloma

-- an d they are listed briefly 1



### in the slides. 2

3



### So, in the mid

- 1980s, the National Cancer Institute 4



### conducted a series of population

- based case controlled 5



### studies in the Midwest in which they evaluated several 6



### pesticides, I think 38 specific herbicides, includ ing 7



### atrazine, several dozen insecticides and other types of 8



### pesticides. So

-- evaluated many different pesticides in 9



### association with these cancer outcomes. 10

11



### So, looking across these three studies, authors did not 12



### observe an association between atrazine , specifically, in 13



### either multiple myeloma or leukemia. EPA notes that these 14



### studies are relatively strong in design; the low potential 15



### for systematic error. However, the studies were 16



### reflective of a relatively small number of exposed cases, 17



### in some inst ances. 18

19



### In our literature search, we also identified two 20



### evaluations which are hospital

- based case

- controlled 21



### studies conducted in France. They are connected by the 22



### same group of researchers using similar methods, but at 23



### different points in time ; s o, ag ain, looking at several 24



### different pesticides, including atrazine. So across these 25



### two studies, authors did report some evidence of non

26



### significant elevated risk in association with triazine 27



### use. These authors evaluated triazines only. 28

29



### A significant as sociation with hairy cell leukemia

-- 30



### that‟s the HCL acronym that I did not define for you

-- 31



### were also noted by EPA. These studies, particularly the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### latter study by Ochi in 2009 reflected good quality 1



### exposure assessment. I think it was self

- reported 2



### ex posure information administered by a trained interviewer 3



### with a small validation study included. However, the 4



### studies were, again, reflective of a few numbers of cases 5



### and did not adjust for the exposure to other pesticides 6



### over the relevant exposure per iod. 7

8



### So, with respect to non

- Hodgkin lymphoma, the same set of 9



### population

- based studies conducted by the NCI in the mid

10



### 80s looked at atrazine in association with NHL. So, 11



### initially, some non

- significant positive associations were 12



### reported. However, u pon adjustment for the exposure to 13



### other pesticides, those associations attenuated 14



### significantly and became statistically non

- significant. 15

16



### In a pooled analysis using hierarchical regression 17



### techniques, so authors were able to co

- adjust for exposure 18



### to t he 47 other pesticides evaluated across these studies. 19



### Authors brought together the individual observations 20



### across the three case

- controlled studies into kind of one 21



### big pool of the study, and again, looked at atrazine 22



### exposure, as well as exposure to oth er pesticides in 23



### relation to NHL and reported an odds ratio of 1.5, which 24



### was statically significant. 25

26



### Within, again, the same group of studies, other 27



### investigators were able to measure the presence of the 28



### t(14:18) chromosomal translocation. This chromo somal 29



### anomaly is thought to be a risk factor for NHL in the 30



### human population. 31

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### So, among participants who were positive for the t(14:18) 1



### translocation, authors reported an elevated odds of non

2



### Hodgkin lymphoma. However, this is the only study of the 3



### p otential effect modifying role of this chromosomal 4



### translocation available. 5

6



### Within the Agricultural Health Study cohort, while the 7



### initial cohort study on atrazine exposure, looking at 8



### various cancer outcomes, reported some suggestive, not 9



### significant, associations with non

- Hodgkin lymphoma and 10



### multiple myeloma, this finding was not replicated in the 11



### recent follow

- up study with over twice the number of non

12



### Hodgkin Lymphoma cases. 13

14



### So across NHL, multiple myeloma, leukemia and several 15



### different sub

- ty pes of lymphohematopoietic cancers for 16



### which these authors had the sufficient number of cases to 17



### evaluate

-- including evaluation of an exposure

- response 18



### trend

-- across each of these risk estimates the odds 19



### ratios did not significantly differ from one or from the 20



### null; so a lack of evidence of an association. 21

22



### So, among the available studies, those with stronger 23



### design and methods, again, do not suggest a positive 24



### association in the populations studied. The recent 25



### studies are prospective in nature. Aga in, the Ag

- Health 26



### Study reflects a large sample with the ability to evaluate 27



### exposure response and control for the use of other 28



### pesticides. 29

30



### Limitations of the database are the small number of cases 31



### for some of these sub

- types reflected in a few of the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### s tudies presented. The possible effect modifying role of 1



### the t(14:18) chromosomal translocation was observed in 2



### one, and only one, study with a relatively small number of 3



### cases and controls and has not yet been reproduced. And 4



### again, the target population across several of these 5



### studies is Caucasian male population. 6

7



### So very briefly, we also identified epidemiological 8



### evaluations of other cancer sites. Research with NIOSH 9



### looked at the association between glioma, a major type of 10



### brain tumor, and pestic ides including atrazine. These 11



### authors did not observe an association among either men or 12



### women. 13

14



### In addition to an ecologic study on instance of cancers in 15



### the pediatric population, there is one hypothesis 16



### generating a case controlled study produced by the 17



### researchers with the Northern California Childhood 18



### Leukemia Cohort. In this analysis, authors observed four

19



### fold elevated odds of acute lymphocytic leukemia in 20



### relation to triazine exposure. 21

22



### Authors modeled pesticide exposure using maternal 23



### residen ce as a proxy for pesticide exposure. And we note 24



### that the elevated association was observed in the midrange 25



### group, but not in the upper ranged groups. So the data 26



### lacked an exposure

- response trend

-- and this is the only 27



### study available on this cancer e ndpoint in the pediatric 28



### population. 29

30



### So, again, given the relative strengths of the design and 31



### conduct of the Ag

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### completeness, we have delineated each of the atrazine 1



### cancer

- specific point estimates available across the two 2



### cohort studies, and the six Nested case

- controlled studies 3



### made available since 2003. And overall, very briefly, 4



### authors did not report evidence of an association between 5



### atrazine in any of these cancer sites. 6

7



### So, available preliminary studies concerni ng these other 8



### anatomical sites are not strongly suggestive of an 9



### association. Several of these studies were hypotheses

10



### generating in nature among studies with relatively strong 11



### design, however they lacked a priori hypotheses. 12

13



### The one observation of el evated odds of pediatric acute 14



### lymphocytic leukemia is just that, only one observation. 15



### It has not yet been replicated in this database at this 16



### time. It's inclusive as to whether or not this 17



### association is a true one. 18

19



### So as we move toward integrating with the experimental 20



### toxicology database, I thought I would just take a moment 21



### to briefly summarize our view of the epidemiology datasets 22



### discussed. Concerning the lymphomas and leukemia, as well 23



### as prostate cancer, our preliminary conclusion is that the 24



### stronger studies are not suggestive of a positive 25



### association in those target populations evaluated; mainly 26



### white male pesticide applicators. 27

28



### With reference to breast cancer, thyroid cancer and 29



### ovarian cancer, the available epidemiological database is 30



### limited. However, some positive associations are 31



### observed. But at this time, alternatives cannot be 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### excluded; namely, the relatively small sample size, a few 1



### number of exposed cases across several of these studies. 2



### With respect to the relatively hetero geneous grouping of 3



### other anatomical cancer sites, at this time these data are 4



### not strongly suggestive of a positive association. 5

6



### So this slide summarizes information previously presented 7



### by other EPA presenters regarding the experimental 8



### database on the potential carcinogenic effect of atrazine. 9



### So the current cancer mode of action is mammary gland 10



### tumors in the rat due to the disruption of the 11



### hypothalamic, pituitary and gonadal axis. However, 12



### additional mechanistic data and the results of internal 13



### and external review determine that this mechanism is not 14



### operational in the human population. Therefore, the 15



### current cancer classification, as has been stated, is not 16



### likely to be a carcinogen. 17

18



### EPA notes that there are no other tumors identified in th e 19



### experimental toxicity data, and that the weight of the 20



### evidence does not support genotoxicity or mutagenicity of 21



### atrazine. So over all, considering these factors, the 22



### experimental evidence does not indicate a role for 23



### atrazine in the carcinogenic proces s in humans. 24

25



### So integrating the experimental toxicology and 26



### observational epidemiology datasets, the two streams of 27



### evidence are consistent in our view, and are supportive of 28



### the conclusion of no association. There is no evidence of 29



### prostate hyperplasi a or tumorigenesis in the rat although 30



### EPA acknowledges that the rodent bioassay is a poor 31



### predictor of human prostate cancer. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Across the observational studies, those available with 2



### stronger design and methods do not suggest a positive 3



### association. So, considering these streams of evidence, 4



### available data at this time do not support the association 5



### between atrazine exposure and prostate cancer. That is 6



### our preliminary conclusion upon which we are asking your 7



### feedback. 8

9



### Regarding breast cancer, again, the experimental 10



### toxicology and available epi data are consistent. The 11



### mammary gland tumors are not relative to the human 12



### population, given the mode of action identified. And the 13



### available epidemiology database, however limited, is not 14



### indicative of str ong positive associations. So, for these 15



### reasons, our preliminary conclusion is that available data 16



### from the toxicology and epidemiology literature do not 17



### support an association between atrazine exposure and 18



### breast cancer. 19

20



### Concerning ovarian cancer, th e tox and epi databases are 21



### somewhat inconsistent. This is mainly the observation of 22



### some significant risk in the human population or 23



### associations identified in studies in the human 24



### population. 25

26



### Regarding experimental toxicology, there is no evidence of 27



### ovarian pathology or tumorigenesis in animal studies. EPA 28



### notes that tumors may indeed result from an altered 29



### endocrine environment however, the current mode of action 30



### is actually suggestive of a reduced risk of ovarian 31



### cancer. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And, again, the availab le epidemiological database is 2



### limited, but some positive associations were observed. 3



### However, at this time, given the relatively few number of 4



### studies and small number of exposed cases reflected in 5



### many of these studies, alternative explanations may exis t. 6

7



### So, for these unique reasons, considering the toxicology 8



### and epidemiology data, our preliminary conclusion is that 9



### available data do not support an association between 10



### atrazine exposure and ovarian cancer. 11

12



### Concerning thyroid cancer, we only have t hat one point 13



### estimate made available through the recent updated 14



### atrazine cohort analysis within the Ag

- Health Study 15



### cohort. Therefore, results are somewhat inconsistent. 16



### With respect to the toxicology database, there is no 17



### evidence of thyroid hyperplasi a or tumor formation, nor is 18



### there evidence of altered thyroid hormone in rodents. We 19



### note, particularly, that the rat is sensitive to thyroid 20



### carcinogenesis, and no observation of tumor formation was 21



### identified in these studies. So again, within the 22



### obs ervational database, based upon only one evaluation in 23



### which a positive association was observed, the data at 24



### this time are inconclusive and require replication. So 25



### given these specific reasons, our preliminary conclusions 26



### is that available data do not su pport an association 27



### between atrazine exposure and thyroid cancer. 28

29



### Concerning the leukemias and lymphomas, these datasets are 30



### consistent. There is no evidence of lymphohematopoietic 31



### tumor formation in animal models. And in addition, there 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is no eviden ce that disruption of the HPG axis or any 1



### other hormonal component is related to the etiology of 2



### lymphohematopoietic cancers. 3

4



### And within the observational epidemiology database, those 5



### with stronger design and methods, at this time, are not 6



### suggestive o f a positive association in the population 7



### studied. So for these reasons, again, our preliminary 8



### conclusion is that available data do not support an 9



### association. 10

11



### Concerning the other cancer sites, again, we observed 12



### little evidence of an association in either the 13



### experimental tox or the epi database, and we find these 14



### two databases to be consistent in this way. 15

16



### So as stated at the conclusion of chapter 3 of our draft 17



### issue paper, EPA believes that while epidemiology studies 18



### are weakly suggestive of an association across some of the 19



### anatomical cancer sites evaluated, considering the 20



### different lines of evidence from both experimental, 21



### toxicology and observational epidemiology studies, 22



### evidence does not strongly suggest a role for atrazine in 23



### human car cinogenesis. 24

25



### So at this time, the weight of the evidence supports that 26



### atrazine is not likely to be a carcinogen in the human 27



### population. So that concludes my presentation and my 28



### review of these 40 observational studies and integration 29



### with the toxicol ogy database and I would be happy to take 30



### any clarifying questions. 31

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### DR. ELLEN GOLD : So, I have a question about the data 1



### collection in the AHS regarding

-- you know, they updated 2



### their analyses several times, and I am wondering if they 3



### did repeat adminis trations of a questionnaire to update 4



### the exposure information as well as the covariate 5



### information? 6

7

8



### DR. CAROL CHRISTENSEN : Yeah. I can briefly address that, and 9



### maybe I will ask my colleague, Dr. Laura Beane

- Freeman to 10



### elaborate. Yes, to my knowledge , reviewing these papers, 11



### the Ag

- Health Study researchers have updated exposure. 12



### However, in the recent analysis made available earlier 13



### this year, that information was not included. Do you want 14



### to add anything to that? 15

16



### DR. LAURA BEANE

- FREEMAN : No. Thi s is Laure Beane

- Freeman from 17



### the National Cancer Institute. What Dr. Christensen said 18



### was correct. In the most recent analyses, they have all 19



### relied on exposure data that was collected at phase 1 or 20



### enrollment, which was collected from 1993 through 1997

. 21



### However, they were asked about their lifetime use of 22



### pesticides or chemicals at that time. 23

24



### The second questionnaire elicited information on their 25



### use. It took place about five years after the initial 26



### questionnaire was administered and elicited use a bout 27



### their use of chemicals within that intervening five years. 28



### So it would have only added an additional five years of 29



### exposure information. 30

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### Our cancer incidence data actually only goes through 2007, 1



### in that most recent publication, and so some of tha t 2



### exposure information, it would have only been pertaining 3



### to 1998 through about 2003. 4

5



### DR. ELLEN GOLD : Covariate information? 6

7



### DR. LAURA BEANE

- FREEMAN : We used the same covariate 8



### information that was also included at phase 1. 9

10



### DR. SUSAN AKANA : Just at point of clarification. On your 11



### weight of evidence, are there sites that includes

-- I 12



### assume there is no evidence to support adrenal tumor 13



### formation in rodents? 14

15



### DR. CAROL CHRISTENSON: That is correct. We did not identify 16



### any epidemiological evaluation s of that cancer site; 17



### that‟s correct. 18

19



### DR. KENNETH PORTIER : By the way, it is a very good summary. I 20



### really enjoyed reading it and it was very clear. The only 21



### thing that kind of caught my attention is the thyroid 22



### cancer study and the four

- fold increase in two of the four 23



### exposure categories. Can you give me some insight as to 24



### why they choose those exposure categories? Because the 25



### ones that have very low odd ratios are the ones that have 26



### very few cases. So they have like three cases and there 27



### are 18 cases and then it is five cases and then 23 cases 28



### or something like that. 29

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### DR. CAROL CHRISTENSEN : Sure. I think I will defer to Dr. 1



### Beane

- Freeman as that question relates to the conduct of 2



### the research. 3

4



### DR. LAURA BEANE

- FREEMAN : Sure. So, since we di dn't a priori 5



### think that we did not have any evidence for thyroid 6



### cancer, we based our cut points on the distribution of all 7



### cancer cases. So what you are seeing is the reflection of 8



### a distribution of

-- the cut points are based on the 9



### distribution of all cancer sites combined. 10

11



### We did not change them specifically to be thyroid cancer 12



### cases. Certainly, we could have made those quartiles 13



### specific to thyroid cancer cases, but we had made the 14



### decision up front to base cut points on all cancer sites 15



### combined

. 16

17



### DR. FRANK BOVE : Yes. On the slides on ovarian cancer, it 18



### mentions that alternative explanations may exist. Have 19



### you thought of what those are? 20

21



### DR. CAROL CHRISTENSEN : Yes. Again, there were only a few 22



### studies available to consider in our synthesis. Among 23



### those studies available, the relatively small number of 24



### exposed cases included just sample size, increasing sample 25



### size and possibly issues with method of exposure. I 26



### think, for each of the ovarian cancer studies, authors 27



### were only able to look at ever/never exposure, whether 28



### additional clarity would be provided through review of 29



### exposure response is a question. 30

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### DR. BARRY TIMMS : I have some questions about the prostate 1



### cancer study. In that study, did they

-- 2

3



### DR. CAROL CHRISTENSEN : Are you r eferring to the study of 4



### Triazine manufacturing plant workers or which

-- 5

6



### DR. BARRY TIMMS : Yes, the agricultural study on atrazine 7



### exposure to the workers. Did they show a difference in 8



### the timeframe from the initial diagnosis to clarification 9



### of pros tate cancer or a change in the Gleason score in 10



### those workers that were exposed compared to the controlled 11



### group? 12

13



### DR. CAROL CHRISTENSEN : I will ask one more time if you could 14



### clarify which set of studies you are referring to. Let me 15



### try to go back to t hat slide. The studies produced by the 16



### Agricultural Health Study or the Triazine manufacturing 17



### plant studies? 18

19



### DR. BARRY TIMMS : The manufacturing plant studies. 20

21



### DR. CAROL CHRISTENSEN : Oh, manufacturing plant studies. And 22



### again, your question is whethe r there is information 23



### regarding Gleason score? 24

25



### DR. BARRY TIMMS : Gleason score and/or the timeframe from the 26



### initial diagnosis to the actual confirmation of prostate 27



### cancer through prostatectomy or biopsy. 28

29



### DR. CAROL CHRISTENSEN : So, I believe across th ese studies, 30



### these were all PSA

-- the cancers identified were 31



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### identified among men who were generally younger, and only 1



### among men who were currently employed in the plant during 2



### the time period of the PSA testing program. 3

4



### Tumors were generally of low

- grade and low

- stage, although 5



### I do not recall Gleason score being reported within that 6



### study by Hessel et al. in 2004, and I do not recall 7



### information regarding the time period between employment 8



### and diagnosis. 9

10



### DR. HEATHER YOUNG : Just a minor clarification on your slide 11 11



### on the ovarian cancer. For the Italian study, I think 12



### that is actually a 90 percent confidence interval. You 13



### have that correct in your appendix B, but on the slide you 14



### have it as a 95 percent. So, if people have not read the 15



### Appendix B, it is a 90 percent confidence interval. 16

17



### DR. CAROL CHRISTENSEN : Thank you very much for that 18



### clarification. I apologize for my error. 19

20



### DR. TRAVIS JERDE : I have just a follow

- up on Dr. Timms' 21



### q uestion regarding the Gleason score. So, I looked around 22



### and I see about 50 men in the room. Twenty

- five of us 23



### will get prostate cancer in our life, but only one or two 24



### of us will probably die from it. So, this is a disease 25



### about strength progression, w hat type of cancer. I see 26



### from your chart that you say relatively few studies 27



### available, and you have got database limitations. Do you 28



### know if those data are extractable from those studies that 29



### one could go and look at Gleason grade biopsy and things 30



### lik e that from those studies? To get that answer, would a 31



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### DR. CAROL CHRISTENSEN : You are considering the totality of 2



### that database or considering the manufacturing plant 3



### workers? So with regard to Gleason score, that 4



### information , I believe

-- and I will defer to Dr. Bean

5



### Freeman

-- that information is available through the 6



### Agricultural Health Study, and I believe have been used in 7



### other analysis, although not in the recent cohort 8



### evaluation. That information is collected and rep orted to 9



### the respected state cancer registries. Presumably, the 10



### cancers reported in the states in which the triazine 11



### manufacturing plant employees resided is also 12



### theoretically available, although I would have to look 13



### more into that question. 14

15



### DR. DANIEL SCHLENK : Any other questions or clarification? 16



### Okay. Thank you, Dr. Christensen. Let me just point out, 17



### too, just for the agency; when questions come to you, can 18



### you please state your name for the record when you make 19



### the answer? I know it sounds repe titive but we need that 20



### for the auditory record, so I just want to highlight that 21



### a bit. Okay? 22

23



### Our next presentation will be by Dr. Mendez again, I think 24



### two or three; got another couple to go here. And she is 25



### from HED/OPP. 26

27



### DR. ELIZABETH MENDEZ : All right. As Dr. Schlenk just 28



### mentioned, this is the second of my third presentation. I 29



### will be coming in periodically to sort of into the nodes 30



### to start tying things up together as we progress during 31



### today's talks. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So, the second presentation is the inte gration of 2



### epidemiology and toxicity data into the health risk

3



### assessment. And Dr. Christensen just went through the 4



### integration of these two disciplines with respect to 5



### cancer in great detail, so I am just going to go very 6



### quickly over that. And I am go ing to concentrate 7



### primarily on the integration of the noncancer effects and 8



### the epi data. 9

10



### Now, typically, the agency's human health risk

- assessment 11



### relies heavily on experimental toxicity data. But 12



### realistically, we are not trying to protect the rodent , we 13



### are trying to protect the human population. So it is 14



### important for us to

-- our ultimate goal is to evaluate 15



### the potential impact of the toxicant on the human 16



### population. 17

18



### And this instills an understanding of the mode of action 19



### as well as what is h appening within the epidemiology data. 20



### Because that way we can start to extrapolate what we are 21



### seeing in the rodent or what we are seeing in the test 22



### species to see if that is relevant to the human and how 23



### good our model might be. 24

25



### So, we start out our evaluation with a draft framework for 26



### integrating these two streams of evidence, and the concept 27



### in the draft 2010 framework are based on peer

- reviewed 28



### robust principles and tools. 29

30



### The Bradford Hill criteria has been used for many, many 31



### years in helpin g us organize data to look at data when we 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### have multiple lines of evidence. And to that effect we 1



### have used modified, Bradford Hill criteria to look at all 2



### of these datasets. 3

4



### But in addition, it is integrating new approaches based on 5



### the recommendations from the National Academy of Sciences 6



### in their reports of 2007 and 2009; Toxicity testing in the 7



### 21st Century: Science and Decisions and Advancing Risk

8



### assessment. 9

10



### So what we are trying really to do is move beyond just 11



### looking at adverse outcomes and tr ying to understand the 12



### underlying biology that is leading us to these adverse 13



### outcomes. 14

15



### But using these processes, it allows us the flexibility to 16



### incorporate information from different sources, and it 17



### also provides as a transparent tool for organizing

, 18



### reviewing and interpreting the complex information that is 19



### also not only useful to us, but to the general public who 20



### is looking at our work so they can see how we are looking 21



### at these data. 22

23



### So, in February 2010, the SAP reviewed the agency's 24



### proposed d raft framework, and in general, they were in 25



### agreement with our proposal. And so, you have seen this 26



### image before when Dr. Cooper spoke about the mode of 27



### action, and Dr. Christensen just spoke about the human 28



### epidemiology data. So my job, at this point, is to try to 29



### bring those two disciplines together. 30

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### The NRC report had two very important statements for us. 1



### One is that we are trying to shift away from a focus on 2



### adverse health effects and experimental outcomes towards a 3



### deeper understanding of biolog ic perturbations in the key 4



### toxicity pathways. 5

6



### But the other thing that the committee cautioned us is 7



### that, virtually, all environmental agents will perturb 8



### signalling pathways to some degree. And the challenge for 9



### us to determine when is that perturbat ion meaningful in 10



### terms of leading to a toxic effect, and when it is just

- 11



### - as Dr. Fowle usually refers to it

-- a blip in the road. 12

13



### So, let's just go into a little bit of detail in the 14



### adverse outcomes pathway. So the organism is going along 15



### and it h as its biological inputs and its got its normal 16



### biological function. And in comes and exposure, some sort 17



### of insult to the system. And there is a delivery to the 18



### target tissue and there is a perturbation. 19

20



### Now, when we have a toxicity pathway, what happ ens is that 21



### that perturbation is of either such a magnitude or such 22



### duration that it can cause an early cellular change. The 23



### question then is, can there be adaptive responses or 24



### mechanisms that can lead us back to the normal biological 25



### function, or is the insult of such degree that it actually 26



### causes a cell injury and an adverse outcome? And our goal 27



### here is to identify the difference between this and this, 28



### and trying to make sure that what we are regulating on is 29



### letting us prevent going from this path o n. 30

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### So then, to the mode of action framework, the modified 1



### Bradford Hill criteria; we have a postulated mode of 2



### action which is the neuroendocrine disruption of the HPG 3



### axis. As Dr. Cooper mentioned in his presentation, we 4



### have identified sequence of k ey events on the path to the 5



### health outcome. 6

7



### We have a rather robust dataset with experimental support 8



### that has concordance of dose response for key events as 9



### well as temporal relationships for the key events. The 10



### data shows that all of these events are biologically 11



### plausible. 12

13



### As Dr. Christensen mentioned, we have strength and 14



### consistency not only within the experimental tox data, but 15



### also when we look across the epi data. We keep our eye 16



### out for other modes of action, but we have not seen one as 17



### of y et. And we have tried to the best of our abilities to 18



### identify the uncertainties and tried to reach some 19



### preliminary conclusions based on the data that are 20



### available to us today. 21

22



### But the goal here is to promote the maximal use of the 23



### relevant informatio n that is available to us. So the 24



### organization of the draft framework for integrating epi 25



### and tox data

-- we are reviewing the epidemiology studies 26



### for using pesticide risk

- assessment. 27

28



### And as Dr. Christensen elaborated in her presentation, we 29



### have loo ked at a variety of types of studies. We have 30



### looked at the scientific factors that need to be 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### considered in reviewing. What is the exposure? It is an 1



### ever/never? How are we doing the odds ratios? 2

3



### The benefits and uses of epidemiology and risk

- asses sment 4



### cannot be denied. Ultimately, that is the population we 5



### are trying to protect. 6

7



### T he way that we have gone about this is looking at it from 8



### a proposed weight of evidence analysis. We consider the 9



### mode of action information that we have in the test 10



### species. We consider the experimental toxicity data and 11



### we consider the epidemiology data all wrapped together ; 12



### s o, the weight of evidence analysis; the non

- caner 13



### effects. The mode of action of is neuroendocrine 14



### perturbation of the HPG axis, and we see ovarian cyclicity 15



### disruption, reproductive senescence and other reproductive 16



### effects in the animal tox dataset. 17

18



### We also see low birth weight or small for gestational age, 19



### but those are not really related directly to the HPG axis 20



### perturbation, are more li kely indicative of just general 21



### toxicity. 22

23



### In September 2010 of SAP, the SAP concurred with the 24



### agency's conclusion that the epidemiology data is useful 25



### for hazard ID but not robust for dose

- response assessment 26



### or risk characterization. 27

28



### So, we do see some disruptions in the menstrual cycle in 29



### women. We do see, when it comes to menstrual cycles and 30



### estrous cyclicity, it is actually going in opposite 31



### directions in the rodent. We see an early reproductive 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### senescence in the epidemiology data. It appear s that 1



### there may be a little bit of a delay , a nd either 2



### reproductive effects are generally testosterone levels in 3



### semen quality, and they are kind of tracking with the 4



### animal data. 5

6



### Dr. Christensen just went through the cancer effect, so 7



### I'm just going to go through this very quickly. The 8



### mammary gland tumors in the rats are due to the HPG axis 9



### disruption; a mode of action that has been established not 10



### to be operative in humans. We do not see any other tumors 11



### identified in experimental toxicity data. An d to address 12



### Dr. Akana's question earlier, we do not see any adrenal 13



### either in the rats. 14

15



### And at the April 2010 SAP, the panel concluded that they 16



### felt comfortable with retaining the classification of 17



### atrazine as not likely to be carcinogenic to humans, based 18



### on the information available. 19

20



### The epidemiology data, we have varying degrees of study 21



### quality and limitations that Dr. Christensen went through 22



### in detail ranging from inconsistency in findings to method 23



### of exposures assessment and the small numbe r of exposed 24



### cases. But the weight of evidence does not support an 25



### association between atrazine exposure and cancers in 26



### general. 27

28



### So when we are trying to bring the two lines of evidence 29



### together, what we see is that, for the non

- cancer effects, 30



### based o n the experimental toxicity data, LH suppression in 31



### the rats appears to be protective of other effects. And 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### we have a benchmark dose of 2.56 milligrams per kilogram 1



### per day coming from the Cooper et al. 2010 dataset. The 2



### epidemiology data is useful for h azard ID but not robust 3



### for dose

- response or risk characterization. And as Dr. 4



### Christensen mentioned, in the cancer effects, the 5



### available data do not appear to support an association 6



### between atrazine exposure and cancer. And with that, I 7



### will conclude. 8

9



### DR. DANIEL SCHLENK : Thanks, Dr. Mendez. Any quick questions 10



### on the integration of the Epi and tox data? Yes, Dr. 11



### O'Byrne? 12

13



### DR. KEVIN O'BYRNE : I just have one point of clarification. I 14



### must have missed it in the literature. I was not aware 15



### that there was any evidence of menstrual cycle 16



### disturbance. 17

18



### DR. ELIZABETH MENDEZ : That actually comes from the 19



### epidemiology data. There are one or two studies, and I 20



### will defer to Dr. Christensen for that. 21

22



### DR. CAROL CHRISTENSEN : Yes, hello. In September of las t year 23



### we brought forward to the panel the epidemiology data on 24



### the non

- cancer health effects of atrazine and that 25



### included two evaluations, again, within the Agricultural 26



### Health Study; this time on the non

- cancer side in which 27



### they looked at the relations hip between several different 28



### pesticides including atrazine, and two specific outcomes: 29



### Menstrual cycle characteristics

-- and I think, if I 30



### recall correctly, there were five outcomes from long 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### cycle, short cycle or regular cycle, that type of thing

-- 1



### an d then a separate evaluation on timing of menopause. 2

3



### And so those were the only two evaluations that we 4



### identified looking at menstrual cycle characteristics. 5



### They were epidemiology studies in the human population 6



### and, again, among women in the Ag

- Healt h Study who are 7



### among the more highly exposed in the population. 8

9



### DR. DANIEL SCHLENK : Okay. Any other questions before we move 10



### on? Okay. Thanks. Our final presentation before lunch; 11



### no pressure, is going to be made by Dr. Chester Rodriguez 12



### who is also at HED and OPP. Thanks. 13

14



### DR. CHESTER RODRIGUEZ : Thank you very much. So the title of 15



### the talk is Updates to the Dose

- Response Assessment with 16



### Implications for Water Monitoring Frequency. 17

18



### Just to put the presentation in context, this is what the 19



### out line is. I am going to start with a recap of the 20



### September 2010 SAP meeting. The agency proposed using 21



### internal measures of exposure based on radiolabeled 22



### atrazine studies. And then, I am going to move on to 23



### analysis of additional data based on radiolab eled atrazine 24



### studies. Then I'm going to cover some information that is 25



### available on the pharmacokinetics of atrazine in human. 26



### That is not a radiolabeled study. That is a co

- study, if 27



### you will. 28

29



### Based on those analyses , I am going to go over a 30



### pharmac okinetic modeling approach that the agency is 31



### proposing based on a simplified one

- compartment linear 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### model. And I am going to go over some model evaluation 1



### exercises. 2

3



### So based on that, then, I am going to walk you through a 4



### current understanding of phar macokinetic behavior

, 5



### internal dosimetry and the endpoint of concern, LH 6



### attenuation in rats. 7

8



### And lastly, I am going to go over how we plan to estimate 9



### the human intake of the dose rate through an area

- under

10



### the

- curve analysis of water chemographs. An d the 11



### application of these methodologies will follow in a later 12



### presentation when we apply them to case studies, so stay 13



### tuned for that. 14

15



### So, I am going to start with a recap then of the September 16



### 2010 SAP regarding international measures of exposure. 17



### Ju st as a historical context, in the previous risk

18



### assessment to support the RED, the risk

- assessments were 19



### actually based on a NOAEL and LOAEL approach. The 20



### critical study

-- it was a six

- month study, and the key 21



### event is actually attenuation of LH. 22

23



### At t he September 2010 meeting we actually introduced more 24



### sophisticated approaches for doing those response 25



### analyses , and those include benchmark of the dose 26



### modeling, as well as internal measures of exposure. 27

28



### Now, for an old chemical like atrazine, there is enough 29



### information, pharmacokinetic information, to depart from 30



### the traditional external dosimetry to an internal dose 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### that can help refine the linkage between atrazine exposure 1



### and the endpoint of concern, LH attenuation. 2

3



### This is a quote from the Natio nal Research Council 4



### regarding the use of internal does, and it says; "The does 5



### at the target site, the internal dose is the ultimate 6



### determinant of risk." So that is a good motivation of 7



### moving towards an internal dose

- response analysis. 8

9



### In the case of atrazine, the use of internal measure of 10



### exposure is even more relevant because atrazine as a 11



### parent chemical is short

- lived in the body due primarily 12



### to being metabolized to other species, which at least some 13



### of them tend to also be active in the endpoin t attenuation 14



### of LH. 15

16



### At the September 2010 meeting we actually proposed to use 17



### the area under the plasma concentration

- time curve as 18



### internal measure of exposure. And the rationale for that 19



### actually follows the endpoint of concern, LH attenuation 20



### which does not seem to be a single dose effect. 21

22

23



### This is a figure from the Cooper et al. 2000 report that 24



### shows that a single does

-- and it has to be as high as 25



### 300 mg per kg to what you see a decrease in LH

-- whereas, 26



### a much lower does, as low as 3.12 mg per kg per day given 27



### to rats over four days, once daily, leads to a nice dose

28



### response relationship. So based on these findings then, 29



### duration seems to be a critical parameter for the endpoint 30



### in rats, LH attenuation. 31

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### So plasma AUC as an internal dose metric does not only 1



### take into account internal dose levels, but also duration. 2



### And a simplified way of thinking about it is that it is 3



### basically the product of how much the exposure is and for 4



### how long. So the AUC that was selected, by the way, was 5



### for plasma triazines based on radiolabeled atrazine 6



### studies. And the reasons for that is as follows: There 7



### is a lack of detailed pharmacokinetic information for 8



### atrazine and its metabolites as it relates to the 9



### endpoint. 10

11



### Radiolabeled atrazine studies ar e available in rats. The 12



### same species where the endpoint has been characterized, LH 13



### attenuation

-- and another reason for selecting 14



### radiolabeled atrazine studies is that these studies, for 15



### the most part, achieve a high degree of mass balance so 16



### you know w here the dose is going. Is it getting excreted; 17



### is it getting retained; et cetera? 18

19



### Radiolabeled pharmacokinetic studies with atrazine have 20



### been carried now with a 14C radiolabeled triazine ring. 21



### And it is usually labelled at the all the carbons on the 22



### ring. This ring is metabolically stable, will now be 23



### degradable by metabolism. 24

25



### So the radiolabeled atrazine study that was selected was 26



### by Thede 1987, and we selected this study for two reasons, 27



### actually. We wanted to use it to estimate the plasma A UC 28



### for radiolabeled triazines and as well as to learn about 29



### the temporal relationship between atrazine exposure and LH 30



### attenuation in rats. This study was very similar to 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the 4

- day LH attenuation study carried by Cooper et al. in 1



### that he actually used in take young female rats. 2

3



### It involved repeated once daily dosing with atrazine for 4



### at least four days, and it covered a wide range of 5



### atrazine doses from one to 100 mg per kg per day. And he 6



### also provided repeat plasma measurements which included 7



### the el imination phase. 8

9



### This is what the plasma profile looks like and I just want 10



### to make two points from this slide. Number 1 is that when 11



### you start dosing with atrazine, you get accumulation of 12



### plasma triazines. So the dosing is being done once daily. 13



### And as you can see, by the fourth day of dosing you start 14



### to get a plateau or what I called pseudo steady state 15



### plasma triazine levels. And what I mean by that is that, 16



### the plasma levels stay within a specific range as long as 17



### dosing continues at the same le vel and frequency. 18

19



### This is a hypothetical figure showing how three studies 20



### with different durations can have the same pseudo steady 21



### state plasma levels. So as you can see, we have four 22



### days, we have 14 days and then we even have six months. 23



### These studi es, even though they differ drastically in 24



### duration, they will have the same pseudo steady state 25



### level, because as soon as you reach this level and you 26



### continue dosing at the same level and frequency, plasma 27



### levels will remain within that range. 28

29



### Plasma t riazines will decrease only when dosing actually 30



### stopped, and that is what the elimination phase is. So if 31



### the endpoint of concern is related to pseudo steady

- state 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### plasma levels then studies of different durations should 1



### have the same LOAEL; and that is what the next slide 2



### shows. 3

4



### This is the critical study from the 2003 risk

- assessment. 5



### This is the new study by Cooper et al. Two studies are of 6



### different durations. You know, they were performed in 7



### different labs, but the one thing that they have in co mmon 8



### is that the frequency in dosing that was involved were 9



### very comparable. 10

11



### Now, as you can see from the LOAELs, they are very, very 12



### similar. So the bioaccumulative profile of plasma 13



### triazines then is consistent with the similar LOAELs for 14



### studies acro ss different durations of atrazine exposures 15



### in rats. So based on these observations, then, we 16



### actually proposed a daily steady state AUC for internal 17



### dose response analysis. 18

19



### Other features that were noted in the behavior of plasma 20



### triazine from the T hede 1987 study is that there is linear 21



### pharmacokinetic behavior. Now, what I mean by that is 22



### that the internal dose metric that we are proposing in a 23



### steady state AUC, it scales directly with atrazine does. 24



### Also, the elimination kinetics that is exhibit ed by 25



### radiolabeled plasma triazines follows linear behavior. 26



### And I would like to spend some time trying to define what 27



### that is in a conceptual way. Linear elimination kinetics, 28



### it actually means that a change in plasma concentration 29



### or, a change in time, equals

-- now, there should be a 30



### minus sign here, by the way. 31

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### So the change in plasma concentration then will be 1



### directly proportional to the plasma concentration. This 2



### means that the body can adjust to eliminate more or less 3



### without changing anything. But actually, more importantly 4



### though, this is elimination rate constant, kel. 5

6



### When you solve this simple differential equation, what you 7



### get is an integrated form of this expression that relates 8



### plasma concentration as a function of time. Now, as yo u 9



### can see from this, this is the equation of a line with 10



### slop; kel, the elimination rate constant. So the linear 11



### expression of plasma triazines will have kel as a slope. 12

13



### Now, this should say fractional rate of elimination. The 14



### fractional rate of elimin ation of plasma triazine will 15



### proceed at a rate that is independent of plasma levels. 16



### The fraction or rate will be determined solely by the 17



### elimination rate constant, which is a constant. That 18



### translates to a plasma half

- life, a constant plasma half

19



### life that is predictive for extrapolation across dose 20



### levels. 21

22



### This is pretty important because this is one of the most 23



### attractive features of having linear kinetics in that you 24



### will have a constant plasma half

- life that is independent 25



### of dose levels. 26

27



### So when we analyzed the elimination phase from the 28



### different groups of the Thede Study, we actually noted two 29



### things; number 1, linear behavior across different dose 30



### levels. But actually, more importantly though, the 31



### elimination rate constant was very consis tent for the one, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### three, seven and ten dose groups. And that elimination 1



### rate constant translates into a plasma half

- life between 2



### two and three days. 3

4



### So now I am going to go over the analysis of additional 5



### animal pharmacokinetic studies with radiolabele d atrazine. 6



### Two of the limitations from the Thede Study that were 7



### noted by the panel at the September meeting was that only 8



### two animals were used per dose group, and the elimination 9



### phase was estimated with only three data points from a 10



### single animal. 11

12



### A nd so, the panel urged caution in actually analyzing this 13



### dataset. So one of the things we wanted to do right away 14



### is to try to find additional support that will support our 15



### findings about plasma clearance from the Thede Study. We 16



### were able to find two a dditional rats studies with 17



### radiolabeled atrazine; one by Paul et al. in 1993 and the 18



### other one by Simoneaux in 1985. These studies are not 19



### quite ideal to actually compare to the 4

- day LH 20



### attenuation study. 21

22



### For one thing, these two studies actually inv olved male 23



### rats. The 4

- day study use female rats. But regardless, 24



### we wanted to analyse the plasma clearance from these two 25



### studies to see how they compare from our findings from the 26



### Thede Study. 27

28



### In the first study by Paul et al., plasma measurements 29



### re sulting from single oral gavage doses of 1 or 100 mg/kg, 30



### radiolabeled atrazine was given to groups of three male 31



### rats. In the Simoneaux 1985 study, plasma measurements 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### were taken at various days post

- dosing resulting from 1



### doses of either .4 or 4 mg/kg rad iolabeled atrazine given 2



### to 36 male rats, 3 per time point for seven days. 3

4



### This is the analysis from the Paul et al. Study. This is 5



### what the plasma profile looks like either at 1 or 100 6



### mg/kg radiolabeled atrazine. This is the plasma 7



### elimination analys is from these two dose levels. And as 8



### you can see, the slope of the line, which is elimination 9



### rate constant, is about .01, which is very consistent from 10



### the study from the Thede 1997 report. We did the same 11



### thing for the Simoneaux 1985 study, to see wha t the plasma 12



### profile looks like. When we analysis the elimination 13



### phase this is what we get. 14

15



### Now, it should be noted that the plasma levels were 16



### actually reported as days post

- dosing. This slope that 17



### you have on the first line is elimination rate con stant in 18



### per

- day units. But when you convert that to per hour, as 19



### the other studies, you again see a very similar 20



### elimination rate constant of about .01. 21

22



### So, when you put all these studies together, what you have 23



### is a wide range of atrazine doses that g oes from .4 all 24



### the way to 100 mg/kg per day, and they all exhibit a very 25



### similar elimination rate constant. So what we are seeing 26



### is that there is a half

- life that is from two to three 27



### days that is exhibited across different studies in oral 28



### doses of radi olabeled atrazine. 29

30



### So, all the studies that are discussed thus far have been 31



### in rats. There is a new study that was recently published 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### by Hui et al. in which they examine the pharmacokinetics 1



### or radiolabeled atrazine in non

- human primates; monkeys. 2

3



### Rhesus monkeys were actually dosed by oral gavage with 1, 4



### 10 or 100 milligrams of radiolabeled atrazine. Plasma was 5



### sampled for radioactivity at various time points. But the 6



### most important observations from this study is that the 7



### internal dosimetry tha t we are purporting to use also are 8



### scaled in the linear fashion with atrazine dose. And the 9



### elimination of plasma triazines, of radiolabeled 10



### triazines, was also linear. And these are what the 11



### pharmacokinetic parameters that were reported. 12

13



### So now I am going to go over some human pharmacokinetic 14



### information that is available for atrazine. So as for 15



### most environmental chemicals, human information is very 16



### limited, like especially controlled human studies. 17

18

19



### There is a report from 1985 by Davison where six human 20



### volunteers received a single dose of atrazine at a level 21



### of .1 mg/kg. Whole blood from a single subject was 22



### analyzed for atrazine and its chlorotriazine metabolites 23



### DEA, DIA and DACT. And urine from all subjects was 24



### analyzed for DEA, DIA and DA CT. So the results from the 25



### study suggest that only DIA and DACT, two of the 26



### chlorotriazine metabolites for atrazine, were detected in 27



### whole blood. Only DEA, DIA and DACT were detected in 28



### human urine. 29

30



### So it should be noted that the parent atrazine co uld not 31



### be detected in either blood or urine. But the most 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### important thing here is that the three metabolites that 1



### were detected, they all exhibited linear elimination 2



### kinetics, and I cannot emphasize that enough. 3

4



### I should also note that in the study, t here was a lack of 5



### mass balance. That when they monitored DEA, DIA and DACT, 6



### those three metabolites only accounted for 14.5 percent of 7



### the atrazine dose that was given. 8

9



### So in summary, I can say that chlorotriazine

-- whether 10



### it's atrazine DEA, DIA or D ACT

-- when you monitor those 11



### individually, they tend to exhibit linear elimination 12



### kinetics, which is the same when you monitor radiolabeled 13



### atrazine. So we are seeing very consistent 14



### pharmacokinetic behavior in this. 15

16



### The human pharmacokinetic paramete rs that were reported by 17



### Davidson

-- and as you can see, there is a linear 18



### elimination very constant, along with elimination of half

19



### life. Whole blood; like I said before, atrazine was not 20



### detected, and DEA was not detected either. In urine; DEA, 21



### DIA and again, DACT were detected, and those are the half

22



### lives that were reported. I should also say that these 23



### half

- lives were obtained using a one

- compartment linear 24



### model for urinary excretion. So this is a quick summary 25



### of the pharmacokinetic information t hat I just presented. 26

27



### The use of radiolabeled plasma equivalents will include 28



### atrazine in all of its metabolites. We feel that this is 29



### a very conservative approach, given that we do not have 30



### detailed pharmacokinetic information of this species as it 31



### r elates to the endpoint. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### The proposal of use in the a rea u nder the c urve for plasma 2



### as internal measure of exposure accounts for duration 3



### which seems to be important for the endpoint, LH 4



### attenuation. 5

6



### Plasma triazines, they tend to accumulate upon repeat ed 7



### dosing with atrazine to reach a plateau or pseudo steady 8



### state by the fourth day of dosing. And I should also 9



### note that the endpoint in the 4

- day study was also 10



### measured by 4th day or once daily dosing. 11

12



### So the proposed internal dose metric then that we are 13



### moving forward with is the daily steady state plasma AUC 14



### for triazines. And I should emphasize once again that 15



### linear behavior of plasma triazines is the most consistent 16



### feature that is observed across different doses of 17



### atrazine in species, inclu ding humans. 18

19



### There is additional pharmacokinetic information that is 20



### actually emerging. There is a new in vivo PK study that 21



### was carried out in rats that was recently submitted to the 22



### agency by the Registrant. A new PBPK modeling effort 23



### based partly on this new dataset that was also submitted 24



### by the Registrant in collaboration with the Hamner 25



### Institutes. I should note that the agency has not 26



### completed a thorough review and evaluation of this new 27



### PBPK modeling effort, but it is something that we plan to 28



### do in the future. 29

30



### So now I am going to go over the pharmacokinetic modeling 31



### approach that the agency is proposing. Pharmacokinetic 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### modeling can be very useful in the case of atrazine 1



### because it is a tool that you can use to get an estimate 2



### of an inte rnal dose metric for your endpoint of concern. 3



### It can also be used in the extrapolation of an internal 4



### dose associated with the endpoint to different species, 5



### including humans, life

- stages, different exposure 6



### conditions, et cetera. And actually, from the exposure 7



### side you can use the model to relate the human ingested 8



### dose through drinking water to human plasma levels that 9



### can then be compared to a rat plasma point of departure 10



### for the endpoint LH attenuation. 11

12



### So the ideal approach for doing all these f ancy things is 13



### a PBPK model, okay? Given that we do not have one at this 14



### time; the agency as such is considering other options that 15



### will inform on pharmacokinetic behavior of internal dose 16



### and water monitoring. 17

18



### So this is the proposed pharmacokinetic mo deling approach, 19



### based on a one

- compartment linear model that I should 20



### relate atrazine dose to plasma triazine levels, and is a 21



### single elimination rate constant. This model is actually 22



### based, like I said before, on linear behavior. That is a 23



### very consis tent feature of plasma triazines across 24



### different studies, doses and species. This model is also 25



### based on the internal dose that scales directly with 26



### atrazine dose. And the elimination rate constant, which 27



### is a process that is linear that results in a co nstant 28



### plasma elimination half

- life. 29

30



### So this one

- compartment linear model is consistent with 31



### previous efforts that have been reported in the past by 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Timchalk et al., by McMullin et al. and Hui et al. Again, 1



### modeling chlorotriazine equivalents ; s o we a re actually 2



### using a similar approach, but based on radiolabeled 3



### atrazine studies. So just a few things about the one

4



### compartment linear model that is being proposed ; t he good 5



### thing about having a simplified model like this is that 6



### you only need two parame ters
, the volume of distribution 7



### and the elimination rate constant. 8

9



### I have been talking a lot about elimination rate constant 10



### and the volume of distribution. These two parameters have 11



### to be reflective of the conditions for the endpoint which 12



### is in stead y state. So we were able to estimate the two 13



### parameters, the volume of distribution of plasma triazines 14



### as steady state and the elimination rate constant, from 15



### single dose plasma data from the Paul et al. Study. 16

17



### T he only nice thing about having a simp le one

- compartment 18



### model is that you actually have an analytical expression 19



### that relate those rates to plasma levels, and this is what 20



### the expression is. So plasma levels at steady state is 21



### actually equal to the dose rate in mg per kg per day, or 22



### with the volume of distribution or the elimination rate 23



### constant in actually 24 hours. 24

25



### So, one of the things that we wanted to do is to see how 26



### the model will behave in predicting pseudo steady state 27



### plasma levels from the Thede Study. As I mentioned 28



### before, t his study only use two animals per dose group. 29



### These are the average values that were reported for each 30



### animal. 31

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### So we wanted to use the model to see how close we can come 1



### to the values that were measured for plasma radiolabeled 2



### equivalence. And the model does a pretty good job of 3



### actually estimating those levels. In some case, the model 4



### predicts at the halfway, actually, between the two 5



### numbers. That is all very consistent for all of those 6



### groups. So this builds confidence in using the model to 7



### in form a PK behavior of internal dosimetry. 8

9



### So now I am going to talk about what our current 10



### understanding is of pharmacokinetic behavior, internal 11



### dosimetry and the endpoint of concern, LH attenuation. 12

13



### So this is our understanding of internal dosim etry and LH 14



### attenuation is rats. So we know that an oral dose of 15



### atrazine is actually given to rats. It is a good 16



### assumption to say that you will get very close to 100 17



### percent absorption, so you can assume complete absorption, 18



### so this will be your input. T hat absorbed dose then will 19



### get distributed in a body volume of distribution to result 20



### in plasma triazines. At this point, these plasma 21



### triazines can get eliminated with eliminate rate constant. 22



### That is your plasma clearance. So this will be your in put 23



### and this will be your output. 24

25



### When the input equals the output is when you have the 26



### condition of pseudo steady state, if you will. So upon 27



### repeated dosing with atrazine, you will get 28



### bioaccumulation until you get to what we call pseudo 29



### steady state , and that will result in your steady state 30



### plasma levels. 31

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### You add duration to that and you have your internal dose 2



### metric that we are proposing to relate to the endpoint of 3



### concern, LH attenuation. 4

5



### So what the model is doing, pretty much, is to relat e the 6



### atrazine dose to this, okay? And that is what that is. 7



### This is the expression of the one

- compartment model for 8



### the adult rats. L ike I said, the dose rate to the 9



### internal dose metric of concern, AUC

, daily steady state 10



### AUC. 11

12



### Now, so the human situ ation is different. It always is, 13



### right? So, in the case of animal studies, you know, they 14



### have been carried out at a constant dose of atrazine as 15



### well as a constant frequency of dosing. From here 16



### you will get then an internal dose that can be related to 17



### the endpoint of concern, LH attenuation. 18

19



### The human situation is different in that the dose level, 20



### nor the frequency, is likely to be constant. But we think 21



### that this would also lead to an internal dose that can be 22



### associated with the endpoint that has been observed in 23



### rats. So this is how we are relating the two of them. So 24



### this is our current understanding of the human situation. 25

26



### The intake rate is going to be determined by the water at 27



### consumption rate in the chlorotriazine levels in water. 28



### The product of these two will give us the absorbed dose 29



### just like we did with animal studies. That will get 30



### distributed in body volume of distribution to result in 31



### the plasma triazine concentration, which can get 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### eliminated at this point. And then, once again, you have 1



### the input and the output. When those two are equal, then 2



### you have the condition of pseudo steady state. 3

4



### Upon repeated exposures you will also get bioaccumulation 5



### of plasma triazines to reach what we are calling an 6



### equivalent pseudo ste ady state level. Then, if you add 7



### duration to that, you will have a human

- equivalent of an 8



### average daily AUC. 9

10



### And the reason why I do not say pseudo steady state here 11



### is because humans are not likely to reach such conditions 12



### in the same way as rats, ba sically, because we have a very 13



### variable intake dose rate that is determined by the 14



### chlorotriazine in water and in the water consumption rate. 15



### But we think that we can still use the one

- compartment 16



### model to relate what we think is the intake dose rate to 17



### the internal dosimetry of concern, which will be the human 18



### average daily plasma AUC. 19

20



### So this will be the expression for the one

- compartment 21



### model. Once again, so you have an expression that relates 22



### the dose rate to the internal dosimetry for plasma 23



### tri azines that will include all the metabolites as well as 24



### atrazine. And in the two parameters that we are proposing 25



### for humans have been allometrically scaled from the rat 26



### values. 27

28



### Now I am going to go over how we plan to estimate the 29



### human dose rate. Ok ay. The way we are proposing to do it 30



### is that we are following a recommendation directly from 31



### this panel. So we are not inventing the wheel here. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### At the September 2010 meeting the panel recommended the 2



### use of an integrated or daily average internal me asure 3



### along with a related drinking water monitoring approach 4



### based on the area and the concentration time curve. 5

6



### So, the way we feel that we have addressed this is that 7



### the internal dose, or daily average is our plasma AUC. 8



### And the proposed approached for water exposure would 9



### involve what we are calling a water schemograph AUC, AUC 10



### for water. 11

12



### Now, the way we are proposing to do this is that

-- let's 13



### take a typical schemograph , a water schemograph , showing 14



### how all triazine levels vary as a function o f time. But 15



### the way we are proposing to use this is that we can 16



### estimate the area of this curve for a given duration. So 17



### we can use the old

- fashioned sort of rule, so you will be 18



### dividing the duration of concern into trapezoids, which 19



### will be dictated by the sampling frequency. 20

21



### So the area of the trapezoid will basically be the area, 22



### at the average level, water times duration. And the AUC 23



### for water then will be the sum of the area of all the 24



### trapezoids. 25

26



### And the way that area is used, is that it actually 27



### provides us to actually come up with an estimate for the 28



### average atrazine level in water. Y ou will take the AUC 29



### for water for a given duration and you will divide it by 30



### the number of days, whether it is 4, 14 or 28, and then by 31



### 24 hours. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So th is expression four here gives a time

- weighted average 2



### level of atrazine in water which, along with water 3



### consumption information, can result in an estimate for the 4



### human dose rate, and this is the way it works. 5

6



### So after you come up with the average valu e for atrazine 7



### in water, then that can be incorporated into the one

8



### compartment linear model expression that will result in an 9



### estimate of the human equivalent average daily plasma AUC. 10

11



### So this is the approach that we are proposing. And here, 12



### I am jus t going to give you a quick summary. So plasma 13



### AUC seems to be a reasonable internal dose metric since 14



### the duration appears to be important for the endpoint of 15



### concern in rats. 16

17



### So the accumulation of plasma triazines to pseudo steady 18



### state is consisten t with a temporality of LH attenuation. 19



### Linear pharmacokinetic behavior of plasma triazines is a 20



### feature that is very consistent across different doses of 21



### atrazine, studies and even species, including humans, and 22



### they all support the use of a one

- compartm ent linear 23



### model. 24

25



### The extrapolation to adult humans is actually possible 26



### with two parameters, the volume of distribution and the 27



### elimination rate constant being allometrically scaled. 28



### And the human dose rate

-- we are proposing that we can 29



### estimate thi s through an AUC analysis of water chemograph. 30

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### And the application of these methodologies will follow in 1



### a presentation that we will do later on today. Thanks for 2



### your attention. 3

4



### DR. DANIEL SCHLENK : Thank you, Dr. Rodriguez. Questions or 5



### clarificati on? Dr. Greenwood? 6

7



### DR. RICHARD GREENWOOD : I was unable to get hold of either the 8



### Paul report or the Simoneaux report because they were 9



### internal Ciba

- Geigy reports, so I have not got all of the 10



### information I need to evaluate those. Can you tell me 11



### what the limits of quantification in these studies were ? 12

13



### DR. CHESTER RODRIGUEZ : I do not quite recall exactly, but I 14



### believe they were in the range of .01 ppm, but I will have 15



### to double check on that. 16

17



### DR. KEVIN O'BYRNE : It was quite difficult for me to fol low the 18



### science behind your talk because it is just so foreign to 19



### me. But I was astonished that the plasma levels and the 20



### elimination rates of atrazine and its metabolites were 21



### sort of constant, irrespective of dose. 22

23



### So, this only implies to me that t here is no toxicity to 24



### the kidney, even up to 100 milligrams per kilo per day, 25



### which is astonishing. Is this hopeless? 26

27



### DR. CHESTER RODIGUEZ : That is very interesting, and it tells 28



### you that the body can adjust up to a point. But if you 29



### get something lik e kidney toxicity, then you have other 30



### issues. But for the dose range that has been studied, you 31



### see linear kinetics all the way. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. JAMES MCMANAMAN : Yes. I have a question about the 2



### assumption that it is a single state elimination, because 3



### if you go to slide 22 for humans you will see that the 4



### DACTs get the rate constant for elimination of that is

-- 5



### lets just look at the urine is .060 versus the DIA's .3. 6

7



### So, that suggest that both are two elimination rates, one 8



### for each compound, which is still li near but that is fine, 9



### but there are still two elimination rates. So does that 10



### mean that there is a single compartment or

-- you would 11



### have to postulate that the rate of elimination of one 12



### would have

-- the mechanism would be different from the 13



### other then , right? So it suggests that there may be more 14



### than one compartment. 15

16



### DR. CHESTER RODRIGUEZ : Yes. And that is actually one of the 17



### reasons why we are proposing to use a radiolabeled study. 18



### When you look at the radiolabeled, it does not matter what 19



### the metabolite is, just follow the radiolabeled and that 20



### is the elimination rate constant that is actually 21



### estimated here. 22

23



### DR. JAMES MCMANAMAN : Well, if you do that, you would have to 24



### know what percentage of metabolite the radiolabeled 25



### represents. So lets say that the majority of your 26



### radiolabeled compound is eliminated as metabolite A, and a 27



### very small minority is eliminated as metabolite B

-- so if 28



### you are just looking at radiolabeled, you are going to 29



### pick up the totality, which is going to be mainly 30



### met abolite A. Whereas, the active component may be 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### metabolite B and you will not be able to distinguish 1



### between those two using the radiolabeled. 2

3



### DR. CHESTER RODRIGUEZ : That is correct. And we feel that this 4



### is very conservative, but in the absence of spe cific 5



### information about what the contribution of the metabolites 6



### are, I think this is our best option and it is 7



### conservative. 8

9



### DR. DANIEL GRIFFITH : When you talk about water consumption, is 10



### it oral consumption? Is there any evidence that there is 11



### absorpt ion through skin? 12

13



### DR. CHESTER RODRIGUEZ : The information we have is that the 14



### main route of exposure is drinking water. 15

16



### DR. WILLIAM HAYTON : Now, as far as scaling the rate constant 17



### to human, I just found it a little curious that, as you go 18



### from rat to m onkey, the half

- life actually, for the 19



### radioactivity, gets quite a bit shorter, whereas you would 20



### expect on a body weight, you know, three

- quarter par 21



### scaling, expectation that it would get longer. 22

23



### DR. CHESTER RODRIGUEZ : Yes. And you are correct, but yo u have 24



### to go by weight of evidence. You know. You have multiple 25



### radiolabeled studies that give you a very consistent kel. 26



### Also, we did a minor exercise with DACT. We took the 27



### half

- life that was estimated from rats and we 28



### allometrically scaled

-- so the half

- life of DACT in rats 29



### is about seven to eight hours. So we allometrically 30



### scaled that to see if it could predict the measured value 31



### in humans. And I can tell you that the estimate was in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### two

- fold. It is in the issue paper. But that is the best 1



### we can do, I think, with the information we have, and you 2



### have to go by weight of evidence. You know. You have a 3



### single monkey study. You have multiple rat studies, so we 4



### do the best we can. 5

6



### DR. JAMES MCMANAMAN : Yes. So do you know how the metabolism 7



### of atrazine differs between rats and primates? I mean, 8



### the P

- 450 system of the rat is pretty good. I am not sure 9



### that the same system is equivalent for the monkeys or 10



### other primates. 11

12



### DR. CHESTER RODRIGUEZ : I do not think that information is 13



### known. 14

15



### DR. DANIEL SCHLENK : Any other questions before we head to 16



### lunch? I did not want to shut everything off by saying 17



### that, but since it is time

-- okay. Let's adjourn for 18



### lunch. And since we are a bit early, let's try to get 19



### back by 1:20, okay? 20

21



### DR. DANIEL SCHLENK : Let's go ahead and get started. Welcome 22



### back to our atrazine SAP re

- evaluation of the human health 23



### effects of atrazine; review of non

- cancer effects, 24



### drinking water monitoring frequency and cancer 25



### epidemiology. 26

27



### So, we spent the first half of the day talking about the 28



### latter. We are about to talk about some of the former 29



### now, in terms of drinking water monitoring data. And 30



### giving that presentation is going to be Nelson Thurman, 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### who is with the Environmental Fate and Effects Division of 1



### OPP. 2

3



### NELSON THURMAN : Okay. Good afternoon. Just to try to give 4



### you a very, very brief recap; as part of the 2003 5



### condition of re

- registration for atrazine, Registrant 6



### Syngenta began taking weekly samples of both the source 7



### water and treated drinking water a t a selected number of 8



### community water systems to ensure the concentrations did 9



### not exceed the toxicological level of concern for a 90

- day 10



### exposure period, which is what we had at that time. 11

12



### And as we started re

- evaluating based on some of the 13



### additional studies that came in and started looking at 14



### potentially shorter durations of exposure for the toxin 15



### points, we started asking how well those weekly samples 16



### were characterized as shorter duration of exposure. And 17



### that led to why we are sitting here with L iz at the table 18



### in that regard. 19

20



### We have focused on methods for analyzing the uncertainty 21



### and monitoring for atrazine. And, in actuality, for the 22



### drinking water they are looking at total chlorotriazine. 23



### So, it is not just atrazine that is being measured ; it is 24



### the chlorodegradates as well as simazine. 25

26



### What we are going to present to you is not an analysis of 27



### drinking water monitoring data itself, but we are taking 28



### the recommendations of the previous SAPs. The methods 29



### that we have been evaluating

-- an d we are flushing those 30



### out. So we are focusing on the methods and not the 31



### assessment itself, but the methods we had used to analyze 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### that data. W hat we have done is based on the 1



### recommendations from the SAP. We have developed some 2



### proof of concept appro aches of various methods. We are 3



### not saying we are zooming in on one as ideal; we actually 4



### are looking at a handful of methods. And when it comes 5



### down to the ultimate assessment, it may depend on which 6



### duration of exposure we end up with and which method we 7



### ultimately use, but we at least want the flexibility of 8



### the tools to get there. 9

10



### So, we have looked at a number of approaches and there are 11



### a lot of people who put effort into developing these 12



### approaches. I get to talk, but I want to make sure that 13



### m y colleagues who have worked on these are up here and be 14



### ready to answer the questions in some of those. 15

16



### Mary Frankenberry had conducted a comparative statistical 17



### analysis looking at the effect of different monitoring 18



### frequencies on estimating concentrat ions of different 19



### durations. Drs. Jim Hetrick and Jim Wolf evaluated some 20



### of the Geostatistical and stochastic methods that were 21



### used to conduct the time series distribution. It can be 22



### used to fill

- in between sampling measurements. A lot of 23



### that is deta iled in the Appendix D

- 2. They went into a 24



### lot more detail than we summarized in the background 25



### paper. 26

27



### Dr. Stephen Wente also looked at a simple watershed 28



### balance model similar to something he worked on when he 29



### was with USGS. That is presented in App endix G

- 3. He had 30



### some issues with the flow data available for doing that, 31



### and so we did not fully develop that assessment. We are 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### not going to be really talking about it, but if you have 1



### some questions, Dr. Wente is here to respond to those. 2

3



### So the first part of this presentation is going to provide 4



### a brief summary of the monitoring issues as they have 5



### evolved as a result of the feedback we have had from the, 6



### primarily, the April and September 2010 SAPs. The bulk of 7



### the presentation is going to be l ooking at approaches we 8



### are proposing to characterize the uncertainties and 9



### estimates of the atrazine concentrations in water, 10



### addressing both the day

- to

- day or short

- term variability 11



### as well as year

- to

- year patterns and the spatial patterns. 12

13



### And so, I w ill begin with a recap. I think, as I pointed 14



### out earlier, some of the questions related to monitoring 15



### between the April SAP and now kind of evolved from; is the 16



### existing weekly monitoring program adequate for the 17



### shorter term duration of exposure to how do we best 18



### characterize the uncertainties in exposure estimates based 19



### on existing monitoring. So, instead of determining do you 20



### need to monitor more, it is what can we get out of the 21



### available monitoring that we have ? 22

23



### So we are focusing on approaches to characterize the 24



### uncertainties in a way that takes into account the short

25



### term variability and atrazine concentrations in water that 26



### you expect to be able to address with monitoring. But we 27



### also need to take into account the year

- to

- year 28



### variability that we will see, as well as spatial patterns. 29

30



### So the complexity of the spatial patterns and the temporal 31



### patterns in pesticide concentration are driven by a number 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### of factors, some we understand and can predict better than 1



### others, but there are some tools o ut there that help us 2



### take into account the impact of those factors on pesticide 3



### exposure. 4

5



### I will say that they do make it very challenging to design 6



### a monitoring study that takes those into account, and so 7



### as a result, we are often looking at not just t he 8



### monitoring data but what models or tools can we bring in 9



### to help better characterize that monitoring data so that 10



### we can use that. 11

12



### As we go into this presentation, the background paper, we 13



### have broken the variability down to the components, and 14



### actual ly we have separated the temporal variability into 15



### your short

- term day

- to

- day patterns as well as year

- to

16



### year patterns. But we are also mindful that the 17



### uncertainties are not necessarily additive in that there 18



### is a lot of integration that needs to go int o the final 19



### result. So while I am presenting approaches separately, 20



### what we are going to look at, at the end, is making sure 21



### we do not compound uncertainties where they do not exist. 22

23



### So this is going to be a recap of some of the preliminary 24



### monitoring e valuations we did at the last SAP. One of the 25



### emphasis of the SAP is that you really need datasets with 26



### more intensive sampling to evaluate the potential 27



### uncertainty that we have seen in the weekly samples. 28

29



### And as we have presented in previous SAPs, we do have some 30



### data available, but they are not community water systems. 31



### We are aware that Syngenta began this year monitoring six 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### community water systems on a daily basis, and we look 1



### forward to being able to analyze that data as additional 2



### data to help us as we develop these and evaluate these. 3

4



### But in this case, we are looking at a chemograph, which is 5



### the dark blue line which is based on daily monitoring. 6



### There is a dashed blue line there that represents your 4

- 7



### day rolling average. For community water system that have 8



### weekly samples, you might have a sampling date that hits 9



### that peak. 10

11



### Honestly, with the seven

- day sampling intervals, you would 12



### probably have about a 1 in 7 shot of hitting that. You 13



### may not hit that peak. The problem we have is givi ng 14



### weekly samples we do not know, and that is part of what we 15



### are trying to take a look at. 16

17



### One of the reasons we are looking at the daily monitoring 18



### is it helps us develop methods and gives us some feedback 19



### so that when we do apply these methods to the community 20



### water systems we have some confidence in terms of what 21



### they are able to provide for us. 22

23



### We have built on the recommendations of those April and 24



### September SAPs. We are not really trying to open up new 25



### ground here, but to more or less tie togeth er the sets of 26



### tools that have been discussed in those previous SAPs and 27



### try to follow up on the recommendations that the panel 28



### have made. 29

30



### To evaluate the monitoring data, the April of 2010 SAP 31



### recommends that we consider, first of all, the tox 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### exposure duration of concern because that is going to 1



### define how important capturing the peak concentrations 2



### are ; t he shorter that duration, the more important those 3



### peak concentrations are in there. They also recommended 4



### using intensive monitoring that cover a re presentative 5



### range of sites. You want monitoring that is sampled more 6



### intensively than what you are evaluating. 7

8



### And one of the comments they made is, when you are looking 9



### at monitoring, you really need to look at methods that can 10



### predict values that a re greater than what was measured, 11



### because with some sampling of any duration, you cannot 12



### expect to have captured the highest concentration in every 13



### case. 14

15



### As we came back and explored a number of approaches, the 16



### September SAP had recommended taking USGS' s watershed 17



### regression for pesticides, combining that model

-- which 18



### is regression

- based model

-- with a deterministic model, 19



### such as the pesticide root zone model that we use in our 20



### drinking water exposures, or SEAWAVE

- Q, which is another 21



### USGS model that they have used to evaluate pesticide 22



### trends over time. 23

24



### I also noted that most of these models are fairly data

25



### intensive. And one of the comments was well, it may be 26



### easier to use WARP in combination with some statistical 27



### approach such as kriging. 28

29



### So with that background, I am going to begin by talking 30



### about looking at some of the approaches we have evaluated 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### for characterizing the uncertainty monitoring in capturing 1



### day

- to

- day patterns. 2

3



### As I pointed out, the SAP recommended using intensively 4



### sample d monitoring data. We are aware of, in general, a 5



### couple of monitoring datasets that monitor atrazine either 6



### daily or near daily during the periods of time when you 7



### are expected to find atrazine in the water, which roughly 8



### corresponds from April to August /September timeframe, from 9



### the time the corn is planted to well into the season when 10



### you are likely to find the high runoff periods. 11

12



### One of these is from Heidelberg University, the National 13



### Center at Water Quality Research. They have collected 14



### data on a number of watersheds of various size in Ohio. 15



### We looked at the Maumee River, which is roughly a 17,000 16



### square kilometre catchment in Ohio. 17

18



### Another dataset is the monitoring Syngenta has done on 19



### atrazine for the ecological exposure monitoring. This was 20



### a separate monitoring program that focused on, primarily, 21



### headwater watersheds and looking at the impacts on aquatic 22



### plant communities. 23

24



### It is a much smaller watershed, but it gives us an 25



### opportunity to look at a range of exposures. They do have 26



### monitor ing that covers more than just the spreads from 27



### Ohio well into Missouri and Nebraska, so it gives us a 28



### broader geographic range. 29

30



### As we have developed the approaches, we picked two 31



### particular datasets as an evaluation approach. One was 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Maumee River from 1995 and the other one was Missouri

- 01 1



### from 2007. Missouri

- 01 had a fairly high peak. Maumee 2



### River had much lower concentrations. It gives us a way of 3



### bracketing that information. 4

5



### So one of the first approaches we did was

-- let's take a 6



### look at how w ell we can characterize the uncertainty of 7



### different sampling frequencies in estimating the exposure 8



### varying durations. 9

10



### Essentially, we are asking the question; how well do 11



### estimates that are based on sampling at different 12



### intervals compare to the true v alue, and can we develop a 13



### multiplication factor of some sort based on sampling 14



### frequency and duration of concern? 15

16



### To do this, we defined a sampling window across the 17



### datasets. And the sampling window range from 4

- day 18



### intervals up to 28 days. Then we u sed a bootstrapping 19



### simulation to select a random day within each of those 20



### sampling windows to reconstruct a monitoring dataset for 21



### those. And we did that 10,000 times for each of these 22



### four windows that we looked at, ranging from 4

- day 23



### intervals to 28

- da y. 24

25



### The community water system is represented by the 7

- day 26



### intervals. Then for each of those sampling simulations, 27



### we derived the 1

- day maximum, or peak, as well as a 28



### maximum for 7

- , 14

- , 28

- and 90

- day rolling average for 29



### each of those. 30

31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And then wha t we did is we took those 10,000 simulations 1



### for each of the sampling intervals and compared the true 2



### maximum concentrations against the 5th percentile of those 3



### estimates. 4

5



### That ratio, we have described in the paper as a bias 6



### factor, which we look at as a potential multiplicative 7



### factor that could be applied to exposure estimate, 8



### depending on the sampling frequency and the duration of 9



### exposure. 10

11



### I want to emphasize that this is more of a proof of a 12



### concept based on two examples. It is not an exhaustive 13



### analysis. For instance; we have only sampled one. We 14



### only looked at one year in each of these sites. We have 15



### multiple years on those. 16

17



### To develop this further, we would obviously be looking 18



### across the years. We would also probably be looking at 19



### sites that represent not just flowing water

-- and both of 20



### these, by the way, are flowing water bodies, but we look 21



### at reservoirs, looking at water bodies of different sizes. 22



### So this is more of an illustration purpose of how this 23



### might be applied. 24

25



### The two tr ends I want to point out, and first off, is that 26



### the multiplicative bias factor or the uncertainty 27



### increases as your sampling interval gets wider , w hich 28



### means that it gives you obviously less data to work with. 29



### The other point is that, as your duration of concern 30



### expands, becomes larger, then your uncertainty factor 31



### decreases. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And I want to point out, I would caution too much against 2



### saying, "All right. This is a small watershed; this is a 3



### large watershed and the bias factors are greater for the 4



### small t han the large." We are not sure if that is the 5



### case of the watershed or if it is the case of the 6



### magnitude of the concentration. 7

8



### And for example, Maumee River

-- we used the 1995 data for 9



### this

-- in the previous SAP we did some analysis with 2008 10



### data w here the maximum concentration was around 50 parts 11



### per billion rather than 14. We would like to do a little 12



### further analysis using wider range of data to see exactly 13



### how that bias factor would play out. And that kind of 14



### leads us to the next approach we were considering. 15

16



### Kind of following up on the recommendation of the SAP is 17



### that, when you are not sure what that exposure period is, 18



### you may be better off investing your resources in trying 19



### to capture the pattern of atrazine concentrations, and we 20



### starte d looking at ways that we might be able to do that. 21

22



### The SAP had recommended combining a regression based model 23



### such as WARP with either a deterministic model or a 24



### geostatistical approach. We operated on the philosophy of 25



### lets go simpler

-- the simpler, the better

-- in terms of 26



### turning things around, and we started looking at WARP in 27



### combination with the geostatistical approach. 28

29



### But as we started building on that, what we found is that 30



### -- we found some promising results in constructing the 31



### shape of tha t time series using the geostatistical 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### approaches and conditional simulations with some of the 1



### more intensive sampling. 2

3



### And so, this may be a little bit of departure of what the 4



### SAP recommended, and that is one of the reasons why we 5



### want to bring this ba ck to get your reaction to this, 6



### because is it a little bit

-- in some cases, we think we 7



### might be able to construct fairly reliable time series 8



### just with a geostatistical analysis. In other cases, it 9



### looks like we would need to move on to add WARP in the re. 10

11



### So I want to present a little bit about how we went about 12



### approaching this. This is kind of the analysis strategy 13



### that we developed after working around with the data for a 14



### while. This particular figure is in

-- I think it is 15



### Figure 6.1 in the back ground paper. It outlines the 16



### approach we are considering. 17

18



### And we began by looking at the time series, the frequency 19



### of sampling. In this case, we basically looked at are 20



### there 15 or more data points in the time series, and that 21



### roughly equates to a sa mpling frequency of seven days or 22



### more often. 23

24



### And what we found in there is that, if you have sufficient 25



### samples, we can provide reasonable time series estimates 26



### by going through a variogram analysis, doing some kriging 27



### of that, and then doing statistic simulations. 28

29



### With less frequent sampling, then you need to do something 30



### to fill

- in in the dataset. We presented a couple of 31



### options in the Appendix D

- 2. One was looking at covariate 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### to estimate concentration either with something like 1



### another pesticide or with flow. 2

3



### We also looked at

-- and what we will highlight here is 4



### using WARP to provide a percentile of the time series, and 5



### then using it in relation with flow percentiles to create 6



### the time series. So, to begin with, because we are 7



### looking at wee kly samples for the community water systems, 8



### I am going to focus on the approach we did for our 9



### dataset, but would be that robust. 10

11



### Now, before we apply these geostatistical methods, we 12



### needed to consider stationarity. And essentially, 13



### stationarity is t he assumption that there is an equal 14



### probability of occurrence, in this case, regardless of the 15



### time. 16

17



### This is a typical chemograph over a year for atrazine. If 18



### you were to apply this on an annual basis, then as 19



### stationarity, it is probably not going to hold. There are 20



### times outside the use period where you are not likely to 21



### find atrazine in the waters. 22

23



### However, as we took a closer look, if you narrow that 24



### window to what we describe as the runoff period

-- and 25



### that basically coincides from the time the pesticides are 26



### going to be applied to the field and after that. You can 27



### define a runoff period within the chemograph where we can 28



### at least make a contention that stationarity will hold 29



### well enough for this particular analysis. For atrazine, 30



### we can c ome up with a reliably predictable period, 31



### depending on the corn planting season. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Now, as we did some of the exploration with the Heidelberg 2



### data with some other pesticides, what we did find is that 3



### is probably going to be more difficult for some of the 4



### insecticides that have a less predictable or less 5



### consistent application period. And so, this may work well 6



### for atrazine or other corn herbicides, but it may not 7



### necessarily work for some of these other pesticides. 8

9



### F or that runoff season, what we did is we analyzed the 10



### monitoring points for a covariate structure in time. We 11



### could have used the correlogram and we chose to use a 12



### variogram, which is what you see here. 13

14



### E ssentially, what we did is we took the 1995 Maumee River 15



### data and simulated a 4

- da y sampling in that, and we also 16



### simulated a 7

- , 14

- and 28

- day samplings, so I wanted to 17



### show you a couple of examples. A couple of terms for 18



### those who may not be familiar ; t he Nugget describes the 19



### amount of the variance that results from random processes 20



### that do not have a temporal correlation, and there would 21



### be such things as measurement error. 22

23



### The Sill represents the variance value where the variogram 24



### levels off. And the Range is that time to where you reach 25



### the Sill. Within that Range, the monito ring values are 26



### auto

- correlated. So, for Maumee River, that Range of 27



### autocorrelation is roughly 50 to 60 days. 28

29



### When we pulled together this analysis we used a visual 30



### process to define the model rather than the least squares 31



### method. And because of that , as we did the kriging, we 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### put more emphasis on fitting the nearer points in the 1



### variogram. We also had more data pairs in the nearer 2



### points than the farther points. But that was the approach 3



### we used to fill in between the time series. 4

5



### And what you s ee here are realizations of the atrazine 6



### time series using the variogram models to fill in the data 7



### points. The red line, which you can sort of see on these 8



### is the actual time series from the daily measurements. 9



### The black points are the realizations of t he time series 10



### using the variogram models, and the bars around each of 11



### those points represent the standard deviation. 12

13



### A couple of things I want to point out here is that when 14



### you look at

-- this is based on 4

- day sampling intervals. 15



### This is 7

- day sam pling intervals. When you look at these 16



### two, what you do see is that the variogram models using 17



### conditional simulations provide a reasonable 18



### characterization of the time series. 19

20



### What happens when you started going to 14

- day sampling 21



### intervals, your var iogram structure started falling apart; 22



### looking fairly messy. Your standard deviations got a lot 23



### larger. We missed the highest sample peak. 24

25



### At 28 days, we really could not construct a variogram. 26



### What you see here is for illustration purposes and that 27



### was a variogram constructed based on daily flow. And this 28



### is one reason why if we go back to that figure we use that 29



### cut

- off, in terms of the amount of data, the approach we 30



### took. 31

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### Now, if we take a look at the Missouri dataset, what we 1



### did find is tha t the variogram models do not fit as well 2



### as they did for the Maumee River dataset. And your range 3



### is a lot shorter and it may very well reflect the spiky 4



### nature of the smaller watersheds. 5

6



### But as you go from here, these are the variograms from the 7



### 4

- day sampling intervals and for the 7

- day sampling 8



### intervals. I want to show the realizations of the time 9



### series from those variograms. 10

11



### And a couple of points; we still had a fairly good

-- 12



### except for the fact that we did miss the peak

-- we did do 13



### a fai rly decent recreation of the time series for four and 14



### seven days, and once again, it started falling apart at 15



### the 14

- and 28

- day intervals. 16

17



### And I do want to point out is that, the sampling

-- and it 18



### was a 4

- and 7

- day intervals we simulated

-- did miss that 19



### peak concentration. But what we wanted to see

-- this 20



### provided us an opportunity to take a look, as we go 21



### through with the assessment, is how much that impact has 22



### from missing that peak concentration as it carries through 23



### in analysis. 24

25



### Okay. I am going to jump back to the Maumee River. For 26



### the case study you are going to hear about later this 27



### afternoon, what we did was we generated a thousand 28



### conditional simulations of the time series

-- and in this 29



### case for the Maumee River, as well as for the M issouri

- 01 30



### dataset

-- using the variogram model that was constructed 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### from the 7

- day sampling intervals, which represented what 1



### we are seeing in the community water system. 2

3



### The black line you see here, which you can see a lot 4



### better in the previous, is the known concentration. It is 5



### based on most intensive sampling. So this is the daily 6



### time series. This is the 4

- day rolling average that is 7



### constructed from the daily time series; the 14

- day and 28

- 8



### day rolling averages that we constructed from the time 9



### series. 10

11



### So what we did is, for each of those thousand simulations, 12



### we took at 95th and a 5th percentile, which is what the 13



### upper red line represents; the 95th percentile, those 14



### thousand simulations, and the lower red line represents 15



### the 5th percentile, those thousand simulations. And so, 16



### we did this for the daily time series and we looked at the 17



### constructive 4

- , 14

- , 28

- day rolling averages as well. 18

19



### If we take a look at the Missouri

- 01, as you can see, we 20



### did miss the actual maximum peak and we star ted looking at 21



### those simulations. In the 95th, we were still 22



### underestimating the maximum peak. But when you move to 23



### something as short as a 4

- day rolling average, the 95th 24



### percentile did provide a reasonable upper bound on the 25



### estimate of that exposure. 26

27



### We want to examine this in more cases to see whether it 28



### holds true or this one just happened to be a fortunate 29



### circumstance. We are also looking at, ultimately

-- what 30



### we are interested in is how well the estimates that we 31



### provide here, based on monito ring, represent what we are 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### going to see in the internal dose study to what you will 1



### see in the case study later. 2

3



### So let's go back to those 14

- or 28

- day averages. This is 4



### not an issue with the community water system monitoring 5



### that is going on now bec ause they have done weekly 6



### samplings, but it may be an issue if we wanted to pull in 7



### other monitoring datasets that are likely to be sampled 8



### less frequently, or if ultimately we want to try to apply 9



### this to other pesticides. But typically, if you get 10



### sam pling every two weeks or monthly, you are doing pretty 11



### good on a lot of the monitoring. 12

13



### As I pointed out, we evaluated a couple approaches, and 14



### one is a covariate approach using other monitoring data or 15



### flow data. And one of the things I wanted to po int out 16



### here

-- because this played into how we went from a 17



### percentile time series to a time series distribution

-- if 18



### you trying to do covariate analysis between flow and 19



### monitoring data over a long time period, you really do not 20



### find a correlation. 21

22



### Ho wever, if you narrow that window primarily to the time 23



### whenever your pesticide is applied and shortly after, we 24



### did see some correlations between flow and monitoring 25



### data. So we took advantage of that in the approach that 26



### we did use, and we are going to p resent to you. 27

28



### So we go back to something like the sampling every two 29



### weeks or monthly. We found that the data was too sparse 30



### to really go directly into variogram analysis, so we 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### needed some way of filling in that time series in between 1



### those data poin ts. 2

3



### So, what we did is we used WARP, pulling together the 4



### characteristics for the monitoring site. We used that to 5



### estimate a time series and that gave us a percentile 6



### distribution of your monitoring time series. Then we 7



### could place the existing monit oring in context with that 8



### percentile distribution. 9

10



### Then we took advantage of what we knew about those 11



### percentile distributions and we ranged the flow 12



### percentiles and matched them up with the percentiles from 13



### WARP, and then we could rearrange that based on the actual 14



### time series. So we could reconstruct the time series from 15



### that percentile distribution. And once we did that, we 16



### could proceed through the variogram and kriging and 17



### stochastic simulations. 18

19



### I am going to just show you an example that w e presented 20



### in Appendix D

- 2. When we are looking at the Maumee River 21



### data, we used a 28

- day sampling intervals. If you 22



### remember I pointed out, we really could not even construct 23



### a variogram with those 28

- day intervals because there was 24



### too little data in between. 25

26



### But once we merged that with WARP estimates

-- and what we 27



### ended up doing, if you read through that appendix, we did 28



### not have all the WARP parameters we needed for the Maumee 29



### River watershed at the time. We did have a couple of the 30



### atrazine e co

- monitoring sites located nearby and we use 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### those WARP data parameters to bracket this just as a proof 1



### of concept to see how well this might work. 2

3



### I am showing you one that we did with the Ohio '03 4



### monitoring from the WARP site. We used that and rela ted 5



### it back to the flow to reconstruct a time series, and what 6



### you see is that we were able to construct a variogram with 7



### that merged dataset, and we went from that variogram to 8



### the conditional simulations. 9

10



### We came up with the realization that we felt w as not too 11



### bad of a fit for the time series. You can see there is 12



### the actual peak concentration so we were not too far off 13



### on that. We did miss a little bit there. I think we 14



### are likely to see greater uncertainty bounds around the 15



### estimates from the le ss robust monitoring data but it does 16



### give us an option for providing a time series estimate 17



### from that dataset. 18

19



### So we do have a couple of questions that were related to 20



### that approach. What I would like to do, if we are going 21



### to address this, is to move on to year

- to

- year patterns, 22



### because if we are going to address the uncertainties in 23



### estimating pesticide concentrations from monitoring data, 24



### we do need to account for that year

- to

- year variability as 25



### well. 26

27



### And once again, we are looking at this separ ately, but in 28



### the end we are going to have to integrate that to show 29



### that we are not compounding uncertainty that may not be 30



### compounded. 31

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### We did a quick look at the atrazine monitoring program. 1



### There are more than a hundred community water systems 2



### inclu ded in this program that have at least six years of 3



### monitoring data. 4

5



### And what we did, as a quick look at those, is that we 6



### looked at the highest maximum annual detection and 7



### compared that to the lowest maximum annual detection for 8



### each of the community water systems that had at least six 9



### years of data. And what we found is that the difference 10



### between the highest measured concentration and the lowest 11



### measured concentration in a given year might be an order 12



### of magnitude or more. 13

14



### The issue for atrazine comes down to how many years of 15



### monitoring are really necessary to characterize that 16



### expected range in concentrations from year to year. And 17



### alternately, can we use modeling in addition to monitoring 18



### to provide a characterization to that year

- to

- year 19



### vari ability? 20

21



### We have presented a few options in the background paper. 22



### One is to take a look at monitoring in spans of longer 23



### periods of time. And a couple are looking at modeling 24



### type approaches that we might be able to tie in with the 25



### existing monitoring to provide some characterization of 26



### the range and year

- to

- year variability. 27

28



### One is a PRZM Hybrid model. I think Syngenta has put a 29



### couple of papers in the docket related to their approach 30



### to the hybrid model. In effect, what you are going to do 31



### is yo u run PRZM with the watershed

- specific inputs, the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### rainfall data for that particular year. I think, in their 1



### analysis they were evaluating the utility of using this to 2



### fill in between monitoring datasets. What we were looking 3



### at is, this may be a way to

-- by calibrating this to the 4



### concentration monitoring data for a particular year, then 5



### running that model for additional years, and we might be 6



### able to use this to characterize a range of concentrations 7



### over time. 8

9



### With PRZM, we do have weather datasets that run at least 10



### 30 years of data that we could use to characterize that. 11



### That is data

- intensive in that it does require pulling 12



### together a lot of site watershed

- specific data to work 13



### with. 14

15



### One other option is to use WARP to provide a way of 16



### characte rizing the range concentrations by varying the 17



### temporal patterns. In particular, you can look at a range 18



### of your May/June precip and the atrazine use intensity 19



### over a likely range of values. And by running that, it 20



### may give a way of characterizing that r ange. 21

22



### One thing I will point out is, one of the biggest 23



### uncertainties in input data that we have is atrazine use 24



### intensity, which is a major driver in WARP. And it is 25



### possible that the uncertainty in estimating the use 26



### intensity may override the uncert ainty in all the other 27



### parameters. So that is something we are wrestling with. 28



### We laid those options out in the background paper and we 29



### have asked for the panel to provide us some 30



### recommendations and feedback on that approach. 31

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### And finally, I am going to wrap up with the spatial 1



### patterns, and you will be glad to know that we are not 2



### asking you a question on this. We are actually punting 3



### this to a future SAP that

-- since I have got to be 4



### involved in another one, we might as well go with that. 5



### What we are asking is what can we say about pesticide 6



### exposures from one site ? How much can we apply that to 7



### another site? Can we link the results from the monitored 8



### data sites to other sites either based on some type of 9



### statistical design or similarities in sit e 10



### characteristics? 11

12



### Now, it is important to point out that the community water 13



### systems that are included in the atrazine monitoring 14



### program are based on compliance monitoring data. In other 15



### words, these were quarterly samples that were taken, and 16



### essent ially, Syngenta did an analysis and any community 17



### water system that had annual average atrazine 18



### concentrations from the quarterly samples of 1.6 parts per 19



### billion or greater were included in the monitoring 20



### program. 21

22



### As it turns out, this map

-- the backg round you see on 23



### that map

-- the dark represents a watershed vulnerability 24



### assessment we did based on WARP and WARP monitored. 25

26



### The darkest blue that you see there are the watershed 27



### areas that we identified as being the most vulnerable, 28



### likely to have th e highest atrazine concentrations based 29



### on WARP. The lighter blue is the next highest here. As 30



### it turns out, the community water systems that were 31



### included in the monitoring program all fell within these

- 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### - almost all fell within the highest two vulnerab ility 1



### tiers based on WARP. 2

3



### While this helps corroborate the vulnerability approach we 4



### used, community water systems do not represent a 5



### statistical sampling across the vulnerability tiers. And 6



### we may not necessarily be able to infer results of these 7



### t o other community water systems that occur in the same 8



### vulnerable areas, not without some additional work. 9

10



### Now, fortunately, we have had a separate analysis looking 11



### at vulnerable watershed properties for the eco

- exposure 12



### assessment, and we have identifi ed characteristics in 13



### those watersheds that are associated with sustained 14



### elevated atrazine concentrations. 15

16



### Essentially, you are looking at watersheds that have a 17



### fairly high atrazine use intensity. They are dominated by 18



### soils that have a shallow soil l ayer that restricts 19



### drainage. And in fact, what you are doing is you are 20



### enhancing runoff and spreading the runoff over a larger 21



### period of time. And related to that, when you set it back 22



### on a national scale, there is a rainfall component that 23



### contributes to that. 24

25



### We will be, in 2012, coming back and saying, "All right. 26



### Based on our analysis, based on the monitoring, these are 27



### what we have determined to be the watershed 28



### characteristics and threshold values in those watersheds 29



### that would drive high expo sure for the eco

- exposure." 30

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### It would be simple enough, looking at these community 1



### water systems, to take a look at what the characteristics 2



### are within those to determine whether we can make a 3



### similar relationship in that regard. 4

5



### So that is our plan ned approach for the spatial component, 6



### to put those in context. It is important just to keep in 7



### mind we are confident that what we are dealing with are 8



### community water systems that are in vulnerable tiers, just 9



### making sure we can make inferences to other s that may also 10



### reoccur in that tier. 11

12



### So I am about to wrap up. This is a simple overview. The 13



### focus of what we are bringing on monitoring to the SAP is 14



### looking at addressing temporal variability. And we have 15



### questions for the panel regarding the met hods we use to 16



### address both short

- term variability

-- in other words, how 17



### well can we address the variability in day

- to

- day 18



### variations given the sampling interval frequencies we have 19



### -- as well as to look at year

- to

- year variability. 20

21



### So we have looked at potential of taking a multiplicative 22



### bias factor to whatever exposure estimate we have and 23



### using that as a way of characterising the variability, or 24



### alternately, generating, creating a time series analysis, 25



### time series distribution that could be used in that 26



### regard. 27

28



### And honestly, we may use both. We may, in the end when it 29



### comes down to it

-- depending on the duration of concern 30



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### works better than the other, but we would like to have 1



### that option to look at. 2

3



### And we have also asked questions about how best to address 4



### that year

- to

- year variability in terms of how long do we 5



### need to keep this monitoring going? How long do we need 6



### to look at it? And with that, I am going to quit talking 7



### and open t his up for questions. 8

9



### DR. DANIEL SCHLENK : Thanks a lot. Dr. Coupe. Glad you could 10



### make it. Would you mind just briefly introducing yourself 11



### and where you are from and your area of expertise for the 12



### panel just so that everyone knows who you are? 13

14



### DR. R ICHARD COUPE : Sure. I am Richard Coupe. I am with the 15



### U.S. Geological Survey. I am working out of the 16



### Mississippi Water Science Center and spent most of the 17



### research time on the fate and transport of agricultural 18



### chemicals. 19

20



### DR. DANIEL SCHLENK : Than ks a lot. Again, let me just remind 21



### speakers to please introduce yourself before speaking into 22



### the microphone so that we know who is talking. So do we 23



### have any questions about water sampling strategies? Yes, 24



### Dr. Lee? 25

26



### DR. HERBERT LEE : When you say you used ordinary kriging, does 27



### that mean you estimated an unknown mean? 28

29



### DR. NELSON THURMAN : I am actually going to punt this over to 30



### Jim Hetrick who did the detail kriging analysis. 31

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### DR. HERBERT LEE : So when you say you used ordinary kriging, 1



### does that mea n you estimated an unknown mean level for the 2



### function? 3

4



### DR. JAMES HETRICK : All I know is that we used the ordinary 5



### kriging that was in GEOEAS. All right? 6

7



### DR. HERBERT LEE : Okay. So then my follow

- up questions is, 8



### because normally ordinary kriging you are estimating mean. 9



### On slide 16, the Maumee river, the 28

- day intervals, they 10



### do not look anything like the real data, and so I am 11



### wondering if you think that may be because it's mean 12



### reverting to the wrong level as opposed to mean reverting 13



### to zero or s omething like that, or if you have an 14



### alternate explanation for why that does not look anything 15



### like it? 16

17



### DR. JAMES HETRICK : First off, if you look at those 28

- day 18



### intervals on the

-- when we went back and looked at the 19



### variograms for that particular samp ling interval, we 20



### essentially had a Nugget. There was no real temporal 21



### correlation. 22

23



### I was trying to squeeze something out of nothing, to be 24



### quite honest with you. So what I did is I went back and 25



### took the flow data that we actually had for that site, fit 26



### a variogram to it and then used that variogram in the 27



### stochastic conditional simulation. So that is probably 28



### one of the reasons why it does not fit, I would guess. I 29



### don't know. 30

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### DR. NELSON THURMAN : And this is one reason why we knew needed 1



### to do s omething else for the 14

- and 28

- day intervals. 2

3



### DR. JAMES HETRICK : Actually, Nelson, can you put up the 4



### Missouri site, the conditional simulations? Actually, 5



### that is a representation, a 28

- day is essentially a Nugget 6



### for that 28

- day, and that is what we would have probably 7



### seen in that 28

- day for the Maumee River if we had put a 8



### Nugget model simply in the stochastic simulation. 9

10



### DR. KENNETH PORTIER : On that same graph, how does the program 11



### handle potential negative values? I mean, are you just 12



### truncati ng at zero; are you censoring at zero? 13

14



### DR. JAMES HETRICK : Yes. You can truncate at zero. It does 15



### truncate at zero. And in addition to that, which is kind 16



### of interesting

-- I do not know that it would be 17



### interesting to get SAP's input on

-- you can als o 18



### extrapolate to a maximum value and it can be higher than 19



### the value that is in your dataset. 20

21



### So one idea, at least in my mind, was to take the bias 22



### factors that we have for a certain sampling interval and 23



### we could multiply that out from the peak and be able to 24



### put in a maximum value to make sure that we are not 25



### underestimating. 26

27



### DR. RICHARD COUPE : I am sorry if you have already discussed 28



### this. Let me know and we could talk about it later; but 29



### explain to me how the bias works, how you plan on applying 30



### i t. 31

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### DR. NELSON THURMAN : What we were looking at is exploring 1



### whether we could take a bias factor and

-- let's say a 28

- 2



### day tox window of exposure window. And so, we come up 3



### with

-- based on weekly sampling, we estimate here is your 4



### maximum 28

- day rolling average concentration. The idea 5



### would be we'd take that bias factor where you'd go to the 6



### table and look up where you have 28

- day duration window 7



### and your 7

- day sampling intervals and multiply that 8



### exposure by that factor. 9

10



### Now, I do want to point out th at if we took that approach, 11



### it would be difficult to do what we are doing in a case 12



### study, which is folding that time series into the case 13



### study to get an internal dose. So that is one of the 14



### reasons why we were looking at that as one approach, but 15



### also looking at it in terms of creating that time series; 16



### filling in between. 17

18



### DR. KENNETH PORTIER : If you look at the 4

- day interval and you 19



### mentioned that you use common kriging, and I was sitting 20



### there thinking, you know, this is really just time series 21



### m odeling, right? In time series modeling; you have a mean 22



### pattern and you have variability. It is structured 23



### variability in this case. You are putting on a variogram 24



### on autocorrelation function. You are saying that the 25



### residuals

-- so in my thinking on common kriging, that 26



### mean is usually just a mean. It is not a function of 27



### time. It is just a constant. Am I correct? 28

29



### I was thinking in what they call generalized kriging, you 30



### are actually smoothing, so your mean is a function of 31



### time. You are pulli ng a little bit of the pattern out and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### then you are looking at residual variability. And if you 1



### were doing generalized kriging, I would think that‟s what 2



### you would get because you're really following pretty much 3



### the general pattern in your simulations. T hey are all 4



### kind of following the pattern over time with some noise. 5



### So your simulations create a bunch of noisy patterns that 6



### are about that general pattern. So maybe I am kind of 7



### confused between common and generalized kriging. 8

9



### DR. JAMES HETRICK : Wel l, let me go back and tell you how we 10



### did the analysis and then I may straighten

-- it may 11



### either cloud up the issue or may clear up the issue; I 12



### don't know. But the bottom line is, what we did is 13



### essentially

-- the data that we used to build the 14



### variogra m off of is the same data that we used in the 15



### conditional simulation without any type of in

- filling. So 16



### the missing data points there are strictly estimated using 17



### a stochastic approach, okay? We did not use the best 18



### linear unbiased estimate for estimatin g those missing 19



### values. 20

21



### DR. DANIEL GRIFFITH : When you did the variogram analysis, you 22



### did not use the log transformation? You did it on the 23



### original? 24

25



### DR. JAMES HETRICK : No. I did a log transformation in the 26



### variogram analysis. 27

28



### DR. DANIEL GRIFFITH : Okay. So the back transformations would 29



### not have negative values; is that right? 30

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### DR. JAMES HETRICK : That is probably true; yes. By the way, 1



### the conditional simulation was done using a z

- score 2



### approach, so those were normalized through that program. 3

4



### DR. KENNETH PORTIER : I want to remind Nelson that we talked at 5



### lunch, on the next slide

-- I think it is the next slide

- 6



### - where we talked about the five percent and 95 7



### percentile, and I was going to ask you to kind of remind 8



### us because it is not clear i n the write

- up exactly what 9



### the five percent and 95th percentiles really mean. 10

11



### DR. NELSON THURMAN : Okay. What we did is, we did those 12



### conditional simulations, a thousand simulations. And 13



### essentially what we did is we went across each day of the 14



### simulat ion to come up with the 95th and 5th percentile. 15



### So, in effect

-- we were discussing

-- you are going to 16



### end up with a wider range because you are looking at that 17



### percentile for each day. 18

19



### DR. KENNETH PORTIER : So they did a thousand simulations, then 20



### you take one day and you look across a thousand simulated 21



### values for that one day and you get the five percentile 22



### and the 95th percentile. And what that tells me is that 23



### it is 95th percentile simulated curve there is not any one 24



### of the patterns that you simu lated; it is really the worst 25



### or the worst, right? And the 5th percentile is kind of 26



### the fifth best of the best. 27

28



### DR. HERBERT LEE : So, I want to clarify now because I am a 29



### little confused. When you did the conditional 30



### simulations, what scale did you do them on; the log scale 31



### or the original scale, the z

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### DR. JAMES HETRICK : We used the z

- score for the

-- that‟s in 2



### the 6M. 3

4



### DR. DANIEL SCHLENK : Any other questions? Clarifications? 5



### Okay. Let's move on to our next presentation. Dr. 6



### Mendez, your third of three there. 7

8



### DR. ELIZABETH MENDEZ : Good afternoon. Yes, three of three. 9



### Now I can sit back and enjoy the discussions later on. So 10



### throughout the day, you have heard a lot of discussion 11



### about mode of action, about epidemiology, about 12



### pharmaco kinetics, water monitoring now. 13

14



### In addition to all of those things that we typically have 15



### to evaluate for all chemicals, for pesticides, we have a 16



### unique situation that we have a statute that speaks to us 17



### about the sensitivity of infants and children. S o in this 18



### presentation, what I am going to do is to describe the 19



### state of the science with respect to the potential for 20



### pre

- and/or post

- natal toxicity and the completeness of 21



### data with respect to toxicity in infants and children. 22

23



### So as I just said, we h ave a statute that governs 24



### pesticide regulation, and perhaps we would start with that 25



### so that we are all on the same page. 26

27



### The Federal Food, Drug and Cosmetic Act, as amended by the 28



### Food Quality Protection Act in 1996, requires the agency 29



### to give special attention to the potential risk to infants 30



### and children. Specifically, FQPA instructs EPA in making 31



### its "reasonable certainty of no harm" finding that in "the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### case of threshold effects, an additional tenfold margin of 1



### safety for the pesticide chemical re sidue and other 2



### sources of exposure shall be applied for infants and 3



### children to take into account potential pre

- and post

4



### natal toxicity and completeness of data with respect to 5



### exposure and toxicity to infants and children." 6

7



### Section 408(b)(2)(C) furth er states that "the 8



### Administrator may use a different margin of safety for the 9



### pesticide chemical residue only if, on the basis of 10



### reliable data, such margin will be safe for infants and 11



### children." 12

13



### This additional margin of safety is referred to as the 14



### " FQPA Safety Factor." So in essence, all these words, 15



### what they mean is, when we start looking at a pesticide, 16



### we start out with a 10x FQPA factor that is automatically 17



### on, and then we have to, based on the data that we have in 18



### front of us, we may reduce i t; we may change it but it has 19



### to be, from the get

- go, we start with a 10x. 20

21



### Now, this talk about both exposure and toxicity, but as 22



### Nelson just finished with his presentation, we are still 23



### dealing with the exposure uncertainty so I am not going to 24



### reall y address that in this talk. I am going to 25



### concentrate on hazard and toxicity. T he hazard 26



### considerations; the important issue is do we have 27



### available data to assess critical life

- stages? And if you 28



### remember from my talk earlier this morning, I said tha t 29



### when we have a neuroendocrine mode of action like the one 30



### we have for atrazine, this becomes a particular critical 31



### issue because the hormonal environment changes 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### significantly between life

- stages, so that is something 1



### that we really have to be very cogni zant of as we move 2



### through our process. 3

4



### We have to consider all the relevant information, mode of 5



### action obviously, the animal database of toxicity studies, 6



### the dose response relationships, the human relevance of 7



### the animals findings and, last but not le ast, epidemiology 8



### findings. 9

10



### So back in 2003 when we came to the SAP, in 2000 actually, 11



### the neuroendocrine mode of action was determined to be 12



### relevant for reproductive and development effects, even 13



### though it is not for the mammary gland tumor development

. 14



### And during the epidemiology findings that were discussed 15



### in the September SAP meeting, what we heard from the panel 16



### and what the agency concluded was that there is 17



### qualitative information on human relevance of the animal 18



### findings, but that they were not sufficiently robust to 19



### establish a causal associations. 20

21



### So, we were seeing things that were somewhat similar in 22



### epidemiology data to what we were seeing in the toxicity 23



### data. So we felt that we could still believe our premise 24



### that these findings were r elevant for human risk

25



### assessment. 26

27



### So let's talk about what we do have in terms of 28



### experimental toxicity studies. We have core guideline 29



### toxicity studies. These are a developmental toxicity 30



### studies in two species; rat and rabbit. And for those who 31



### don 't know how our guideline studies are done, those 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### studies usually start with exposure during the 1



### implementation time, usually around gestation day 6 2



### through gestation day 21 when the animals are sacrificed 3



### and their fetus' are examined. 4

5



### And we have a mu lti

- generation reproduction study. That 6



### study actually

-- exposure starts 10 weeks prior to mating 7



### of the animals. It continues throughout mating, gestation 8



### and lactation, and so the pups are exposed in utero and 9



### also through lactational exposure postnat ally; and that is 10



### what we typically get from most pesticides. 11

12



### But in addition to that, in the case of atrazine, we have 13



### a rather robust dataset of specific and special studies 14



### that concentrate on specific life

- stages, mainly 15



### gestation, perinatal, peripub ertal and reproductive age. 16

17



### And when we last visited the SAP before this re

18



### evaluation, one of the things that we heard from the panel 19



### was we need a little bit more information on the 20



### peripubertal period. 21

22



### Now, now we have all this data, and thus far, none of the 23



### available studies have provided us an endpoint lower or 24



### more sensitive than the studies on LH attention in the 25



### adult female rat. So I am just going to go quickly 26



### through this. 27

28



### Now, we have a lot more studies than these, but I have 29



### just sele cted the ones that are the most sensitive within 30



### the datasets. And as you can see, we have for gestational 31



### exposure, the lowest NOAEL that we have is 10, with a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### LOAEL of 50, and that is delayed preputial separation 1



### after exposure from gestation day 14 thr ough parturition. 2



### And from Fraites et al., data that was in Davis et al., 3



### data that came in around April of this year, the NOAEL is 4



### 20 and the LOAEL is 100. 5

6



### And we have the Fraites et al. is looking at males. The 7



### Davis et al. is looking at females and their siblings. 8



### The endpoints are decreased pup weight and pup viability 9



### and delay in VO , vaginal open in the Davis et al. dataset ; 10



### and the exposures were from gestation day 14 through 21. 11

12



### Perinatal exposure we have data from Stoker et al. in 13



### 1999, an d this is postnatal day 1 through 4 and postnatal 14



### day 6 through 9. And the lowest NOAEL in there is at 12.5 15



### and a LOAEL of 25 and the effect is prostatitis. 16

17



### Peripubertal exposure, which was the period that initially 18



### we needed more information on, we g ot more information and 19



### then some. But you can see that the lowest that we have 20



### is a delay in preputial separation with a NOAEL of 6.15 21



### and a LOAEL of 12.5. 22

23



### Now what I want to remind you is that, when we do a 24



### benchmark dose analysis for the LH attention after four 25



### days of exposure with Cooper et al. data, the BMDL is 26



### 2.56. 27

28



### In addition to these studies, we recently received the 29



### completed multiple life

- stage study from Syngenta. This 30



### is an exposure encompassing prenatal, postnatal, 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### peripubertal and adul t

- life

- stages. It evaluated female 1



### offspring only. 2

3



### The doses were 0, 6.5, 25 and 50, and no effects on LH 4



### were seen at doses of 50 milligrams per kilogram or less, 5



### and that is kind of inconsistent with a preponderance of 6



### the peer review literature whe re we are seeing things 7



### starting to happen with LH around 6

- ish or even lower, 8



### depending on the duration, more like 3. 9

10



### To be honest, we have looked at that data and we can't 11



### quite figure out why that inconsistency is happening. It 12



### appears to be a well c onducted study over all, so we are 13



### still puzzled by that. 14

15



### What they do see is a slight delay in vaginal opening or 16



### delay of 1.4 to 2.3 days at 50 milligrams per kilograms 17



### per day. And what is interesting about that is that this 18



### delay is seeing if the ex posure started in utero, but not 19



### if it started postnatally. So let me just kind of quickly 20



### flash up the study design so that you can see how that 21



### goes. 22

23



### Cohort 1 in Subset A; you have exposure from conception 24



### gestation day 0 through lactation day 0 of th e dams, then 25



### from postnatal day 21 through the time of blood collection 26



### and necropsy. So for B you have exposure again from the 27



### day of conception through postnatal day 133, C from 28



### conception to postnatal day 133 and then you have a 29



### recovery period, and th en for Cohort 2; D, E and F, 30



### exposure starts on a post

- weaning on postnatal day 21, and 31



### you have a similar paradigm. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### What is interesting here is that some of these exposure 2



### paradigms are similar to others that have been seen in the 3



### literature where we d o see the LH attenuation. 4

5



### So the FQPA safety analysis, the summary; what we have is 6



### the data available spanning life

- stages from conception to 7



### adulthood. There does not appear to be any evidence of a 8



### unique quantitative susceptibility in the developing 9



### organism. The reproductive and development effects that 10



### we are seeing are consistent with the perturbations of the 11



### HPG axis and the decreases in LH that we are proposing to 12



### use as a sentinel key event in atrazine's neuroendocrine 13



### mode of action that leads to these adverse outcomes in the 14



### rat. 15

16



### The effects that we see, none of the doses are lower than 17



### those eliciting the LH surge attenuation in the adult 18



### female rats with BMDL of 2.56 ; a nd with that, just a quick 19



### overview. 20

21



### I did not go into a great deal of detail about the 22



### experimental data because we discussed that quite a bit 23



### during the September SAP meeting, so I just wanted to give 24



### a general broad overview. With that, I will stop. 25

26



### DR. DANIEL SCHLENK : Thank you, Dr. Mendez. Any questions on 27



### safety factor evaluations? Wow. 28

29



### DR. ROBERT GILLIOM : So what was the conclusion about whether 30



### the safety factor was appropriate or not? 31

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### DR. ELIZABETH MENDEZ : Well, at this point in time, we have not 1



### finished our evaluation and exposure, and the FQPA safety 2



### f actor looks at both things. But from a hazard 3



### standpoint, it seems that we don't have any sensitivity in 4



### the young. 5

6



### DR. TRAVIS JERDE : So you repeated again the results of the 7



### Stoker paper from '99, but last year in December the EPA 8



### group had put out a group, lead author was Stanko. Have 9



### you seen that? Because it looked like the atrazine 10



### metabolites were effective in inducing prostatitis semen 11



### as low .87. Are you familiar with that work? 12

13



### DR. ELIZABETH MENDEZ : Yes. We are familiar with that. When 14



### you discussed that paper back in September, the agency had 15



### some concerns regarding the conduct of this study and how 16



### reliable it could be for selection of a point of 17



### departure. And during the September SAP meeting the panel 18



### agreed that there were some sig nificant issues with the 19



### paper at that point. 20

21



### DR. TRAVIS JERDE : Okay. And yet they published it and it came 22



### out in December. Okay. 23

24



### DR. DANIEL SCHLENK : Okay. Are there a ny other questions for 25



### Dr. Mendez? Okay. Due to the massive consumption of 26



### ca ffeinated beverages, I would suggest that we take a 27



### break right now. I have got 2:32 according to my watch, 28



### so let's try to get back at maybe 2:45. Okay? We will 29



### re

- adjourn at 2:45. 30

31

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### DR. DANIEL SCHLENK : Let's go in with our last presentation by 1



### the a gency. This will be made by Dr. Rodriguez who has 2



### not elevated his self to Dr. Mendez's status in terms of 3



### three, but is doing number two

-- still up there though

-- 4



### and he is going to be talking about some case studies to 5



### sort of put some of these applic ations in better light 6



### there. Okay? Dr. Rodriguez? 7

8



### DR. CHESTER RODRIGUEZ : Thanks very much. I just wanted to 9



### mention that this is going to be a tac

- team effort. 10



### Nelson Thurman is going to be speaking with me here. 11



### So the title of the presentation is Case Studies, and this 12



### is where we actually apply the one linear compartment 13



### model to inform water monitoring. 14

15



### So this is what the outline is. I am just going to give a 16



### brief summary of how did we get here. And then we are 17



### going to go over the propo sed water monitoring durations; 18



### that is going to be done by me. And then I am going to 19



### turn that over to Nelson who is going to be going over the 20



### water exposure estimates based on two datasets that he 21



### previously talked about. 22

23



### Then he is going to turn it back to me and I am going to 24



### be presenting how we take that information and try to come 25



### up with estimates of human plasma area under the 26



### concentration time curve for plasma triazines from his 27



### drinking water exposure estimates. And then I am just 28



### going to end with a quick summary. 29

30



### So how did we get here? Well, got here from the four

- day 31



### study in the endpoint LH attention, which does not seem to 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### be a single dose effect? Okay? It seems to be a repeated 1



### dosing effect. And this is the same slide that I showed 2



### you before with the 4

- day study with a LOAEL of 3.12 that 3



### is based on repeated daily dosing for four days. 4

5



### We tried to understand what the pharmacokinetics of 6



### atrazine that would correspond to this study would be, and 7



### for that we turned our atte ntion to the Thede 1987 study 8



### because it actually resembled the 4

- day study by Cooper et 9



### al. in that it involved repeated daily dosing for at least 10



### 4

- days. It used intact young female rats, and you also 11



### had plasma measurements that were taken daily. And the 12



### dosing frequency, I should say, was the same. So these 13



### animals were dosed daily with atrazine, once daily at 14



### different dose levels. 15

16



### So one of the things that we noted from the plasma profile 17



### from the Thede study is that we saw linear 18



### pharmacokinetic s. And actually, what I mean by that is 19



### that the internal dose metric, plasma AUC, is scaled in a 20



### linear fashion with atrazine dose at all dose levels 21



### tested. And also, we see elimination kinetics for plasma 22



### triazines. And as I said before, we were able to analyze 23



### two additional studies that actually support our findings 24



### for the elimination rate constant or the plasma half life 25



### for plasma triazines. 26

27



### So based on these findings, then, we proposed a one

28



### compartment linear model. It is very simple. It is only 29



### based on two parameters; the elimination rat constant and 30



### the volume of distribution. But we think that it is 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### informative because it takes into account information on 1



### body distribution and elimination rate. 2

3



### W e show in my other presentation that we can predict 4



### plasma levels that will correspond to the rat study using 5



### the one model linear expression. And we also want to 6



### extrapolate this one compartment model to humans using 7



### allometrically scaled volume of distribution elimination 8



### rate constant. 9

10



### No w, we are going to walk you through this. And the 11



### critical part more than anything is the estimation of the 12



### human dose rate which, like I showed before, actually 13



### depends on the water levels as well as the consumption 14



### rate. So the product of these two wil l give us an 15



### estimate of a human dose rate for a given duration. 16

17



### In terms of the range of windows of exposure, we are 18



### proposing three durations. We are proposing 4, 14 and 28 19



### days. And the rationale for these is as follows. The 4

- 20



### day duration, that duration is based on the accumulation 21



### of plasma triazines to a plateau, or pseudo steady state 22



### level, which seems to be related to optimal LH attention. 23



### It should be noted that this 4

- day duration is based on a 24



### constant dose level and frequency. 25

26



### So, b ased on this condition, the time to steady state in 27



### the rat is four days. Four days just happens to be also 28



### the length of the rat estrous cycle. Twenty

- eight days is 29



### within the, at the allometrically scaled time range, for 30



### adult humans of 60 kilograms to reach steady state based 31



### on a constant dose level and frequency. And actually, 28 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### days also happens to be the average length of the human 1



### menstrual cycle. So we have four and we have 28 days. 2

3



### We also are proposing to include 14 days just to serve as 4



### a mid

- point, given that the other two durations are on the 5



### extremes. And it also seems to be reasonable to include, 6



### given that human exposure is neither going to be at a 7



### constant dose level nor constant frequency. So, those are 8



### our proposed durations and I am going to turn this over 9



### now to Nelson. 10

11



### DR. NELSON THURMAN : Okay. I should be able to do this pretty 12



### quickly since we just got finished talking about what we 13



### did here. 14

15



### We took the two monitoring datasets that we talked about 16



### earlier, the Maumee River, the 1995 monitoring dataset, 17



### and the Missouri

- 01 from 2007. We simulated the 7

- day 18



### sampling intervals for this data, then we used the 19



### geostatistical methods to develop a variogram model that 20



### captures the covariance of monitoring data based on the 7

- 21



### day sampling intervals. 22

23



### We ran the 1,000 conditional simulations of that variogram 24



### model to estimate the daily time series from the 7

- day 25



### sampling. We bracketed it with the 5th and 95th 26



### percentiles. As Dr. Portier pointed out is that we 27



### calculated tho se percentiles and we looked each day, so 28



### they may be a wider range than you may have if you looked 29



### at the overall simulation, but that was one thing we 30



### wanted to take a look at. 31

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### Once again, you just saw this in the last present, the 1



### Missouri

- 01. We wan t to point out, we did the daily time 2



### series. We derived the 4

- day rolling averages, which is 3



### what we used for representing the 4

- day window. Those 4



### would be used for representing the 14

- and 28

- day windows 5



### in that regard. 6

7



### So there's the Missouri sites, there is the Maumee River 8



### sites and those are in your slides so you do not have to 9



### leap back through mine for a reference. And at this 10



### point, I am going to turn this back over to Chester and 11



### let him carry it the rest of the way through. 12

13



### DR. CHESTER RODR IGUEZ : Thanks. So this is how we come up with 14



### estimates of human equivalent plasma AUC from atrazine 15



### concentration in drinking water. We basically applied the 16



### expression that I showed before, based on a one

17



### compartment linear model. 18

19



### So what you have h ere is the average atrazine level for a 20



### given duration, whether it is 4, 14 or 28. We have a 21



### water consumption rate which, in this case, we are 22



### assuming two liters per day for an adult human, a body 23



### weight of 60 kilograms. And we have the elimination rat e 24



### constant in the volume of distribution, both of which have 25



### been allometrically scaled from the adult rat values. 26

27



### It should be noted that when you take this estimate of the 28



### human plasma average daily AUC and you compare that to the 29



### rat plasma, point of departure value for the endpoint LH 30



### attention, you will get an estimate of the margin of 31



### exposure that will be based on internal measures now. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So this is similar to what we are used to doing when we 1



### have a NOAEL here and we compare that to human exposure. 2



### It is actually very similar, but in this case it is going 3



### to be based on internal measure of exposure. 4

5



### So what you have on the Y axis here are the human plasma 6



### AUC estimates based on the water exposure values that 7



### Nelson showed. It is not surprising t hat the pattern is 8



### actually the same, because what you have is a linear 9



### relationship between water exposure and human plasma 10



### values. It is a one compartment linear model, so it is 11



### not surprising then that you have a similar pattern. 12

13



### Just for reference, the dash lines here represent the BMDL 14



### rat plasma AUC with a combining certain factor of either 15



### 300x or 100x. And as you can see, that the general trend 16



### here for the 2007 Missouri

- 01 dataset is that, as a 17



### duration of exposure gets shorter from 28 to 14 to 4, then 18



### you have a higher probability of exceeding this reference 19



### values based on this dataset. 20

21



### For the Maumee 1995, this is the results that we get. 22



### Basically, the water levels that Nelson actually estimated 23



### were actually very low and the human plasma values are 24



### actually correspondingly very low, so they will not exceed 25



### the rat point of departure value. There is a linear 26



### relationship

. 27

28



### So this is just a quick summary. This is a short 29



### presentation. I wanted to summarize just a few points 30



### about the a pproach that we are using. It is actually 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### based on an internal dose metric, plasma AUC, which is 1



### consistent with temporality of the endpoint, LH attention. 2

3



### One of the reasons why we selected this internal dose 4



### metric is that it accounts for magnitude of exposure as 5



### well as duration. Duration seems to be critical for the 6



### endpoint and we feel that the one compartment model is 7



### actually based on the best available science in the 8



### absence of a fully calibrated and evaluated PBPK model. 9

10



### We think that this model is simple and incorporates an 11



### average dose rate for a given duration, it incorporates 12



### body distribution information as well as plasma clearance. 13



### So we think this is the best science right now that we can 14



### use. 15

16



### And it is not surprising that the wat er levels, you know, 17



### the higher the predicted human plasma levels for a given 18



### duration, because what you have is a linear relationship, 19



### is a one compartment linear model. And with that, I am 20



### going to stop talking and try to address questions. 21

22



### DR. DANIEL SCHLENK : Thanks, Dr. Rodriguez and Mr. Nelson; 23



### appreciate it. Any questions or clarification? Yes, Dr. 24



### Hayton? 25

26



### DR. WILLIAM HAYTON : The human volume of distribution, you 27



### scaled that but did you use the rat?

-- liter per 28



### kilogram, you assumed it to be the same, right? 29

30



### DR. CHESTER RODRIGUEZ : Yes, you are correct. Yes. So we took 31



### the rat volume of distribution value on a liter per 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### kilogram body weight basis, and we scaled that to the 1



### corresponding human body weight. 2

3



### DR. WILLIAM HAYTON : Okay. And th en the elimination rate 4



### constant value was about 1/4th of the rat value in the 5



### human, something like that. That is about how it is 6



### scaled out. But the monkey

-- you know we talked about 7



### that this morning. The monkey actually went the other 8



### way. It got bigger; not smaller, but I guess you do not 9



### use that information in this scaling. 10

11



### DR. CHESTER RODRIGUEZ : But the monkey study; I mean, you just 12



### have to go by what the science gives you. And what it 13



### gives you in the monkey is that the internal dose metri c 14



### is like it scales directly with atrazine dose and the 15



### elimination is linear. 16

17



### We cannot explain why it goes the other way, but you have 18



### to go by weight of evidence. We have multiple rat 19



### studies. Rats are a species where the endpoint has been 20



### charact erized, not in monkeys. So based on that, we do 21



### the best we can. 22

23



### DR. KEVIN O'BYRNE: I mean, I like the simplicity of your one 24



### compartment model but do we have some idea as to where 25



### atrazine and its metabolites sit within that? I mean, 26



### does it sit in fa t? Does it sit in some other tissue? 27

28



### DR. CHESTER RODRIGUEZ : Yes, indeed. So let me just say that 29



### the condition of pseudo steady state also supports the one 30



### compartment model which, by definition, assumes that all 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the other compartments, all the tissues are at 1



### equilibrium. So do you follow that? 2

3



### DR. KEVIN O'BYRNE : But is that realistic? I mean, I don't 4



### know. Does it have a tensity to sit in fat, for example? 5

6



### DR. CHESTER RODRIGUEZ : Well no, actually. But the site of 7



### action is in the brain and we t hink the plasma is a good 8



### surrogate because that is how chemicals travel in the 9



### body. 10

11



### DR. KEVIN O'BYRNE : The brain is full of fat. 12

13



### DR. CHESTER RODRIGUEZ : Yes, but there is no accumulation in 14



### fat. There is no significant accumulation in fat. 15

16



### DR. KEVIN O'BYRNE : So that is known? 17

18



### DR. CHESTER RODRIGUEZ : Yes. Let me just say that there is 19



### accumulation in red blood cells, you know, apparently up 20



### to 1.5 percent of the dose actually accumulates in red 21



### blood cells, but there is no red blood cell toxicity that 22



### we can talk about. 23

24



### So, it is like we think that, at this point in time, this 25



### is what the science has actually given us. This feature 26



### of linear kinetics I think we should take advantage of 27



### because it simplifies everything. You know. What you 28



### have is a constant half

- life that is independent on those. 29

30



### DR. DANIEL GRIFFITH : If you go to slide number 9. Clearly in 31



### the 1

- day, and even in the 4

- day, you see that there is a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### breaking of the threshold line. So why wouldn‟t you be 1



### adjusting that thresho ld line as you do increasing 2



### smoothing to try and make an adjustment for what is 3



### happening with the smoothing of the data? 4

5



### DR. CHESTER RODRIGUEZ : If I understand your question 6



### correctly, you are asking about the reference values that 7



### we are showing, corr ect? 8

9



### DR. DANIEL GRIFFITH : Right. 10

11



### DR. CHESTER RODRIGUEZ : Okay. That is just for a reference 12



### value just to compare how values will become relative to 13



### the rat point of departure. 14

15



### DR. ELIZABETH MENDEZ : Let me just clarify a little bit about 16



### the BMDL a nd the 300. The BMDL comes from the point of 17



### departure from the study, so that is standard throughout. 18



### The 300 factor comes from the fact that, in the current 19



### risk

- assessment from 2003, the uncertainty factor is 300, 20



### 10x for intraspecies, 10x for intersp ecies and the 3x that 21



### was retained as an FQPA factor showed where those 22



### reference values come from. 23

24



### DR. NELSON HORSEMAN : On that point there; you said you are 25



### using a 3x FQPA, not the 10x? 26

27



### DR. ELIZABETH MENDEZ : Correct. 28

29



### DR. JAMES MCMANAMAN : So I ha ve concerns about using the rat 30



### data as a model, and I understand what you are trying to 31



### do. At least, I think I understand what you are trying to 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### do, is trying to see how well you can model both the water 1



### modeling and the animal pharmacodynamics. But ma ybe the 2



### point of departure and dose for a human is not the same as 3



### it would be for a rat, but it might be closer if you chose 4



### a monkey model. 5

6



### And so, if you are going to use this as a way of setting 7



### policy, I am a little concerned about using those value s. 8



### And I am also concerned about the fact that you really do 9



### not know very much about how the atrazine is metabolized. 10

11



### I mean, you know a lot about it in the rat but not so much 12



### in a primate model. So, all those things are going to go 13



### into helping y ou set standards, but it seems to me you are 14



### lacking critical information and, from my perspective, I 15



### would urge you to try another animal model, in addition 16



### to the rat, to see if you can get a more closely modeled 17



### what is going to be going on in the huma ns. 18

19



### And then, in regards to the water, there is a huge 20



### variation in the Maumee data and the Missouri data in 21



### terms of the Y axis. I mean, it looks like there was a 22



### four

- or five

- fold difference. Presumably, that was 23



### because of where the catchment area was, so wouldn't that 24



### also have to be factored into your model as having a 25



### standard catchment area at the headwaters or wherever? 26



### And maybe I just did not understand that. But I think 27



### that all that would have to go into whether you would 28



### break the bar i n terms of being in a critical range to 29



### potentially have some adverse outcome. 30

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### DR. NELSON THURMAN : Let me clarify. I mean, first of all, 1



### these are not drinking water monitoring. Those take a 2



### look at how well the simulations would play into this. 3



### And I think what we would be doing is we'd be looking at 4



### each individual community water system in terms of 5



### providing those estimates for each of the community water 6



### systems, so it wouldn't be breaking down a catchment size 7



### in that regard. We would actually a pply this approach to 8



### the weekly sampling for each system. 9

10



### DR. ROBERT GILLIOM : So you helped a lot explaining where the 11



### benchmarks came from for illustration and I might've just 12



### missed something in what is written, but how are you going 13



### to actually det ermine what the actual threshold from all 14



### this information is ? Because you kind of were right on 15



### the brink of just saying, based on all this stuff, this is 16



### what the threshold is and therefore here is what the water 17



### level, but you are not quite saying it. So I'm just 18



### curious where that fits in. 19

20



### DR. ELIZABETH MENDEZ : All right. Let me try and see if I can 21



### explain this a little bit more clearly. So at this point 22



### in time, we have our point of departure that is pretty 23



### solid. Now, in regards to the uncerta inty factor, what 24



### you saw today from Nelson and from Chester is a proposal 25



### in a case study. We have an enormous amount of data that 26



### we need to go through before we can make a final call on 27



### what the factor is. 28

29



### Now, in this particular instance, what you a re seeing in 30



### this slide for instance is, if your critical window of 31



### exposure is four days

-- let's just say that

-- and you 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### are sampling every seven days, then there are some 1



### instances, not very many, when you are going to be 2



### exceeding that benchmark dose divided by a factor if the 3



### factor were to be retained at 300 as it is right now. 4

5



### If once we have looked and done the full

- blown analyses on 6



### the exposure, from the hazard standpoint, it appears that 7



### we may not need to factor. But that could change if new 8



### data were to become available. But at this point in time, 9



### we are just going with the 300 that is currently, so to 10



### speak, on the books, but we will make that determination 11



### once we have fully analyzed all of the data. 12

13



### DR. CHESTER RODRIGUEZ : I just want t o go back to the monkey 14



### study question that you raised. You know, this is state 15



### if the science right now, but there is more data coming 16



### out for atrazine. My understanding is that the Syngenta 17



### is actually doing monkey study with radiolabeled atrazine. 18



### So in the future we should be able to get more 19



### information. This is all we have right now. 20

21



### DR. RICHARD GREENWOOD : On this slide that is on the screen at 22



### the moment, is my interpretation correct that where the 23



### red line, which is the area under the curve, b reaches the 24



### limit, then that is when you have exceeded the critical 25



### exposure for the effect? 26

27



### So when you've managed to get the peaks fairly well 28



### defined when you do daily sampling, then it is 29



### approximately 10 days out of that whole sampling period 30



### that it has exceeded the critical exposure, but only for 31



### 10 days. So if the critical exposure for humans is longer 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### than 10 days, you have not actually exceeded it. Is my 1



### interpretation correct? 2

3



### DR. CHESTER RODRIGUEZ : Yes. Let me try to make sense out of 4



### this. So all the lines here are actually human plasma AUC 5



### estimates, okay? This line here is a 95 percent 6



### confidence interval. That is the worse case scenario: 7



### someone said worst of the worst, you know. 8

9



### This lower line here is a 5th percentile and the black 10



### line is the actual data based on 4

- day rolling averages, 11



### 14, 28, et cetera. So the trend that we are seeing here 12



### is that the shorter the duration of concern

-- whatever 13



### that is

-- the higher the likelihood of exceeding a given 14



### reference value. Tha t is a take

- home message. 15

16



### DR. ROBERT GILLIOM: Sorry, one last thing to make sure I have 17



### it right. So because it is a simple linear model linking 18



### plasma to water, if you translate that graph into water 19



### concentrations, which is on the previous slide there , you 20



### are talking about roughly 50 micrograms per liter as the 21



### 4

- day moving average, something like that. It does not 22



### matter the exact amount. 23

24



### So where this would end up going, whether the 300x stays 25



### the same or whatever you do to policy

- wise change tha t, we 26



### could just visualize that being translated back into a 27



### particular rolling average duration level like 50 or 40 or 28



### 30 or whatever you come up with. 29

30



### DR. NELSON THURMAN : Yes, that is correct. And once again, we 31



### are just pointing out that this is not community water 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### system monitoring. The concentration that we have here 1



### are

-- except for a couple of sites where the monitoring 2



### was in a source that does not necessarily feed into

-- 3



### these concentrations are higher than what we have seen in 4



### the community water system. 5

6



### It was a scoping exercise in that regard to see what 7



### happens if we push something that we think may be at or 8



### around a duration concern. By doing this analysis, would 9



### be able to catch that if it did indeed occur? So I look 10



### at it more of a scoping exercise. 11

12



### From my point of view, looking at it a different way, is 13



### that if the duration of concern

-- the window tox exposure 14



### is four days, then I need to pay more attention to the 15



### frequency of sampling than if it is 28 days. So that is 16



### anot her way for us to look at it in that regard as well. 17

18



### DR. DANIEL SCHLENK : Any other questions, clarification? At 19



### this point, what I will state to the panel is what we 20



### would like to do is, maybe tomorrow after we have had a 21



### night to stew on the plethora o f data, that you guys would 22



### be available for a final questioning period before we 23



### actually begin the charge questions, if that is okay. 24



### All right , w ith that I guess we will conclude the agency's 25



### presentation and move on to the public comment period. 26



### Ou r first presenter is the Syngenta Group, which I believe 27



### Dr. McFarland is going to sort of lead off with an intro, 28



### I believe. 29

30



### DR. DANIEL SCHLENK : Just for the panel's knowledge, you are 31



### going to get copies of part of the presentations, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### initially, and mor e will be flowing in as the presentation 1



### goes on, so we are getting hardcopies of the 2



### presentations. Dr. McFarland, are you going to introduce 3



### everybody or

-- just make sure that they introduce 4



### themselves as they go through; that'd be great. 5

6



### DR. JANIS M CFARLAND : Yes. Thank you. Thank you, Dr. 7



### Schlenk and thank you very much to the panel. I am Janis 8



### McFarland, head of Regulatory Affairs North America for 9



### Syngenta Crop Protection. Syngenta Crop Protection is a 10



### research and development company that d iscovers and 11



### develops herbicides, fungicides and insecticides. 12

13



### We are also a world's producer and breeder of seeds. Many 14



### people don't know we are the number one Pansy flower 15



### producers around the world, and we also produce sweet corn 16



### seeds to make tomat o seeds. And we introduce about a 17



### hundred new ornamental flower varieties every year. 18

19



### We would like to thank the panel for the opportunity to be 20



### here. We greatly appreciate, and we'd like to express our 21



### sincere thanks to both the panel for their work as well as 22



### to all the scientists at EPA for the amazing amount of 23



### work that has gone into the atrazine assessment over the 24



### past year and a half, and then also prior to that. 25

26



### Syngenta has listened closely through the SAP process to 27



### the questions, the sug gestions, and also to the 28



### recommendations that the science advisory panels have 29



### provided. And we have responded by conducting many new 30



### studies and assessments that we provided to EPA and 31



### through the docket process of the Science Advisory Panel. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### The bas ic research that has been conducted on atrazine 2



### both recently and over the last two decades have led to 3



### several improvements in methodologies, databases, study 4



### designs and also risk

- assessments. 5

6



### As part of the SAP process in 2010 and 2011, Syngenta, 7



### wit h the help of several university experts as well as 8



### external scientific experts, have submitted 15 new 9



### toxicology and mode of action studies, more than two dozen 10



### reports with different statistical analysis and water 11



### monitoring, and we have also developed a t new PBPK model 12



### that we will be discussing later on today and that was 13



### spoken about earlier by EPA. 14

15



### We have developed the framework and published an 16



### assessment of how to assess epidemiology and toxicology 17



### data, and we have provided several summary repo rts on a 18



### broad range of the key aspects of toxicology and exposure. 19

20



### At the same time, we are continuing to monitor 88 21



### different community water systems with weekly monitoring 22



### data, and we have continued a second year of an extensive 23



### and comprehensive ec ological monitoring in smaller 24



### streams, first

- and second

- order streams for the 25



### e cological assessment which involves daily monitoring, and 26



### some of that you also saw earlier in the EPA presentation. 27

28



### We have several stewardship projects that are going on in 29



### both environmental, putting in buffers. One of our 30



### projects, we have planted a million and a half trees 31



### along the side banks of streams in Iowa and Illinois 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### working with a non

- profit to reduce runoff of pesticides, 1



### fertilizers and segment into water w ays and improve water 2



### quality. 3

4



### And in additional, we have developed many different 5



### environmental databases and modelling that you will hear 6



### about soon from Dr. Hendley and his team. We really look 7



### forward to the next several days and listening to the 8



### a dvice and suggestions on the risk

- assessment of atrazine. 9

10



### We are excited about the progress that has been made both 11



### by the EPA studies and our research in the various areas 12



### of mode of action, risk and exposure. And with the 13



### comprehensive database we ha ve, we look forward to any 14



### recommendations on how to statistically analyze that. 15

16



### We did start six new water systems, daily monitoring in 17



### community drinking water systems this year voluntarily, in 18



### order to aid in the modeling and statistical analyses. 19



### T he conclusion that we see when looking at this 20



### comprehensive database is, with the toxicology and 21



### exposure, there are wide margins of safety. And the 22



### current regulatory standards are protective. And we look 23



### forward to advice on how to advance its overall area of 24



### science from the panel. And with that, I will go through 25



### what we are going to cover for Syngenta in the next slide, 26



### please. 27

28



### And I am going to introduce Dr. Paul Hendley. He is our 29



### senior research science fellow with Syngenta and he will 30



### be i ntroducing his team to discuss the atrazine occurrence 31



### in drinking water and the statistical analyses. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### We decided to actually start with the water area in line 2



### with the first batch of questions, and then we will follow 3



### up with the various toxicology and modeling of the risk

4



### assessments ; s o with that

-- Paul? 5

6



### DR. PAUL HENDLEY : Okay. Thank you, Janis. Thank you, Mr. 7



### Chairman. Paul Hendley, a senior fellow at Syngenta. I 8



### would like to introduce the two gentlemen on my right; Dr. 9



### Chris Harbourt from Wa terborne Environmental, Dr. Wenlin 10



### Chen from Syngenta, and on my left, Dr. Paul Mosquin from 11



### RTI International and they will be answering questions. 12

13



### We are looking forward to this presentation and I am very 14



### pleased to say it is highly complementary to the 15



### presentation you‟ve heard from Nelson Thurman, and I think 16



### we've got some exciting things to show you. 17

18



### So the overall statement

-- and we have talked about this 19



### before

-- is that atrazine exposure is exceptionally well 20



### characterized due to the databa se. The database sample 21



### numbers provide high confidence on the exposure. In that, 22



### we mean they help us understand what the peak shapes look 23



### like. They help us understand the upper percentiles of a 24



### distribution because of the magnitude of the number of 25



### s amples in the database. They help us understand and 26



### differentiate between community water systems. 27

28



### O n the community water system side we are going to talk 29



### about how we have learned more about them and 30



### differentiated between them, in terms of their water sheds 31



### and their sources. And that is important because that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### leads on to how you use these bias factors. And the bias 1



### factors, we have seen two examples in the earlier 2



### presentation. 3

4



### We are going to show you bias factors from a large number 5



### of additio nal case to give us a better sense of the 6



### distributions, et cetera. And that is going to show how 7



### we have actually developed a synthetic chemograph for a 8



### margin of exposure assessment for TCT that Dr. 9



### Breckenridge will be finishing the presentation with l ater 10



### on this afternoon. 11

12



### Now, I am particularly excited to be able to talk to you 13



### about a modeling development, PRZM

- Hybrid which is showing 14



### great promise at being able to help supplement 7

- day 15



### monitoring data. And then we will talk a little bit about 16



### how the year

- to

- year variation is defined well for 17



### atrazine by the database and how there are opportunities. 18



### Obviously for atrazine we've got a lot of measured data, 19



### but there are opportunities to learn a lot from that 20



### database for understanding monitoring q uestions, in 21



### general. 22

23



### So let's turn to a database which is, of course, 24



### extensive. And when I say that, what I mean is, there is 25



### approximately 340,000 surface water samples in the 26



### database; that‟s not talking about the 200,000 additional 27



### ground water, s afe drinking water, samples that are in 28



### there. 140,000 of those samples approximately come from 29



### drinking water related programs, and 200,000 also from 30



### non

- drinking water. 31

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### The biggest contributor for non

- drinking water is actually 1



### NAWQA program with USG S which covers enormous range of 2



### years, grounds and is very valuable for helping to 3



### calibrate. 4

5



### We are actually going to focus most of our attention today 6



### on the three highlighted groups, and let me just sort of 7



### explain what these initials mean. The AEM P is the 8



### Ecological Monitoring Program that the Missouri

- 01 site is 9



### from. This was probably now 60 or more sites that we have 10



### investigated, 180 plus site

- years of data. 11

12



### Some of these

-- Missouri

- 01, for instance

-- they are 13



### very small. They are 11 squ are miles. You can drive 14



### through them very quickly and they are largely 15



### agricultural. And they are, of course, not drinking water 16



### related. It is about 15,000 samples, and the last two or 17



### three years have been daily, as Dr. McFarland mentioned. 18

19



### The n ext one of importance is the dataset from which the 20



### Maumee came from, which is the NCWQR, as Nelson explained, 21



### the National Center for Water Quality Research, again 22



### about 15,000. That is interesting because the AEMP

-- the 23



### eco

- program has a lot of sites w ith not as many years in 24



### between three and six or seven, whereas the NCWQR has 25



### fewer sites but far more years. So we have got a temporal 26



### and spatial match or complementation there. 27

28



### The other dataset that we are going to talk about, as Dr. 29



### McFarland men tioned, we started daily monitoring at six 30



### community water systems, so we have actually gone back and 31



### found out what the variation is at six real community 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### water systems just to build some confidence that our 1



### models are appropriate. 2

3



### However, all of that is based on what I call the 4



### fundamentals which is; the monitoring we have from the 5



### Safe Drinking Water Act which started in 1993, about 6



### 55,000 finished water samples from about 4,000 community 7



### water systems

-- quarterly samples

-- which is served as a 8



### scr een to identity community water systems that move into 9



### higher frequency programs. Initially, that was the 10



### voluntarily monitoring program, which operated between '94 11



### and 2003. That‟s got about 22,000, maybe a few more, 12



### finished water samples, and then tha t transition to the 13



### atrazine monitoring. 14

15



### Nelson gave the perfect description of that. All samples 16



### that have exceeded 1.6 ppb annual average atrazine 17



### concentration, from 1997 on, were put into that program in 18



### 2003. Any subsequent community water syste ms that have 19



### exceeded that have moved into the frequent monitoring 20



### program. And so, that‟s why the AMP program is looking at 21



### those community water systems, if you like, at the 22



### pentacle of a pyramid, which is a model I have shown you 23



### before. 24

25



### In addition to that, there is a couple more additions. 26



### One is the database of environmental vulnerability 27



### factors, which is pulling together the information we have 28



### been gathering because of the eco

- program to understand 29



### watershed behavior, and in addition, a databa se of 30



### community water system characteristics and watershed 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### information. So those are the new tools we have to play 1



### with. 2

3



### W hen we looked at the challenge before we panel, it was 4



### interesting because there's two types of question: One is 5



### retrospective an d one is prospective. The retrospective 6



### is sort of, what can we say based on the data about the 7



### specific atrazine question? 8

9



### For example, from the magnitude of the data we can say the 10



### 95th upper confidence interval of a 99.9th centile for 11



### finished water from the frequent monitoring is 41.6 ppb. 12



### We can be very precise because of the number of samples 13



### involved. 14

15



### We can also use 7

- day data to look at bias factors to 16



### understand shorter endpoints by the same approach that 17



### Nelson explained very clearly. An d we can use that to 18



### help us understand modeling. We can look at that for 14

- , 19



### 20

- day, 28

- day intervals as well. 20

21



### We also have used a database year

- to

- year variation, 22



### residue patterns and trends, but there is a prospective 23



### element of how might we underst and bias factors for other 24



### sorts of water bodies? What about future assessments 25



### presumably for molecules with less frequent monitoring, 26



### and how would you go about setting upper bounds on the 27



### year

- to

- year variation? 28

29



### Nelson made the point clearly that tho se were exciting 30



### questions if you liked the scientists, but for atrazine, 31



### the database already actually tells us. We have answered 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### a lot of these questions by sheer volume of data that are 1



### measured. 2

3



### And for example, 14

- , 28

- day in tools, while interest ing, 4



### philosophically, when you've got a great database of 7

- day 5



### data; those are the ones we need to focus on when we look 6



### at bias factor, et cetera. The existing database also 7



### gives us the modeling clues. Okay. 8

9



### Moving on to differentiating community wa ter systems ; 10



### w e've set up a new database, 200 plus community water 11



### systems. We've been looking at their source water types, 12



### their watersheds. Interestingly, there are 375 intakes 13



### associated with that. Quite a lot of community water 14



### systems have multiple intakes. I'll show you an example. 15

16



### The database is dominated by static water bodies. 224 of 17



### those intakes are static compared to 100 flowing. And 18



### most of the static intakes are on on

- channel reservoirs 19



### with the stream running through it, but some o f them are 20



### off

- channel where the water is stored, and it has to be 21



### pumped to get in. They don't have a watershed of their 22



### own that is storage units. 23

24



### Once you have characterized the watershed you can use that 25



### environmental database I mentioned in order to find the 26



### environmental parameters, soils data, cropping data, 27



### vulnerability. And equally, the community water system 28



### characteristics like the atrazine monitoring data, 29



### summarized, is all pulled into one convenient location, 30



### and that allows categorizati on. 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Now that sounds nice and fun, but why are we doing it? It 1



### is the help us understand how to use things like bias 2



### factor, because community water systems are individual and 3



### you need to target your thinking and your learning 4



### appropriately to different community water systems. 5

6



### So here, for example, is a community water system that the 7



### red line, which is a little hard to see coming down here, 8



### is a rather tiny creek. It is a two square mile 9



### watershed. But the water they store

-- and you can see 10



### five ponds here

-- there is actually another one off to 11



### the side we cannot see in this image , s o five intakes from 12



### five separate units collecting from one watershed. That 13



### is the level of complexity the database has to cope with 14



### to be useful to understand what might be going on when we 15



### are looking at the residues from this database. 16

17



### We talked about dividing up community water systems by 18



### source and watershed size last time. We have taken a 19



### simple approach; small, medium and large, and basically 20



### 50

- squre mile cut off for small. And the for the statics, 21



### a medium to large cut off of a 1000 square miles for 22



### flowing 800 square miles. And you can see that the 23



### database is dominated by small static water bodies. 143 24



### which is half of all the intakes we are looking a t here 25



### with small static water bodies with watersheds less than 26



### 50 square miles. 27

28



### When you look at the flowing you see, actually, the 29



### majority of them come from large watersheds, which when 30



### you think about the hydrology immediately makes sense. 31

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### I'm not going to dwell on this, but once you have 1



### categorized them you can start looking at the statistics 2



### and the environmental parameters associated with the 3



### different groups. That is the reason why we have been 4



### doing this categorization and spending the time developing 5



### the database. 6

7



### And example is shown here, and I'm coming back. The royal 8



### blue color here, this is a distribution of areas for the 9



### eco

- watershed. And you can see that there is overlap in 10



### terms of watershed areas with the small flowing communi ty 11



### water systems, and there are 16 of those, but there is 12



### almost no overlap with the rest of the medium and large 13



### community water systems on flowing watersheds. So the 14



### eco

- datasets are very useful for understanding the 15



### hydrology and temporal behavior but they are not relevant 16



### to the vast majority of community water systems on a scale 17



### basis. 18

19



### So moving on to bias factors and supplementing what you've 20



### learned from Nelson, we have looked at many locations and 21



### years. And using exactly the same nomenclature that the 22



### 95th centile of the error ratios

-- and the error ratios 23



### were the ratios between the true from the daily data and 24



### the simulated value from the 4 of a 7

- day simulation, and 25



### the 95th centile of those ratios makes up the bias factor. 26

27



### Syngenta use systematic sampling and I am going to spend a 28



### minute on that because it is a question that has been 29



### asked of the panel. Systematic sampling means if it is 30



### four days, you've just got four ways of doing it. You can 31



### do it on day 1, day 2, day 3, day 4 ; s eve n days just the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### same , Sunday, Monday, Tuesday
, Wednesday. And we use that 1



### rather than stratified approach which will be a random 2



### selection from period 1 and then period 2 and could come 3



### up with a range of different intervals. 4

5



### However, we have gone ba ck and looked at what the actual 6



### guys taking samples in the community water systems have 7



### done, and 66 percent of all those samples were taken spot

8



### on the 7

- day intervals. They got used to a weekly 9



### routine. 10

11



### Twenty

- four percent of those were actually tak en with one 12



### day of that; Thanksgiving falls July the 4th, or whatever. 13



### And, so 90 percent of those samples were being taken 14



### within one day of the systematic point. And what my 15



### statistical colleagues are showing me is when you've got 16



### systematic sampling i n the field, systematic simulated 17



### samplings is an appropriate way to look at it. 18

19



### The downside of using systematic sampling is if you've got 20



### four or seven measurements, error ratios, it is difficult 21



### to come up with a 95th centile. So that is why Syngent a 22



### calculated a 95th centile on the group. And when I say a 23



### group, this is not a random group. This is all the eco 24



### sites pulled together, or six community water systems with 25



### daily monitoring or all the years for an NCWQR site, so it 26



### is grouped by logic. 27

28



### M oving on; the data we see is that

-- here is 34 eco

- sites 29



### with one to two years. So that is our spatial 30



### information. There are four NCWQR sites with 15 or 16 31



### years, so that is our temporal dimension. And then St. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Louis, which is finished water from a real but not very 1



### flashy community water system. 2

3



### Just using 7

- day simulated sampling and looking at 4

- day 4



### average for, let's say Honey Creek, the bias factor will 5



### be 2.73. If you look at it as you move across, as you 6



### move

-- as Nelson pointed out

-- from shorter durations to 7



### longer durations, the bias factor drops ; t he amount by 8



### which it drops decreases. 9

10



### I would stress here, this is adding to what Nelson showed 11



### us for two examples. This is giving us a good sense from 12



### a distribution of bias factor s. And you are going to see 13



### the individual ratios in a minute. 14

15



### W e have also done the monitoring at six community water 16



### systems. Those are flowing water; they've got a wide 17



### range of areas. And the preliminary data that I'm 18



### reporting here goes up to th e end of June. It covers the 19



### peak atrazine season and, as many of you know, it's been 20



### quite a high runoff season. 21

22



### We did, again, the same 7

- day and 4

- day simulated 23



### sampling. Bias factors estimated in just the same way and 24



### we will see some of the indiv idual error ratios. The bias 25



### factor that results and you can see in the table, very 26



### similar between raw and finished water, and the bias 27



### factor is actually four within the range that we saw from 28



### the temporal dimension NCWQR sites. 29

30



### Here's an example w here, for clarity, we've spread out 15 31



### years of Honey Creek and of Maumee from the NCWQR so we 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### can see the individual variations of the seven error 1



### points when we are using the 7

- day simulated sampling to 2



### look at 4

- day rolling averages. 3

4



### Y ou can see th ere that the red lines are the group means 5



### for all those years for bias factor, the 95th centile. 6



### The open circle is those points above the 95th centile. 7



### And you can see the larger watershed, Maumee, which is 8



### 6300 square miles, has a lower bias factor, a s you might 9



### expect, than the smaller watershed. 10

11



### Here, what we've done is something slightly different and 12



### the X axis is logged area. So we are looking at the 13



### distributions across the whole range of things we've 14



### looked at, CWS error ratios, for cross ar ea. 15

16



### W hat you can see is St. Louis, which it has the whole 17



### Missouri which is 500,000 square miles and is finished 18



### water. You've got Maumee, Sandusky which is 1200 square 19



### miles, Honey, Rock Creek, and the gold ones are the six 20



### community water systems wit h daily monitoring, and the 21



### gold line is their combined bias factor, and the gray dots 22



### are the ones from the eco

- programs, from these very small 23



### non

- drinking water watersheds. 24

25



### W hat you can see here is a difference as you have an area 26



### with larger watersh ed areas, has generally lower bias 27



### factors. So what we've drawn from our look at bias 28



### factors is that, from 110, 116 sets of error ratios, 29



### systematic sampling is an appropriate way because of the 30



### way the AMP samplers did it. Raw and finished is showing 31



### s imilar ratios. Bias factors decrease as the averaging 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### period increases, and they also decreases the watershed 1



### area increases. 2

3



### There is a simple way, perhaps, we could look at this. 4



### For smaller watersheds you might want to pick a larger 5



### bias factor than for larger watersheds. And just 6



### something simple; not some regression equation but just 7



### pick a couple of categories that match perhaps the 8



### categories for dividing up community water systems. 9

10



### O nce more, there was another point, and I'll show you an 11



### example. With what we know about the atrazine database, 12



### we can put firm figures on some of these upper centiles. 13



### So, to use a bias factor and create numbers that fall into 14



### highly improbable areas wouldn't make a lot of sense. 15



### That is another factor to consider when you apply bias 16



### factor to a chemograph. 17

18



### W e've got a good sense from this wide range of years and 19



### sites about flowing waters. What about static? And I 20



### think the panel agreed last time that static is generally 21



### less flashy than flowing wate r systems. 22

23



### T he one thing we do know is the flowing water bias factors 24



### would be conservative if we were looking at some static 25



### water bodies. T his is a way of applying factors to come 26



### up with a TCT margin of exposure synthetic chemograph, a 27



### worse case ch emograph. And to do this, we took the 149 28



### community water systems between 2006 and 2010. And the 29



### reason why we chose that was because every sample was 30



### analyzed for the components of TCT. And the 4

- day rolling 31



### averages were calculated and ranked, and the 17 community 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### water systems that had the highest 4

- day rolling was 1



### selected as an indicated dataset of the uppermost tier of 2



### 4

- day rolling averages. 3

4



### W hat we did was, we took a worse case assumption, and 5



### atrazine runoff event happened between every pair of 7

- day 6



### samplings. And that will generate an unrealistic number 7



### of atrazine events and it probably distorts the peak 8



### shapes. 9

10



### W hat we chose was to use a three

- fold magnifying factor 11



### that‟s greater than the maximum of two adjacent residues. 12



### Now, what I mean by that; you can see the red points here 13



### are describing the measured values. The linearly 14



### interpolated chemograph that would describe that site for 15



### that year is shown there. 16

17



### Now we put in these three x factors between each of those 18



### pairs of poi nts and we create the new chemograph, and you 19



### can see the new daily points marked on that. And so, 20



### that‟s what has gone into the margin of exposure 21



### assessment that Dr. Breckenridge will discuss. 22

23



### Because that was meant to be a worse case assessment, w e 24



### did not apply the upper bound cap I just mentioned. But 25



### what you would normally think about doing is using what 26



### you know about statistics of an enormous database to 27



### remove highly improbable values, which would have the 28



### effect of capping those synthetic peaks at some number 29



### justified by the sampling statistics. 30

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### Moving to PRZM

- Hybrid

-- and I would like to give credit 1



### to Dr. Miller of Waterborne who's actually driven this 2



### piece of work resourcefully and relentlessly, I think is 3



### the phrase. And I think it's a particularly clever piece 4



### of work he's done. 5

6



### The phrase to remember here is PRZM

- Hybrid is site and 7



### local event specific. It uses PRZM code, which EPA and 8



### the industry are familiar with, atrazine Efate data. The 9



### only regional information used i s crop reporting data 10



### which comes in groups of 10 counties from the NASS 11



### service. 12

13



### But if you are simulating a monitoring year, you have 14



### watershed and year

- specific data for soils, for local 15



### rainfall of the year from the radar maps we see every 16



### night on the TV. 17

18



### So actually, the rainfall that was falling across the 19



### whole area of the watershed is taken into account and the 20



### cropping of the year from the NASS mapping, which maps all 21



### the fields by crops across the nation now. The output you 22



### get is a water shed scaled concentration time series. It 23



### uses available data. 24

25



### There is no model

- specific calibration for each site. 26



### This is applied in the same way to all sites using code. 27



### And it uses conservative edge

- of

- field concentrations. 28



### What I am trying t o say here is it is driven by rainfall 29



### events, which is what happens in the field. You can see 30



### here, rainfall events coming down from the upper line in 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the graph, flow figuratively below. There are uniformly 1



### sampled points. That is our linear interpolat ion. 2

3



### PRZM

- Hybrid runs; every time there's a rainfall big enough 4



### to cause a runoff, we get a PRZM

- Hybrid estimated 5



### concentration. What we do then is say, "Is that 6



### concentration higher than the linear interpolated value?" 7



### If so, you use it in a schemogr aph ; i f it isn't, like 8



### point D, you don't use it. So again, you are retaining a 9



### worse case element in this assessment. 10

11



### Just for the record, we did look. When we were trying to 12



### do this, we thought flow would be an attractive way of 13



### getting into trying to fill in the gaps. We didn't find 14



### useful correlations during the period of high atrazine 15



### runoff when we did it, but the PRZM

- Hybrid seems to be a 16



### better way from the way we are looking at things. 17

18



### T he reason why things have improved

-- the report that you 19



### have in your docket uses a growing degree day approach. 20



### The simulation was good but it wasn't great. 21

22



### There is a new algorithm that accounts for land 23



### workability; can I get a tractor on the land, and 24



### distribution across time; how many people appl y even if 25



### it's a day they could apply. And what that takes account 26



### of is the local response of a soils to rainfall. Is it 27



### too wet to go out? And the wariness of some farmers, 28



### frost concerns

-- if it's a field that isn't no till, to 29



### create seedbeds befor e you can go out and spray. And the 30



### equipment capacity; in some watersheds you simply can't 31



### spray all the fields in a day even if you'd like to. And, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### of course, the possibilities of post

- emergent treatments

- 1



### - there are quite a number of atrazine treatme nts applied 2



### post

- emergent. 3

4



### So PRZM

- Hybrid chose considerable promise for 5



### supplementing 7

- day data. It reflects reality. The peaks 6



### are only predicted when runoff events are likely to occur, 7



### unlike some of the models we've seen. And it does tend to 8



### ove r

- predict at bit at greater than 20 ppb. There is no 9



### need anymore because of its algorithm improvement from 10



### distribution matching we thought we might have to do. 11

12



### Here is a before picture. This is the growing degree day 13



### approach. This is a site. Th e black marks are the PRZM

14



### Hybrid predicting concentrations. The opened triangles 15



### are the measured values; not a bad fit but could do 16



### better. 17

18



### H ere you see what we have with the workability approach. 19



### And what I'd like to do is go back to this slide a nd just 20



### talk about the way we simulated the application across the 21



### watershed. These green bars show that we applied a chunk, 22



### about 15 percent of the chemical that was going to apply 23



### on four occasions, and we filled in in

- between with daily 24



### add

- in loads of atrazine. And that made sure there was 25



### always a little bit of fresh atrazine present if it was a 26



### runoff event. 27

28



### Using the workability approach, you find all the workable 29



### days in that period and you divide the application equally 30



### as a fraction between t hose. And so, you can see here it 31



### identified a whole bunch of workable days. The chemical 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### went down and we caught that first peak rather well. We 1



### also, because of those days, managed to catch the second 2



### peak quite well, so we are matching reality with t his 3



### technology. 4

5



### There's a couple more here. The top one is one of the 6



### less good ones. We thought we really ought to put some 7



### less good ones in as well as the better ones, but it's 8



### still pretty good. I'm still quite pleased with it. And 9



### of course, he re's another one where we're picking the 10



### peaks up in time. And as the modelers will tell you, the 11



### problem is modeling and catching this in time on a 12



### watershed scale. 13

14



### W e realize this is sort of rabbit out of a hat data coming 15



### in at the last minute beca use it is hot off the press. We 16



### want to get this out in the open literature and as a 17



### report into an EPA very soon. There are still some more 18



### tweaks on the workability approach, but the challenge is 19



### perhaps on larger watersheds because I don't think we do 20



### quite a well for that. 21

22



### There are a number of ways we could do it. We do not need 23



### to dwell on it, but I actually think that is where moving 24



### towards the regression models may be, as Dr. Nelson 25



### suggested, an attractive way of tackling larger 26



### watersheds. 27

28



### So moving on to the last key point, year

- to

- year variation 29



### is well defined, and the database is useful for general 30



### purposes. 31

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### Atrazine is a near

- ideal case to look at the year

- to

- year

1



### variation. It is applied to a high fraction of a major 2



### crop nearly every year at uniform rates. It has a great 3



### length of monitoring to understand the results and look at 4



### modeling and it covers a wide range of scenarios for all 5



### of the data in NorAqua and our programs. 6

7



### W e have a direct answer for year

- to

- year measuremen t of 8



### variation for atrazine, but the data offer an opportunity 9



### to answer questions about monitoring for other compounds. 10



### And in simple summary

-- and there is actually, the back 11



### on the handout I think you'll find a few examples showing 12



### the variation

-- bu t there is high variation of residues 13



### and error ratios across years. 14

15



### The primary driver for that is the interrelationship 16



### between rainfall inducing runoff timing and application. 17



### And so, basically, even if you don't have the extensive 18



### database we have for atrazine, even medium term 19



### prospective monitoring is probably not going to answer the 20



### question of putting bounds around year

- to

- year variations. 21



### And that‟s why, for years, for ecological modelling, we've 22



### used probabilistic approaches of many weather y ears. 23

24



### So we think that where monitoring is required, which isn't 25



### always, one approach would be exactly as Nelson suggested, 26



### using PRZM

- Hybrid calibrating for local monitoring data 27



### and then extending that to a probabilistic environment. 28



### And when I say t hat, I mean this schematic will show the 29



### PRZM

- Hybrid approach. 30

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### We run that for a site for two or three years of 1



### monitoring maybe. We check that the model is behaving 2



### itself. Then we move into a probabilistic environment. 3



### And that environment link her e, the key link, is taking 4



### the watershed parameters that we know we are fitting and 5



### then playing the year

- to

- year variation of rainfall data 6



### in a probabilistic sense on that watershed shown to work 7



### dataset. 8

9



### You could also chose to variate the crop treat ed percent, 10



### the crop rotation and perhaps the rate. But the key 11



### driver here will be the weather, and that will give you a 12



### host of PRZM weather years of 365 days of predicted 13



### environmental concentrations which can be looked at in 14



### terms of whatever you want in variation; magnitude 15



### duration, peak shape; that all comes out the PRZM daily 16



### record. So, we think that‟s quite an attractive approach. 17

18



### I n summing up, atrazine exposure is exceptionally well

19



### characterized. It is more than sufficient for analyses of 20



### exposure, magnitude and variation. 21

22



### The database numbers give us high confidence. We know the 23



### high centiles, shapes, trends. The community water system 24



### differentiation allows us to know what's out there and 25



### think what would be the appropriate way of dealing with 26



### filling in the 7

- day record for that community water 27



### system. 28

29



### The daily or near daily data validate analyses. We've 30



### looked at the wide range of bias factors so now we've got 31



### a sense for how those vary across area and across time. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### That‟s be en backed up with daily work at six true 1



### community water systems. And we've used this for 2



### synthetic chemographs for 7

- day TCT record, as Dr. 3



### Breckenridge will show you. 4

5



### The database has provided a test bed for looking at 6



### modeling and monitoring. PRZM

- Hybrid is promising. The 7



### application algorithm has moved us forward, and that 8



### approach is actually giving us a reality

- based way of 9



### coming up with simulated peaks that depend on rainfall, 10



### which is the driver. 11

12



### Y ear

- to

- year variation is characterized by the atrazine 13



### monitoring data. Probabilistic modelling is an attractive 14



### way of looking at other questions beyond atrazine. And we 15



### think it is a smart way of doing it using the new tools. 16



### So that‟s the summary. I thank you for your attention. 17

18



### DR. DANIEL SCHLENK : Thank you, Dr. Hendley. Let's go ahead 19



### and have some questions for he and his group right now for 20



### the panel if you have questions for clarification. Yes, 21



### Dr. Coupe? 22

23



### DR. RICHARD COUPE : On the PRZM model, does that generate 24



### hydrology also? S o, like, you have a point on a stream 25



### you'll get flow through that stream? 26

27



### DR. PAUL HENDLEY : Simply put, no. PRZM is an edge of field 28



### model. And particularly, in this case, we are using it as 29



### an edge

- of

- field sense. In the EPA normal methodology, 30



### it' s linked to the exams model to simulate entry into a 31



### pond system. And there are various implementations that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### can link it to a river system, but because we in PRZM

1



### Hybrid simulate the watershed in terms of area waiting, 2



### the different soil runoffs run under PRZM, the edge

- of

3



### field numbers is simulating edge

- of

- watershed, if you 4



### like. And it is quite surprising that the fit is as good 5



### as it is without having that dilution factor from a 6



### stream, but very satisfying when it does that. Does that 7



### answer the ques tion? 8

9



### DR. RICHARD COUPE : Yes. Thank you. But did you show real 10



### data versus your simulated data? 11

12



### DR. PAUL HENDLEY : Yes. The open purple triangles were the 13



### real data, daily data coming from the ecological 14



### monitoring program from those sites, and it's been run for 15



### the 34 sites that have been in the program, so probably 48 16



### to 50 site years. 17

18



### DR. RICHARD COUPE : I like the PRZM, it's really good. I read 19



### the paper on PRZM and how we triggered planting under the 20



### growing degree day, so how did we trigger pl anting with 21



### the new workability algorithm? 22

23



### DR. PAUL HENLEY: Can I pass that one to Dr. Harbourt? 24

25



### DR. CHRIS HARBOURT: There is a couple of different ways that 26



### we're doing it, and right now, the main characteristic of 27



### workability is soil moisture, so we are modeling soil 28



### moisture and figuring out when is the soil trafficable. 29



### You know, when can a tractor enter the field ; defining 30



### that as the workable days. We are using temperature 31



### windows to set the time. And then we can also, if we 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### choose to, use some of the characteristics of the GDD 1



### model and use the growing degree days as an end 2



### characteristic to kind of limit the window in time to 3



### where the corn is at a height where it's no longer 4



### feasible to apply herbicide or where it's off label. 5

6



### DR. PAUL HENDL EY : And there is actually a description of that 7



### at the back of the slide set. 8

9



### DR. KENNETH PORTIER : Dr. Hendley, this was all pretty quick 10



### and I followed most of it. I just wanted to double check. 11



### When you do the PRZM in

- fill, you're not filling everyd ay 12



### though. You're filling event days between the 7

- day 13



### sampling, is that right? So you'd have a rainfall event 14



### or something that triggers PRZM to compute an estimate 15



### that would go into between two sample points to pick a 16



### peak; is that correct? 17

18



### DR. PAUL HENDLEY : That‟s absolutely correct. And rather like 19



### those simulated peaks, it creates a new schemograph

. 20

21



### DR. KENNETH PORTIER : Well it supplements the schemograph by 22



### adding higher peaks that hopefully reflects some aspect of 23



### variability between the samp le points. Have you looked at 24



### other statistics, the maximum, in terms of duration at a 25



### concentration? One of the other things we were talking 26



### about

-- we'd been talking a lot about peak, but actually 27



### for the AUC you are more interested in duration at a l evel 28



### of concentration. And I wondered if kind of the 7

- day 29



### supplemented graphs, how they would compare to the 30



### everyday picture in terms of that kind of statistic? You 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### know, is it five days at 10 parts per million? You 1



### understand what I'm asking? 2

3



### DR. PA

UL HENDLEY : Yes. You've got it dead right. And what 4



### we've actually got

-- and the report is in draft

-- is an 5



### analysis of the eco

- sites, the NCWQR and a lot of NorAqua 6



### sites, as well, in terms of looking at the peak wits at 7



### different concentration range s for exactly that reason. 8



### My suspicion

-- and I don't have the data to back it up at 9



### the moment

-- is if in fact there is one event between 10



### seven days

-- well, I'm certain, for sites like Missour

11



### 01, which are very small, very flashy sites, that we are 12



### m aking the peaks must broader than they would be in 13



### reality. But if you went to Maumee, which is a very big 14



### watershed, the peaks are broad. So it's a watershed 15



### scaled dependent thing and that is another factor we are 16



### looking at in this analysis of the dat abase. 17

18



### DR. KENNETH PORTIER : So when you're looking at those periods, 19



### statistics, are you thinking to relate them to water site 20



### characteristics so that you'd be able to say, well, a 21



### large water slope might have a distribution of durations 22



### that look differ ent than a flat small

-- I don't know if 23



### you follow what I'm saying. 24

25



### DR. PAUL HENDLEY : Yes. However, let's not expect

-- I think 26



### we are looking for simple relationships here because there 27



### are so many things that sort of complicate

-- one of the 28



### biggest ones is the duration of rainfall events because 29



### you can have very flashy watershed, but if you get two 30



### days of solid rain it is going to look like a broad peak, 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### so there are some confounders in there that you really 1



### have to think hard about. 2

3



### DR. ROBERT G ILLIOM : Staying on the PRZM theme first. So in 4



### terms of size of watershed limits that you are thinking 5



### about from what you see so far, I mean how big are you 6



### thinking it's comfortable to go, given no adjustments for 7



### the flow system? 8

9



### DR. CHRIS HARBOURT: We looked at some base flow calculations 10



### and looking at break points in different streams to try 11



### and see is there a scale at which routing is necessary. 12



### And one of the thoughts

-- and Paul had it in one of the 13



### slides

-- about 800 square miles as being a break point; 14



### we are fairly confident that between 800 to 1000 square 15



### miles or smaller. When we're talking about time of 16



### concentration in watersheds on the order on the scale of a 17



### day, and our monitoring data is on the scale of a day, it 18



### will do fairly wel l with PRZM, a daily time

- step model. I 19



### would think much larger than that, we are going to need to 20



### do some sort of routine to be accurate in the short

- term. 21



### At some point you will catch the peaks, but we'll mimic 22



### what happened in reality, potentially not , depending on 23



### routing, and then depending on the complexity of the scale 24



### of storms. 25

26



### When you get to a scale of 800 or 1000 or 5000 or 50,000 27



### square miles, it can rain in part of the watershed and not 28



### the other. And if we are diluting that across the 29



### wa tershed average, as an example, you may not see the 30



### response that you would see in a local portion of that, 31



### and that somehow needs to be reflected in the modeling 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### scheme as you go up in scale with some of these drinking 1



### water supplies that are much, much l arger, potentially. 2

3



### DR. ROBERT GILLIOM : I just got a couple more just to follow

4



### up. In terms of the readiness of the method to be applied 5



### geographically, am I understanding right that the basic 6



### method can now be applied to any watershed in the US? Or 7



### i s it only for the drinking water intakes you have looked 8



### at? 9

10



### DR. CHRIS HARBOURT: The underlying data

-- and that‟s one of 11



### the strengths of PRZM

- Hybrid. I mean, in traditional 12



### modeling, setting up a model, parameterizing it and 13



### calibrating it is a challe nging exercise. What we have 14



### done here instead is process data nationally. We have set 15



### up datasets. The underlying SSURGO soils

, the weather, 16



### all that stuff. It's setup and ready to go in a way that 17



### can run everywhere. 18

19



### One of the challenges though wi th the PRZM

- Hybrid is that 20



### it corrects itself back to a real time series with 21



### measured points. The hybrid concept of them using it in a 22



### probabilistic fashion, the thought there is using a few 23



### years where you have sampled monitoring data

-- you know 24



### the cr op rotation history of the watershed from national 25



### land cover data, and we are able to expand that or 26



### extrapolate that to multiple years, 50 years of rainfall 27



### record and do some estimates. 28

29



### So there are opportunities, I would think, outside of 30



### areas whe re there is monitored data looking at that 31



### because it's an un

- calibrated model, you know, comparing 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### one where you have monitored data and you check it, but 1



### it's realistic and its behaving property and you could 2



### compare that side

- by

- side to one where you ha ve no 3



### monitored data ; m aybe not in a realistic sense but side

4



### by

- side within the model perhaps in comparison. 5

6



### DR. ROBERT GILLIOM : And I have one last non

- PRZM one. On the 7



### earlier part of the presentation we were talking about the 8



### bias factors for every year from the AMP data, and 9



### basically, when you do the weekly sampling frequency you 10



### have the seven values because you used the systematic 11



### sampling. I know, you made the argument for pooling those 12



### because you only have one year from each. Did you look at 13



### how those pooled values compared to assuming a reasonable 14



### frequency distribution for the individual years? I know 15



### you only have seven values and you may have to estimate a 16



### 95th, but using something like a Weibull or a lognormal

-- 17



### you know where I'm goi ng

-- is some way to get at the 18



### individual site. 19

20



### DR. PAUL MOSQUIN: No. We did not do that but we provided the 21



### plot so you can see what the underlying sampled values 22



### are. 23

24



### DR. WENLIN CHEN: I just want to add to what Paul said. We did 25



### some comparisons, not to the normal distributions, but 26



### actually compared to the sort of stratify it or random 27



### something. Actually it generate fairly small differences; 28



### not a whole lot. 29

30

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### DR. DANIEL SCHLENK : Okay. Any other questions, Dr. Hendley? 1



### Okay. Thanks, Dr. Hend ley. We'll move on to the next 2



### group. 3

4



### DR. JANIS MCFARLAND : Thank you. And we'll now bring on our 5



### toxicology and pharmacokinetic modeling team. Dr. 6



### Breckenridge will be leading that discussion. I am 7



### introducing Dr. Charles Breckenridge. He is a senio r 8



### science fellow with Syngenta Crop Protection and has been 9



### intimately involved in several years of the development of 10



### the mode of action and toxicology of atrazine as well as 11



### basic research on many of our other products. And Dr. 12



### Breckenridge will be intr oducing his other experts that 13



### will be discussing the biology and the modeling of 14



### atrazine. 15

16



### DR. CHARLES BRECKENRIDGE : Good afternoon, ladies and 17



### gentlemen. Thank you again for having us and listening to 18



### our long presentations. We greatly appreciate the 19



### opportunity to discuss our data and concepts relevant to 20



### EPA processes on atrazine. 21

22



### I would like, while I'm introducing the people that are 23



### available at the table and in the room, if we could 24



### advance that slide set to slide 39. I'm sorry I just did 25



### not have the linkage slide at the beginning of the 26



### presentation. We'll come back to this after. 27

28



### The people that we have here today are experts in the 29



### endocrine effects of atrazine are Dr. James Simpkins from 30



### the University of Texas, Dr. Tony Plant from Pit tsburgh, 31



### Bob H a nda from Arizona. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And we've complemented that team with a group that are 2



### involved with the pharmaco PBPK modeling, principally, the 3



### folks at Hamner Institute. Harvey Clewell will be marking 4



### the presentation but Mel Andersen is also in t he room and 5



### he was intimately involved in the creation of the first 6



### atrazine PBPK model while he was at the university in 7



### Colorado. And we also have Jerry Campbell who implemented 8



### the code for the PBPK model which we will illustrate 9



### today. 10

11



### F inally, as part of the PBPK modelling exercise, we 12



### coupled it to a simulation program, and Dr. Bob Silken did 13



### all of that work. And so, he's in the room as well to 14



### answer detailed technical questions about how that 15



### simulation was conducted. 16

17



### I'm going to start wi th a simple schematic that tries to 18



### capture the essence of what we are going to be discussing 19



### today. On the one hand, we want to have a brief 20



### discussion of some key factors relating to the selection 21



### of the point of departure, and for that, Dr. Simpkins an d 22



### Dr. Plant will lead that discussion. 23

24



### Largely speaking, we want to bring up the point, in fact, 25



### that we believe that pulsatile GnRH release is the more 26



### relevant endpoint for human risk

- assessment. And we 27



### acknowledge and we recognize the difficulty of dong 28



### studies in that arena, and so the LH surge stands as a 29



### convenient endpoint for point of departure consideration. 30



### Dr. Plant will have that discussion with you. 31

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### The PBPK modelling, such as we've implemented it, permits 1



### us to take into account distri buted dose versus bolus dose 2



### such as has been done in the rodent studies, age

- dependent 3



### sensitivity, animal model sensitivity, functional 4



### outcomes; those are the topics we'll cover under point of 5



### departure discussions. 6

7



### We then go backward and pick up th e information that Dr. 8



### Hendley introduced the concept of residues in water are 9



### fluctuating dynamically over the time, and coupling that 10



### with a water intake record that permits one to enter those 11



### factors into a PBPK model. 12

13



### Dr. Harvey Clewell will introduc e the work we have done to 14



### develop that model and to characterize it for you so that 15



### you can see then when we go to apply the model for margins 16



### of exposure calculations, you will have some understanding 17



### of where that‟s coming from. 18

19



### And I should just say that, in fact, we did take an 20



### initiative to commence cynomolgus study, a 21



### pharmacokinetics study. Effectively, that has begun in 22



### April and is still going on. We are not administering 23



### 14C

- atrazine. We're administering cold material and we 24



### are doing a rat her comprehensive characterization of 25



### metabolites in plasma, urine, feces, cage

- wash. We are 26



### trying to achieve the mass balance that people were 27



### envious of with the 14C , and also some postulated 28



### metabolites that were introduced into the discussion just 29



### re cently. 30

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### So our intent is to actually take the rodent model that 1



### we've developed, scale it to humans, take analogous data 2



### from the cynomolgus monkey and scale it to humans and see 3



### how we do so that there will be continuous development on 4



### this front. 5

6



### I think, with that, I will stop and I'll turn the topic 7



### over to Dr. James Simpkins. Thank you. 8

9



### DR. JAMES SIMPKINS : Okay. We need to go back to the first 10



### slide, please. I'd like to thank you for the opportunity 11



### to present

-- Tony Plant and I will be very brief. We've 12



### identified five issues that we think are key for 13



### consideration in decisions about point of departure 14



### concentrations of atrazine. Those five features are 15



### listed here. 16

17



### We will discuss four of those features. The fourth one 18



### that is developi ng animal less sensitive than the adult to 19



### atrazine. We fully agree with the EPA's position that the 20



### developing animal is not more sensitive than the adult and 21



### we'll have no more to say about that. 22

23



### We will provide a summary of the presentation that Dr. 24



### Plant did in September of 2010, relative to the role of 25



### pulsatile LH secretion across species in comparison to the 26



### LH surge, the mechanism of which does not cross species 27



### well. 28

29



### In addition to that, we will discuss every so briefly the 30



### concept of distrib uted dose, and that being more relevant 31



### to the manner in which humans are exposed to atrazine. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And we will show you pharmacological data, and then later 1



### in the presentation Dr. Clewell will show you kinetic data 2



### showing that distributed dose produces a re markably 3



### different response as well as exposure than does bolus 4



### dosing with atrazine. 5

6



### We will show you data that we have that functional 7



### endpoints do not appear to be affected by the atrazine

8



### induced modest decline in LH surge suppression, and 9



### finally s how you data that supports our opinion that the 10



### Long

- Evans animal may not be the appropriate animal to 11



### look at because of the instability of its estrous cycle. 12



### With that, I will quickly turn this over to Dr. Plant and 13



### he will talk about comparison of puls atile and surge LH 14



### secretion 15

16



### DR. TONY PLANT : Thank you, Jim. So in September I did present 17



### some data to this panel, and basically, the conclusion 18



### from that talk was
, understanding the way atrazine 19



### interacts with pulsatile LH secretion is more relevant t o 20



### understanding or translating data on the rodent to the 21



### human. 22

23



### Those slides are in your docket. I'm not going to go 24



### through those slides again. I'm just going to sort of hit 25



### the bullets for sake of time, and so I won't have time to 26



### go through any ca veats which, of course, there are to any 27



### scientific discussion. 28

29



### The first point I want to make is that, the pulsatile mode 30



### of secretion is a distinct mode of secretion versus the 31



### surge mode of secretion. So I think you are all familiar 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### with pulsatile LH secretion in the human female. This 1



### result from brief episodes of secretion of LH from the 2



### pituitary, results in a small increase in circulating LH 3



### levels, and these decay exponentially over a matter of 15, 4



### 30 minutes, 60 minutes. 5

6



### Surge secretion, on t he other hand, gives you this massive 7



### discharge of LH, which spans in the human female maybe two 8



### or three days. And these modes are regulated by different 9



### hypothalamic mechanisms. 10

11



### I f we look first at pulsatile LH secretion

-- as we've 12



### talked

-- and I think it's well recognized that this is 13



### driven by a corresponding pulsatile patent of GnRH release 14



### from the hypothalamus, and this occurs in both rats and 15



### humans. A neuro

- mechanism, which we call a hypothalamic 16



### GnRH pulse generator, which even in 2011 is still somewhat 17



### of a black box that is responsible for this pulsatile GnRH 18



### release , t hat of course is present in both rat and human 19



### hypothalamus. 20

21



### In both species there is an increase in the activity of 22



### the GnRH pulse generator as puberty is entered. How ever, 23



### I know that you're interested in lifestyle effects. And 24



### one difference I do want to point out between the rodent 25



### and the human is that, GnRH pulse generator activity in 26



### the human infant is robust, and this is again, a species 27



### difference with the rat . And that leads to gonadotropin 28



### secretion. In fact, in the infantile human male you have 29



### testicular testosterone secretion and elevated blood 30



### levels during human infancy. So that is a very different 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### endocrine environment from childhood and juvenile 1



### dev elopment in the human. 2

3



### Now from what we know, the neuromechanisms that are 4



### responsible for GnRH pulse generator appear to be similar 5



### across mammalian species. So what you learn probably in a 6



### rat, what you learn in a sheep about the GnRH pulse 7



### generator is probably translatable to the human. 8

9



### The other two points I want to make is that you all focus 10



### on ovulation in the LH surge, but pulsatile LH secretion 11



### together with that of FSH is absolutely critical for 12



### folliculogenesis. And if you don't have he alth follicle 13



### or health follicles you may have deficits in ovulation. 14



### You may have deficits in the corpus luteum. And pulsatile 15



### LH secretion also plays a major role in maintaining the 16



### corpus luteum and progesterone production in the human 17



### female. 18

19



### So now, what about the surge mode of LH secretion? So, in 20



### the rat the LH surge is short. It's entrained by the 21



### light/dark cycle. It has a critical period. It fires on 22



### the afternoon of pro

- estrous and it is sensitive to 23



### barbiturate. 24

25



### In the human and pr imate on the other hand, as I 26



### mentioned, this is a protracted event. There is no 27



### critical period and it's photoperiod and barbiturate 28



### insensitive. 29

30



### In both the human female and the rat, the LH surge is 31



### initiated by a positive feedback of estradiol, wh ich is 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### produced by the Graafian follicle. It matures and results 1



### in increasing blood levels of estradiol, which talks to 2



### the hypothalamus in the pituitary. So, again, the ovarian 3



### signal is the same. 4

5



### Now, a key side of this estradiol action in the rode nt, in 6



### the rat, is in the rostral hypothalamus, and this is a 7



### major difference. In the human female, this side of the 8



### positive feedback action occurs at the level of pituitary. 9



### Now, the positive feedback action in the rat, essentially 10



### it opens the gate t o the circadian signal in the rat, so 11



### this can now be relayed to the GnRH surge generator, which 12



### then in turn triggers the LH surge. 13

14



### And interestingly, it appears the GnRH pulse generator 15



### during this LH surge is actually decelerated or arrested, 16



### and that ‟s an important point. And again, it emphasizes 17



### the difference underlying the hypothalamic control of 18



### these two modes. 19

20



### In the human female, on the other hand, the LH surge 21



### results by an interaction of GnRH pulses, pulsatile 22



### stimulation of the pituitary and this action of estradiol 23



### we call a positive feedback action to amplify the response 24



### to the pulsatile stimulation. And in the human female, 25



### there is no evidence for a GnRH surge. On the other hand, 26



### GnRH pulse generator activity is maintained througho ut the 27



### surge in the human female. 28

29



### And so, this difference in the hypothalamic control of the 30



### LH surge in the rat it involves a GnRH surge generator and 31



### a suppression, it appears, or a block of the GnRH pulse 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### generator ; w hereas in the human female ther e is no GnRH 1



### surge generator. All you have is a GnRH pulse generator, 2



### which is maintained, and the action of estradiol is at the 3



### pituitary. 4

5



### Because of this key hypothalamic difference, I think if 6



### you want to understand the mechanism of action of atrazi ne 7



### or anything else using a rodent model, it's okay if you 8



### are translating the effects on GnRH pulse generator. But 9



### I think you're going to run into trouble if you're going 10



### to translate effects that you study in the rat on LH 11



### surges to the human female. 12

13



### DR. JAMES SIMPKINS : Despite our opinion that the pre

- ovulatory 14



### LH surge in rodents is not relevant to non

- cancer 15



### endpoints in humans, the pre

- ovulatory LH surge can and 16



### has been used to gain information about mode of 17



### administration of atrazine, duration o f administration and 18



### functional outcomes of presumed reductions in LH. 19

20



### I would like to point out to you that the mode of 21



### administration of atrazine has pharmacological 22



### consequences when looking at the LH surge. A 4

- day 23



### atrazine administration by a distr ibuted dose in Sprague

24



### Dawley rats does not reduce pre

- ovulatory LH surge if you 25



### administer the same or equivalent doses by bolus. You do 26



### get a high dose of atrazine induced reduction in LH 27



### secretion, so there is a remarkable pharmacological 28



### difference th ere. 29

30



### If one does chronic distributed dose administration in 31



### Sprague

- Dawley rats, six months exposure to atrazine, in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the neuroendocrine aging animal results in prolonged 1



### estrous, and it has been agreed that that is the mechanism 2



### by which tumors in Spragu e

- Dawley animals are induced. In 3



### Fischer 344 rats, the same distributed dose of atrazine 4



### has no effect on LH secretion. I will quickly show you 5



### datasets relative to that. 6

7



### This is a 4

- day bolus dosing with atrazine in Sprague

8



### Dawley rats looking at the pre

- ovulatory LH surge, so this 9



### is the afternoon of the day that the animal shows an LH 10



### peak. These are the doses of atrazine that were 11



### administered by bolus (gavage) once per day, and these are 12



### the resulting LH secretions. As you can see, we can dose 13



### up to 50 milligrams per kilograms, which causes an 14



### approximate 50 percent reduction in peak LH secretion with 15



### bolus dosing. In contrast to that, if we do feeding at 16



### roughly equivalent atrazine doses for the same 4

- day 17



### period in Sprague

- Dawley animals and th en monitor their 18



### pre

- ovulatory LH surge, we see no effect of atrazine 19



### treatment on the pre

- ovulatory LH surge. And again, 20



### Harvey Clewell will present pharmacokinetics data that we 21



### think is relevant to this difference. 22

23



### This is six months distributed do se atrazine in Sprague

24



### Dawley and Fischer 344 rats. In Sprague

- Dawley rats, 25



### high

- dose atrazine feeding four/six months markedly blunts 26



### the pre

- ovulatory LH surge ; whereas in Fischer 344 rats, a 27



### similar feeding paradigm is without effect. So there's 28



### strai ned difference in the response to feeding. 29

30



### In addition to that, we asked the question whether or not 31



### the modest LH suppression achieved with bolus (gavage) 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### dosing

-- this is in Sprague

- Dawley or Long

- Evans animals 1



### over broad dose ranges

-- or distributed dose feeding of 2



### atrazine over these dose ranges, which are equivalent to 3



### the higher doses given by bolus administration, had 4



### effects on outcomes that would be expected if LH is 5



### suppressed. 6

7



### So we looked at percent of animals that became pregnant 8



### when e xposed to a male number of corpora lutea that were 9



### formed, number of implantation sites, number of fetuses. 10



### And the data here are expressed with the zero at 100 11



### percent. As you can see in both Sprague

- Dawley and Long

12



### Evans animals, there is no effect on any of these outcomes 13



### parameters of gavaging or feeding any of the doses of 14



### atrazine. So we are not entirely sure there is a 15



### functional outcome of the modest LH suppression that is 16



### achieved. 17

18



### I will not present the development data because we fully 19



### agree with EPA's position. And then the final issue we 20



### addressed was the animal that‟s been proposed for the 21



### point of departure determination, and that is the young 22



### adult female Long

- Evans rat, and we have a bit of a 23



### problem with that for a couple of reasons. 24

25



### I n a CODAR study recently submitted to the EPA, greater 26



### than half of the Long

- Evans animals in the study, before 27



### they were treated with atrazine, failed to show normal 4

- 28



### to 5

- day estrous cycles. And it has been known for some 29



### time that treatments wit h high doses of atrazine by gavage 30



### results in a further disruption of estrous cycles in Long

31



### Evans animals. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So we have an animal we think that is not stable for doing 2



### these kinds of studies. These are the data

-- and I 3



### apologize for the small size. I'll point to what I think 4



### is the relevant issues. These are the Long

- Evans animals, 5



### and again, these are prior to exposure to atrazine. 38 6



### percent of the Long

- Evans animals; 306 total animals, 38 7



### percent had normal 4

- day estrous cycles. 62 percent had 8



### abnormalities of one or another type. In contrast to 9



### that, the Sprague

- Dawley animals, about 60 percent of the 10



### animals had normal estrous cycles. So we think the Long

11



### Evans rat has an unstable estrous cycle. 12

13



### So to summarize, we do believe that Pulsati le LH secretion 14



### is more relevant to do non

- cancer endpoint assessments 15



### than the LH surge, more relevant to humans. Distributed 16



### dosing is more like the exposure to which the vast 17



### majority of people are exposed to atrazine and it has not 18



### been routinely stud ies. In fact, distributed dosing is 19



### not being used in setting the point of departure. We are 20



### failing to find the functional outcome of the suppression 21



### of LH that occurs with bolus dosing of atrazine. 22



### Developing animals are indeed not more sensitive tha n 23



### adults to atrazine. And finally, Long

- Evans animals, we 24



### think, have a very unstable estrous cycle. And with that, 25



### I'll stop. 26

27



### DR. DANIEL SCHLENK : Okay. Any questions for the panel? Jan, 28



### Dr. Chambers? 29

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### DR. JANICE CHAMBERS : Dr. Simpkins, do you have a reason to 1



### suggest for the difference between the Fischers and the 2



### Sprague

- Dawley rats in their responses? 3

4



### DR. JAMES SIMPKINS : Responses to functional outcomes or 5



### estrous cycle? 6

7



### DR. JANICE CHAMBERS : You showed a graph where the Sprague

8



### Dawleys respond ed and the Fischer 344 did not. Is there 9



### any reason that you have for the difference there? 10

11



### DR. JAMES SIMPKINS : Well, what we know, this study is 12



### essentially a combination of chronic exposure to atrazine 13



### while animals are aging. And so, we know for exa mple, in 14



### Sprague

- Dawleys that by the time of this LH observation, 15



### many of those animals have gone from normal estrous cycles 16



### to persistent estrous. That is, they are not able to 17



### mount a pre

- ovulatory type LH surge probably because the 18



### neuromechanism is no longer working sufficiently. 19

20



### We also know that in the Fischer 344 rats, those animals 21



### can age to as long as two years, and in our hands, have 22



### absolutely normally regulation of LH secretion. The 23



### problem they experienced during their aging is they cannot 24



### suppress prolactin secretion so they suffer from a 25



### hyperprolactinemia, that causes retention of corpus 26



### luteum, and they go into a persistent diestrus state. 27

28



### But their regulation of LH secretion is preserved even 29



### into very late life, and we think that‟s the explanation 30



### for why atrazine is not adversely affecting LH secretion 31



### in the Fischer. They just have a more robust regulatory 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### system for LH secretion, whereas the Sprague

- Dawley animal 1



### is actually breaking down over their regulation of LH 2



### secretion, i s aging, and then you superimpose the atrazine 3



### insult on that, and that happens earlier in their life and 4



### so we detect it by the six months of feeding. 5

6



### DR. JAMES MCMANAMAN : So let me get this straight. You believe 7



### that the LH surge in the rat is totally due to a 8



### hypothalamic effect, and the human, it would be due to a 9



### pituitary effect, and that atrazine, you believe, acts 10



### solely at the level of the hypothalamus, therefore would 11



### not effect the LH surge in the human because that is 12



### through the pituitary; i s that correct? 13

14



### DR. TONY PLANT : Yeah. In the rat, clearly it's a hypothalamic 15



### action of estradiol which, together with the circadian 16



### cycle, triggers the GnRH surge. 17

18



### In the human, you have a hypothalamic component. You have 19



### to have GnRH pulsatility. Without that, you will have 20



### amenorary cyclicity. So it's a combination of a pulsatile 21



### hypothalamic input and an effect of estrogen at the level 22



### of the pituitary. 23

24



### Now, we are told though

-- or I'm told

-- I mean, I'm not 25



### an expert on the rat estrous cycl e, but that the effect of 26



### atrazine is hypothalamic, is a brain effect. I think that 27



### was quoted recently. And what effects does atrazine or 28



### any of these compounds have on the GnRH pulse generator is 29



### much less clear, but there is no reason why it shouldn't 30



### have an action. That‟s what should be investigated for 31



### relevance to the human. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. JAMES SIMPKINS : If I can add, Dr. Handa , do you want to 2



### respond to that question? 3

4



### DR. ROBERT HANDA : We've done studies looking at the pulse 5



### generator in the rat and at razine has an effect at very 6



### high doses in lengthening the pulse period, but that 7



### doesn't occur until 200 milligrams per kilograms in our 8



### hands. We have also looked at pituitary effects of 9



### atrazine and we've found no effects of atrazine on 10



### pituitary sensi tivity to GnRH even at very high levels. 11

12



### DR. JAMES MCMANAMAN : I just want to clarify why it's the 13



### pulsatility versus the surge component that you thought 14



### was the most relevant, and I think that you've answered 15



### the question but I just want to double check on that. 16

17



### DR. TONY PLANT : Well, all the evidence for the human female 18



### suggests there is not a GnRH surge. Now that‟s indirect. 19



### But if you don't have a GnRH surge then you can't 20



### translate the findings in the rodent where the LH surge is 21



### driven by a GnRH surge to the human female. 22

23



### DR. KEVIN O'BYRNE : I'm delighted to see the distribution 24



### dosing. It took a long time for that to come. But why 25



### wasn't it put in the water, the atrazine? 26

27



### DR. CHARLES BRECKENRIDGE : The problem of achieving a high dose 28



### in wat er is the water solubility limit of the compound, so 29



### it can put approximately 20 part per million. And so, you 30



### cannot actually get to an effective dose at a solubility 31



### limit. So that is essentially the reason that we needed 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### to go higher. And by incorpor ating it in the feed, you 1



### can actually get a distributed dose and have the animal 2



### consume considerably more. 3

4



### DR. KEVIN O'BYRNE : This separates toxicology from physiology. 5

6



### DR. SUSAN AKANA : Could you remind me with the distributed drug 7



### dosing whether all the animals voluntarily ate the diet 8



### with the atrazine? 9

10



### DR. CHARLES BRECKENRIDGE : We've done many studies with feeding 11



### of atrazine to animals, and there is an initial body 12



### weight suppressive effect of the compound and that‟s 13



### coupled with a food intake r eduction. There is a 14



### reasonably rapid recovery of that food intake reduction 15



### that happens, and it stays stable throughout. There is a 16



### possibility that those effects on body weight and food 17



### intake are actually mediated through some direct action in 18



### the h ypothalamus, but it seems like the principle interest 19



### was on the endocrine response. We don't understand that 20



### transient change, but we note it does occur regularly, and 21



### that happens even if you give it in bolus dose 22



### administration. 23

24



### DR. KATHERINE ROBY : A nd what will be known about a change or 25



### differential absorption given in feed versus either water 26



### or a bolus? 27

28



### DR. CHARLES BRECKENRIDGE : We're exploring that question in our 29



### monkey study, effectively. We're interested not, 30



### obviously, in feed, so we're tr ying to move away from 31



### that. Typically in the bolus dose scenario, people use 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### five percent or one percent CMC suspension, and 1



### effectively, one would anticipate at high concentrations 2



### that could modify absorptions. We have evidence that that 3



### actually is o ccurring. 4

5



### In a second phase of our primate study, we took atrazine 6



### and put it in five percent ethanol water and we were able 7



### to achieve a hundred part per million under those 8



### circumstances and be able to compare the pharmacokinetics 9



### of aqueous mediated f ormulation as apposed to a CMC. It's 10



### our intent to try to do that same study in the monkey with 11



### only 20 part per million in water. 12

13



### You start to get to limits of detection issues in terms of 14



### picking up metabolites in plasma, but we think we can 15



### actually achieve that by virtue of the volume of water we 16



### might administer to those animals, and the highest 17



### achievable water concentration. And by that way, we can 18



### hope to get around the question of absorption and 19



### presumably what we observe when atrazine is in wa ter, is 20



### that kinetics of absorption are rapid. And we suspect 21



### that we eliminate the potential for gut metabolism, which 22



### can further confound the question, which I think I had 23



### come up at some of the previous SAPs. So that‟s our 24



### strategy to try to understa nd the impact of the vehicle on 25



### kinetics of absorption. 26

27



### DR. JAMES MCMANAMAN : So just let me clarify because I think 28



### I'm hearing maybe different things. Syngenta's position 29



### is that atrazine does have an effect on the hypothalamus 30



### or does not have an effe ct on the hypothalamus? 31

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### DR. CHARLES BRECKENRIDGE : You know, you're asking a very 1



### difficult question as to exactly where the molecular 2



### target is, and we don't know where the molecular target 3



### is. We believe it is in the hypothalamus for probably the 4



### pulse generator and the LH surge, but we have been 5



### pursuing that over the years and we still do not have that 6



### knowledge. 7

8



### DR. JAMES MCMANAMAN : A follow

- up on that then: So the weight 9



### loss effects, you wouldn't attribute that to an LH effect, 10



### would you? 11

12



### DR. C HARLES BRECKENRIDGE : No, I wouldn't, but I wouldn't 13



### discount the possibility that it is somehow affecting 14



### food

- intake centers in the brain. I mean, that‟s always a 15



### conceivable outcome. It could also reflect just general 16



### toxicity. 17

18



### DR. JAMES MCMANAMAN : So, if it is affecting the food intake, 19



### the food regulatory centers and the hypothalamus, then 20



### perhaps by focusing solely on the LH, we might be missing 21



### an important effect of atrazine. 22

23



### DR. CHARLES BRECKENRIDGE : I imagine the simple answer to that 24



### is the dose is whereby the food intake effect disappear or 25



### are substantially higher than the doses, were the LH 26



### effects are observed. So to that extent, the agency's 27



### choice of the LH surge is protected. 28

29



### DR. JAMES MCMANAMAN : So in regards to the neonates where as the 30



### LH may not be anymore sensitive or less sensitive

-- any 31



### difference in sensitivity than the adults

-- that might 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### not be true for food intake. For instance, it's known 1



### that the food regulatory mechanisms develop , at least in 2



### rodents, earlier in life , and it develops through the 3



### hypothalamus, so that might be a key thing to be concerned 4



### about. 5

6



### DR. CHARLES BRECKENRIDGE : We have probably extensive data on 7



### reproductive measurements of food intake in neonatal pups. 8



### And again, I think then the point of reference becomes 9



### evidence of pulse generation change in those developing 10



### animals. And most people believe that vaginal opening and 11



### preputial separation are coupled to the operation of a 12



### pulse generator. We see effects on that pulse generator 13



### in the rang e of 10 to 15 milligrams per kilograms. Food 14



### intake effects, I believe, tend to occur at much higher 15



### doses. So I think that could be looked at carefully, just 16



### to explore that question. Thank you. 17

18



### DR. TONY PLANT : Just to comment on the infant and the m aturity 19



### of the hypothalamus; I mean, the infant primate, the GnRH 20



### pulse generator is robust, it's functioning. And this is 21



### a fundamental difference in the ontogeny of the 22



### reproductive axis between a rodent and a primate. 23

24



### DR. KEVIN O'BYRNE : Could you pos sibly comment on the 25



### distribution of atrazine in the various tissues in rodents 26



### and primates? 27

28



### DR. CHARLES BRECKENRIDGE : Thanks for that question. I think 29



### it's going to be answered by the next speaker, and so, 30



### perhaps that would be a nice segway into our next speaker. 31

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### DR. DANIEL SCHLENK : Thanks. We'll move ahead with Dr. 1



### Clewell, is it? 2

3



### DR. HARVEY CLEWELL : Okay. Thank you. In the September 4



### meeting, David Kim who was with Syngenta at the time 5



### presented a number of pharmacokinetics studies that had 6



### been performed by Syngenta and promised that at the next 7



### meeting he would present a PBPK model based on those data. 8



### However, David is now in Africa. He lives and works in 9



### Africa doing completely different work, and so I'll be 10



### presenting in his place. 11

12



### It is actually an effort that has been carried out between 13



### several of us at the Hamner, Mel Andersen, Jerry Campbell 14



### and myself along with David and Charles and others at 15



### Syngenta to try to design studies that are informative for 16



### a model and then develop t he model on that basis. 17

18



### So, I'm going to briefly talk about the questions relating 19



### to the nature of a pharmacokinetic model that could be 20



### used to help inform the relationship between animal and 21



### human dosimetry for atrazine in support of risk 22



### characteriza tions, and then I'll actually go through the 23



### steps in the development of the refined model. 24

25



### It's called a refined model because an initial atrazine 26



### model was developed in Colorado State by Tammy McMullin 27



### and Mel Andersen and others, and we began with t hat as our 28



### starting point. It was a rat model. We have expanded it 29



### to be also a model for monkey and human, and I'll just 30



### take you through those steps. And then at the end, I'll 31



### very briefly mention how this model can be used and has 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### been used by others to evaluate margins of internal 1



### exposure. 2

3



### So first of all, comparing what seems to be called EPA's 4



### simplified model; the total radioactivity

- based estimates 5



### of pharmacokinetics with a PBPK approach. I've spent many 6



### years trying to justify why I go thro ugh the trouble of 7



### developing PBPK models when you could use a compartmental 8



### model instead, so I'll try to kind of take you along on 9



### that. 10

11



### This slide shows the known metabolites of atrazine. I've 12



### put red boxes around atrazine and the metabolites that ar e 13



### considered to be active in the sense they still have the 14



### chlorine in the key position so that they are part of the 15



### common mechanism group, if you will. 16

17



### Those are the desethyl, desisopropyl, initial metabolites 18



### which are subsequently metabolised to DACT . All the other 19



### unboxed metabolites are subsequent to glutathione 20



### conjugation which replaces the chlorine with the 21



### glutathione conjugate and are considered, generally, 22



### considered inactive. 23

24



### The box in the top on the left, which is called other 25



### oxidative metabolites?

-- is because Ernie Hodgson's lab 26



### recently looked at atrazine metabolism in microsomes and 27



### identified a couple of oxidative metabolites of atrazine 28



### apart from the three that had been known historically. 29



### But those have not yet been identified in vivo. So we do 30



### not actually know if, quantitatively, they are produced in 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### vivo in amounts that are significant, and I'll show you 1



### later why I don't think so. 2

3



### F inally, I want to emphasize this dotted arrow over here 4



### from DACT to protein adducts. One of the things that we 5



### were reminded of by Mel Andersen, who remembers well 6



### because he was involved at the time, is that Colorado 7



### State looked carefully at the impact of protein adducts of 8



### DACT on the concentration of radioactivity in the blood 9



### and plasmas , in the red cell in plasmas, so I'll show you 10



### that data. 11

12



### This shows studies that were done in actually Tammy 13



### Mullin's first paper, looking at red cell binding, and 14



### they determined that

-- and I think it's been mentioned 15



### earlier that as much as two perc ent of the oral dose binds 16



### to the hemoglobin in the red cells of the rat. The red 17



### cells in the rat are different from those of other species 18



### in having a cysteine that is very open to adduction. 19

20



### DACT does react with that cysteine

- 125 and this is, as I 21



### s aid, an example, as dimethyl arsenic also binds in this 22



### way to rat red cells. And so, that is a consideration for 23



### the disposition. But as long as you are measuring plasma 24



### samples, then it doesn't really matter in terms of the 25



### dose metric measurements. B ut a similar effect occurs in 26



### the plasma. DACT was also shown by Colorado State to 27



### react with cysteine and albumin and in similar fashion to 28



### that with hemoglobin. And they actually showed nice proof 29



### of it. It turns out that the half

- life of the adduct i s 30



### consistent with the turnover of albumin in rat plasma, so 31



### that‟s undoubtedly what you're actually seeing. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Tammy McMullin did a nice simulation when she took 2



### Timchalk's data on the total 14C in the plasma and then 3



### ran the model to show what the total ch lorotriazine 4



### concentrations would be. And you can see that the tail is 5



### due to the bound material that DACT bound to the plasma 6



### element. 7

8



### Y ou can see that is responsible for the terminal half

9



### life, which is on the order of 60 hours, as I recall. And 10



### tha t terminal half

- life does not occur for the free 11



### compounds. DACT has got the longest half

- life that‟s on 12



### the order of six or eight hours, as I recall. 13

14



### So that‟s kind of important as it turns out for 15



### understanding what would be a good dose metric. And so, 16



### looking at the 14C atrazine

- equivalence in plasma, it's 17



### been pointed out that they account for total mass of 18



### atrazine derived metabolites, atrazine derived 19



### metabolites. So that‟s a blessing and a curse. 20

21



### The problem is that 14 

### C includes compounds th at are active 22



### and compounds that are inactive. It's not necessarily 23



### conservative to lump everything in to a measurement. In 24



### fact, in order for it to be an accurate basis for cross

25



### species extrapolation, it would have to be true that there 26



### was a similar f raction of relationship of active to 27



### inactive metabolites in both species. And so, it could be 28



### conservative or anti

- conservative depending on whether the 29



### glutathione pathway versus the oxidative pathways had 30



### different relationships, which they very often do. 31

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### The terminal half

- life has the disadvantage that it is 1



### driven actually by the covalent binding in the plasma, 2



### which means that it's really reflecting albumin turnover 3



### in the plasma, and so it is not a good metric for target 4



### tissue exposure to active compounds. 5

6



### Another disadvantage is that there is no human 14C data. 7



### I like to say that risk

- assessment is a ratio business. 8



### If you want to relate human toxicity to animal studies, 9



### you got to have information in both. So if you don't have 10



### human 14C da ta which, of course, is hard to collect, then 11



### you have to use default allometric scaling. And I myself 12



### am not against default allometric scaling. This is what I 13



### would've done in this situation. 14

15



### I like to use the term chemical

- specific adjustment factor 16



### which is what IPCS likes to call these kinds of cross

17



### species relationship factors. And so the animal to human 18



### kinetic relationship using default allometric scaling, 19



### which is body weight to the three

- quarters, is on the 20



### order of three, and that‟s what EP A used. 21

22



### And they say in their report that, basically, for the same 23



### applied dose, then you would have roughly a three

- fold 24



### higher steady state plasma level predicted in a human 25



### compared to the rat. 26

27



### We developed the PBPK model basically to get away fro m the 28



### problem of a dose measure where you don't know to what 29



### extent it's based on active materials. And so, what we 30



### worried about doing was accounting for the majority or the 31



### active species. And one of the things we tried to do is 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### determine are the four that have traditionally been listed 1



### as the active species, do they seem to actually account 2



### for the metabolism of atrazine. 3

4



### It's difficult to assure that kind of mass balance because 5



### of the complexity of the glutathione conjugates and down

6



### stream metabol ites were captured at 16 conjugates. I mean 7



### it is very messy, so it's hard to look for all those 8



### things. 9

10



### But actually, Syngenta is very aggressive in trying to do 11



### that study in the monkey and Mel and I are both really 12



### pleased that

-- you know, we basic ally have asked for an 13



### awful lot here and they are going to try to do a very, 14



### very thorough study to identify metabolites in the monkey. 15

16



### There is data in both rat and human. And one of the 17



### things we in risk

- assessment have to deal with more and 18



### more is that the chemicals that were studied to death in 19



### the human are being taken care of and we are stuck now 20



### with the chemicals where there is not a lot of human data. 21



### And so you cannot calibrate a human model based on a 22



### number of in vivo studies; you actually have to use more 23



### indirect ways of doing it. 24

25



### But there is actually a human study where the half

- life 26



### for DACT, which is almost all of the exposure was 27



### measured, and we have used the model that I'll describe to 28



### you to look at the cross

- species equivalence . What we 29



### found is that it indicates similar internal exposures at 30



### roughly the same ingested dose rate. So the CSAF is about 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### 1.5. In other words, the human has about 50 percent 1



### greater plasma level at the same dose. 2

3



### So what we included in the model we re, of course, atrazine 4



### and its oxidative chlorometabolites, so that‟s desethyl, 5



### desisopropyl and DACT. Then we are now trying to improve 6



### our description of the conjugation metabolites, the 7



### glutathione conjugates and downstream metabolites in order 8



### to be able to use the model to evaluate mass balance. And 9



### we are adding description of the adduction to plasma 10



### proteins so that we can actually do some simulations to 11



### compare 14C

- based dosimetry with active compound

- based 12



### dosimetry under different exposure situ ations. 13

14



### So now I'm going to go through a description of the model 15



### that we've developed. We had a hepatic metabolism from in 16



### vitro studies in the rat, human, and now the monkey. We 17



### had Jeff Fisher when he was at Georgia determine the 18



### partition coefficie nts in vitro. There is not a very high 19



### distribution of atrazine of its metabolites into tissues. 20



### It's a fairly even distribution around the body. 21

22



### We have beautiful datasets on the kinetic differences of 23



### bolus dose and distributed dietary dosing in the rat. 24



### There are also studies in the monkey that are going to 25



### look at different vehicles, comparing water and ethanol 26



### and CMC slurry, as Charles mentioned. The monkey data, in 27



### particular, is going to, as I said, have very extensive 28



### characterization of the various metabolites. 29

30



### This shows the in vitro data that was a study that David 31



### Kim designed. You can see atrazine, DEA, DIA and then 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DACT. The red lines are the rat. The blue curves are the 1



### human. There is a difference in the relative split 2



### between the two intermediate metabolites across the 3



### species. Two different concentrations were used. We used 4



### this data to estimate the metabolic parameters, a nice 5



### spacing of the data across the four

- hour period of the 6



### study. 7

8



### So the description that we used, w e actually had to model 9



### that in vitro data, so we modelled the in vitro system, 10



### including competitive metabolic inhibition, which had been 11



### described earlier at Colorado State. And Jerry Campbell 12



### did this work and he actually had to account for the loss 13



### in viability of the rat hepatocytes during the assay 14



### because four hours is really kind of long to have a 15



### hepatocyte functioning. 16

17



### So, by adjusting for the viability of the hepatocytes, we 18



### were able to actually obtain good data even on the DACT, 19



### which take s a while to appear. And so, then we used 20



### affinity constants from Tammy McMullin's study which were 21



### at higher concentrations and so were better for 22



### determining a KM. And then we re

- estimated the Vmax's for 23



### the conversion of atrazine and the metabolites. 24

25



### This shows the model simulation of the rat hepatocyte 26



### data. You can see it correctly describes the loss of 27



### atrazine, the production of the DIA and DEA and their 28



### subsequent conversion into DACT. 29

30



### I really want to emphasize the fact that

-- so the mode l 31



### has no compartment per other metabolites. So this 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### demonstrates that there is a mass balance between the loss 1



### of atrazine and the production of DIA, DEA and DACT in 2



### this in vitro system. That‟s really all that was going 3



### on. There's not a mystery metabo lite that everybody has 4



### missed. 5

6



### This shows the same analysis with the human data and, 7



### again, you can see that we were able to coherently 8



### describe the conversion of atrazine to DIA, DEA and their 9



### subsequent conversion to DACT quantitatively with the 10



### mod el. 11

12



### So then, that gave us our in vitro metabolism. We had our 13



### partition coefficient physiological parameters, and then 14



### this is the study that was performed for actually 15



### evaluating the model's prediction of in vivo kinetics. 16



### There was three different di etary concentrations, three 17



### different gavage doses and a very, very high rate of 18



### sampling that actually required parallel groups because 19



### you cannot actually sample animals that frequently, so two 20



### groups were used to go back and forth and get a very dense 21



### s pacing for the data. 22

23



### Four

- day study; you can see here a pulse each day of 24



### atrazine for the gavage in red, and it has broaden peaks 25



### for DACT because there is longer half

- life. You can see 26



### for the distributed dietary dosing is the blue lines, and 27



### it's a m uch flatter profile. You can see here the DACT 28



### comes up to about half of the peak value. 29

30



### You can't see the Y axis values, but I can tell you that 31



### DACT accounts for almost all of the exposure. It is very 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### rapid metabolism of atrazine and the intermedia te 1



### metabolite is 2 DACTs and then DACT has a longer half

2



### life. 3

4



### You saw this LH surge data before. What I wanted to point 5



### out was that it is interesting to see that you have an 6



### apparently greater potency for gavage than for diet. And 7



### if you look at the kinetic time courses for those two 8



### administrations, you can see very high peaks exposures, 9



### particularly looking at the DACT which, as I say, is most 10



### of the exposure. And Colorado State shows the DACT is 11



### roughly equal potent with atrazine for the LH effec ts. 12

13



### So the peak values with the gavage study are roughly a 14



### factor of two greater than for the dietary study, even 15



### though the area under the curves
, are similar. So this 16



### suggests a nonlinear relationship between the kinetic of 17



### target tissue dosimetry and the nature of the response; 18



### actually suggest perhaps time above a critical 19



### concentration might be a good metric. But one of the 20



### things we like to do with the kinetic data is to try to 21



### get a good idea of the nature of the dynamic relationship. 22

23



### So, just to review, we took the PBPK model of Tammy 24



### McMullin and added physiological parameters for the monkey 25



### and the human from the literature, added additional target 26



### tissue compartments, used the metabolic rates from our in 27



### vitro modelling and partition coeffic ients from Jeff 28



### Fisher, and then we simplified the description of oral 29



### uptake because we were modelling lower doses of 30



### administration where the kinetics of oral uptake was not 31



### as complicated and it makes for a simpler description. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### This is the model. It looks complicated because you have 2



### four different compounds you are tracking simultaneously, 3



### which are interconverted by metabolism in the liver. The 4



### oral uptake was modeled as a slurry portion and a soluble 5



### portion. Below about 20 milligrams per kilogr am, I think 6



### it is, that it all ends up being just in the soluble dose. 7



### So for human exposures, for example, it's all in the 8



### soluble compartment. And then there's also glutathione 9



### conjugation in the liver. 10

11



### This shows the predictions of the in vivo data. In this 12



### case, this is the single dose data. We used this data to 13



### estimate the oral uptake parameters. So we had the 14



### metabolism petitioning disposition, was already determined 15



### from in vitro studies. The only thing we could not do in 16



### vitro was oral upta ke. So we estimated the rate of oral 17



### uptake for atrazine and its DIA and DEA. And we were able 18



### to get a nice reproduction with the model of the time 19



### course for the four materials. So this is in vivo then 20



### for a single gavage. 21

22



### Now, what we did then was to use that model for the 4

- day 23



### administration data, a much richer dataset. And you can 24



### see DACT, as I said, is the major contributor, and the 25



### model does a beautiful job of reproducing the time course 26



### for DACT in the rats over the 4

- day exposure period. 27

28



### What I was really impressed by was, however, it was the 29



### dietary administration. When they did the study they 30



### actually measured the food ingestion during the dark and 31



### light cycle so that we could input that into the model 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### which produces the diurnal cycles of DACT concentration 1



### which perfectly mimics the data. As you can see, that 2



### wave effect is because each day the animals are eating 3



### more at night than they are during the day. 4

5



### So this is extrapolation; it's not root to root, I guess. 6



### It's administratio n form to administration form from 7



### gavage to a dietary. No parameters in the model were 8



### changed in order to predict the dietary as opposed to the 9



### gavage. We are not done with the model. In particular, 10



### we're really focusing on the monkey now, but as I ha d 11



### mentioned, we are going to incorporate plasma protein 12



### binding. We are doing more work on the formation of 13



### glutathione conjugate in vitro and verifying partition 14



### coefficients that were done in vitro with in vivo tissue 15



### disposition data just to confirm th em. 16

17



### T hen with the monkey study, we will be looking 18



### particularly at the glutathione conjugates and 19



### mercapturates, and the developing data by which we can 20



### estimate with the mild urinary and fecal elimination rates 21



### and try to calculate with the model an in vivo metabolite 22



### mass balance. 23

24



### In particular, we will be

-- we

-- I won't be doing any of 25



### the work on this study but I'll be modeling it later. We 26



### will be looking for the newly postulated oxidative 27



### metabolites from Ernie Hodgson's lab to see whether th ey 28



### are produced in any quantity in vivo. 29



### And then, the major work that we have ahead of us once we 30



### finish with this monkey elaboration is to do a model

31



### sensitivity uncertainty analysis to characterize the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### propagation of the uncertainty from the model inpu ts to 1



### the prediction of dose metrics for the animal and the 2



### human. 3

4



### Finally, what we're going to do with this model

-- so we 5



### have a model for the rat, monkey and human. The monkey 6



### really is to help us define the human model with a more 7



### appropriate surrog ate than the rat, since you cannot 8



### collect as much data in the human as you can in the monkey 9



### or rat. 10

11



### We have already had an initial evaluation of this model by 12



### Battelle, Pacific Northwest Laboratories. We asked them 13



### to follow the new World Health Organ ization's guidance on 14



### evaluation of PBPK models for risk assessment. They 15



### actually are the contractor for EPA NCEA for evaluation of 16



### PBPK models so they know what they're doing. They 17



### concluded that the model was credible, reliable and 18



### applicable for this . That it is "fit for purpose" is 19



### another way of putting it. Everybody has their favorite 20



### terms for just saying it works. 21

22



### We are still improving the model, but I think that right 23



### now I am comfortable that the model accounts for the 24



### active forms of atra zine and its metabolites and that that 25



### is a better way to do the cross

- species dosimetry. 26



### What you'll hear about next is the model is used to 27



### predict human plasmas total chlorotriazines, the four 28



### compounds, resulting from drinking water exposures in 29



### orde r to get margin of exposure for effects in the rat 30



### studies. 31

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### DR. DANIEL SCHLENK : Okay. Thank you, Dr. Clewell. Let's go 1



### ahead and address questions of the model right now because 2



### I think we're going to be getting into more of the risk

3



### assessment compone nt after this. So let's go ahead and do 4



### that; yeah , s o, Dr. Greenwood? 5

6



### DR. RICHARD GREENWOOD : If you look at slide 30 where you were 7



### looking at the area under the curve for the two, I really 8



### do not believe that the area under the gavage curve is the 9



### sam e as the area under the distributed dosing curve. Have 10



### you actually measured them or is it just

-- 11

12



### DR. HARVEY CLEWELL : Oh, yes; we characterized those. I don't 13



### actually remember. Frankly, I don't pay much attention to 14



### the non

- model

- based comparisons. 15

16



### DR. RICHARD GREENWOOD : I would say it is at least double. 17



### You have a look at that. I have looked at DIA, and if you 18



### take one of those peaks and then you lay that flat, two of 19



### those peaks, you're at least going to cover the blue 20



### lines. So if you ar e thinking in terms of the area under 21



### the curve, I suggest that that is something that really 22



### ought to be checked. Before you make a statement like 23



### that you really ought to measure them

. I don't believe, 24



### just looking at those, that that‟s going to be the case, 25



### that they're similar. 26

27



### DR. HARVEY CLEWELL : Okay. 28

29



### DR. RICHARD GREENWOOD : So I think that really is something 30



### that needs checking. The other thing that hit me, because 31



### I was really impressed with the fit, on slide 35 I was 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### really impressed with t he fits there for the dietary 1



### exposure. I think those are excellent, but at the end you 2



### are actually under

- predicting quite markedly, not just for 3



### DACT; I could understand that because I think well maybe 4



### it is binding, as you said. I think that depends o n 5



### turnover of albumin. But what about DIA and DEA, because 6



### they are similarly over

- predicted at longer times by the 7



### model ? The fit is wonderful up to there. Have you any 8



### explanation? 9

10



### DR. HARVEY CLEWELL : Actually, I forgot to point out what that 11



### horizo ntal line in each of these plots is. That‟s the 12



### limit of quantification. So actually we are fighting with 13



### the question of is that a real measurement or not. We see 14



### this, and very often that we get data that is below or in 15



### the vicinity of the limited qua ntification and then we're 16



### really not sure what it's meaning is. So in the case of 17



### DACT, this would not be because of the binding to albumin 18



### because this is free DACT that is being measured, and so 19



### the covalently bound would not be included, so even in 20



### th at case it's not clear what that reflects. Charles, did 21



### you want to say something? 22

23



### DR. CHARLES BRECKENRIDGE : Yes. I think that explains a lot. 24



### It's very difficult to put a number below the level of 25



### quantification. Thank you. 26

27



### DR. DANIEL SCHLENK : I have a quick question for you. On slide 28



### 26 and 27, the rat hepatocyte and human hepatocyte data in 29



### your statement there is that atrazine disappearance 30



### completely accounted for by production of the three phase 31



### 1 metabolites. If you are doing hepatocytes wouldn't you 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### expect to see the glutathione adduct as well being 1



### produced in that? 2

3



### DR. HARVEY CLEWELL : I believe it's a matter of rate. The 4



### oxidative metabolism happens very fast. 5

6



### DR. DANIEL SCHLENK : So would the GST though. I mean, you 7



### should get th e primary metabolite off of atrazine. You 8



### should get that adduct immediately. 9

10



### DR. HARVEY CLEWELL : You can see the slight decrease in DACT, 11



### later on, most likely reflects glutathione conjugation. 12



### The rate was rather slow. 13

14



### DR. DANIEL SCHLENK : Well, a gain, if you go back to metabolic 15



### scheme, for example, if you go straight down from your 16



### atrazine to your first GST adduct, that doesn't require 17



### any oxidative metabolism and that should take place 18



### immediately. If I understand it, I am pretty sure that is 19



### the primary metabolite of atrazine metabolism, isn't it? 20

21



### DR. HARVEY CLEWELL : No, I don't believe so, actually. When 22



### you have high affinity, oxidative metabolism like this, 23



### the concentrations of the compound in the liver stay very 24



### low, and the glutathion e pathway generally is actually 25



### quite slow. 26

27



### At very high concentrations, you would expect, as you 28



### saturate the oxidative metabolism, you would expect more 29



### production by the glutathione pathway. But we are trying 30



### to characterise the glutathione metabolit es better now, as 31



### I mentioned. It does appear that most of it is DACT, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### glutathione conjugates, which makes sense because DACT 1



### isn't subsequently oxidatively metabolized, so it 2



### circulates while it's being conjugated. 3

4



### And we will be running cytosol experi ments looking 5



### e specially for rates or reaction with glutathione, both 6



### with and without GST. So we will be in a better position 7



### to address that. Unfortunately, there really has only 8



### been identification data and really not quantitative 9



### characterization of which are the key glutathione 10



### conjugate metabolites. 11

12



### DR. DANIEL SCHLENK : Yes. It just seems a bit overblown that 13



### you say it completely accounted for production. That just 14



### doesn't jive with what you would expect to see in 15



### hepatocytes, I guess, that‟s my whole point. 16

17



### DR. CHARLES BRECKENRIDGE : Dr. Schlenk, could I perhaps try to 18



### address that question? We are doing cytosolic fraction 19



### studies with hepatocytes so that we can remove oxidative 20



### metabolism from the picture altogether. Like Dr. Clewell 21



### mention ed, we can actually then evaluate the rates of 22



### formation there. So that‟s the first line of attack. 23

24



### We also note that, as you cryofreeze hepatocytes for the 25



### purposes of processing, you actually deplete the GSH, and 26



### perhaps that is maybe complementing to the fact of not 27



### observing. The hepatocytes are obviously taken from whole 28



### animals and provided to the lab for assessment and they 29



### have to be provided in that manner. So it perhaps is a 30



### component of depletion of GSH that could be happening. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So we're tr ying to address the rate by actually looking at 1



### freshly harvested livers and looking at the cytosolic 2



### fractions. 3

4



### DR. DANIEL SCHLENK : Great; thanks. Dr. Chambers? 5

6



### DR. JANICE CHAMBERS : Two questions, Dr. Clewell. Do you 7



### consider any of the protein bind ing to be reversible or is 8



### it all covalent? 9

10



### DR. HARVEY CLEWELL : That would probably be a better question 11



### for Mel Andersen, if we could get him to come up here. 12

13



### DR. MEL ANDERSEN: Mel Anderson from the Hamner Institutes in 14



### North Carolina. The bindi ng that‟s been observed in the 15



### red cells and in the plasma is covalent. That has been 16



### actually evaluated by direct evaluation of the adducts. 17



### We don't have any evidence. I have done kinetic models 18



### for things that bind strongly. I have no evidence with 19



### atrazine that any of this is strongly bound, but 20



### reversible. 21

22



### DR. JANICE CHAMBERS : Thank you. And the second question is, 23



### do you have enough information about t he partition 24



### coefficients to estimate how much is getting into the 25



### hypothalamus or the parts of the brain? 26

27



### DR. MEL ANDERSEN: At this point, it appears that there is a 28



### fairly equal distribution of atrazine throughout the 29



### tissues, and it has a partition of about one. What you 30



### see in the blood is about what you see in the tissues. 31



### That's true of all the tissues that have been looked at. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. CHARLES BRECKENRIDGE : I'd like to add to that. 2



### Effectively in the study where we did the pharmacokinetic 3



### characterization of atrazine, those same animals provided 4



### us with tissue samples on the last blood co llection, so we 5



### have the pituitary hypothalamus adrenal gland and we're in 6



### the process of analyzing for the amount of atrazine, DEA, 7



### DIA and DACT, in those tissues, and we already know what 8



### the plasma concentrations are. So that was what we meant 9



### by in vi vo characterization of partitioning will verify 10



### the components that were derived from an in vitro modeling 11



### system. 12

13



### DR. JAMES MCMANAMAN : Yes, two quick questions. One is that 14



### you show human

-- and this is on slide 24

-- human and 15



### rats cells. What cells were those? I mean, they were 16



### hepatocyte, but presumably liver

- derived somehow, or are 17



### they cell lines, or what exactly were they? 18

19



### DR. CHARLES BRECKENRIDGE : These were human donor samples that 20



### we obtained there. I think there were three different 21



### donor s, so they are real obtained, fresh and 22



### cryopreserved. 23

24



### DR. JAMES MCMANAMAN : The second question is, do you see any 25



### other protein adducts, for instance, with these cells? 26



### Your primary ones may be albumin or some of the others, 27



### but are there protein adduc ts within the cell themselves? 28

29



### DR. MEL ANDERSEN: In the original work that was done at 30



### Colorado State to pay for that was published in 2003, we 31



### looked at these terminal half

- lives that you see in the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### plasma, as well as we saw them existing in tissues. It 1



### appears that atrazine, at a slow rate, cannot react with a 2



### variety of protein cysteines so you get can some level of 3



### adduction. 4

5



### So after the identification of persistence of binding in 6



### the red cells and in the plasma and in tissues, another 7



### student at Colorado State, Greg Dooley

-- so Tammy 8



### McMullin did her PhD at Colorado State with me and Bob 9



### Handa , and Greg Dooley with John Tessari and others in the 10



### Department of Biochemistry. He actually evaluated 11



### directly the binding, both the hemoglobin to album in. And 12



### then they looked at, I believe it was hypothalamic, the 13



### hypothalamic binding. They found a variety of binding 14



### sites in the hypothalamus all associated with cysteine 15



### adducts being formed in the tissue. 16

17



### DR. JAMES MCMANAMAN : So they were associate d with cysteine 18



### adducts, but did they localize where in the cell those 19



### cysteine adducts were? Were they in the endoplasmic 20



### reticulum? Were they in the mitochondria? Where? Do you 21



### know that information? 22

23



### DR. MEL ANDERSEN: It wasn't done by isolation wi thin the cell; 24



### it was done by identification of the proteins to which the 25



### adducts had formed. And they were not proteins that were 26



### expected to be found in any one particular sub

- cellular 27



### compartment but more uniformly distributed. 28

29



### DR. SUSAN AKANA : Short question. I am back on slide 30. 30



### These animals

- were these the first four doses that they 31



### saw either by gavage or the four nights of feeding? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. CHARLES BRECKENRIDGE : Are you referring to the effects 2



### slide of that slide? 3

4



### DR. SUSAN AKANA : Well, wha t I wanted to know is had they been 5



### maintained on the gavage and the diet for a number of days 6



### before the sampling started or were these the very first 7



### four doses that you are characterising? 8

9



### DR. CHARLES BRECKENRIDGE : Again, on the right hand panel, they 10



### represent the progression of doses for the animal. So 11



### that animal went on study for blood collection, it was 12



### dosed everyday for four days. And if it was scheduled to 13



### have a blood collection in the latter part of the study, 14



### then that was after having had four days of dosing. 15

16



### You cannot bleed the animals continuously through so you 17



### have to have sub

- fractions of animals for the purposes of 18



### blood collection. The LH part are the animals that were 19



### treated for four successive days and look for LH surge 20



### suppr ession at that point in time. 21

22



### DR. SUSAN AKANA : My question is, were they being given the 23



### atrazine when there is a known acute effect on food intake 24



### and body weight? 25

26



### DR. CHARLES BRECKENRIDGE : So on the first day of 27



### administration, as indicated by the pl asma data, that 28



### would be the first day they would have received the 29



### compound. They would have not received the compound prior 30



### to that, they're being gavaged. The other animals are 31



### being fed it. We actually were trying to achieve equal 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### doses by means of gavage versus feeding, and we had to 1



### estimate the likelihood that they would reduce their food 2



### intake and we increased the food concentration 3



### appropriately. 4

5



### We slightly undershot

-- and you can see that 40 mg per kg 6



### was an attempt to achieve a 50 mg per kg oral gavage dose, 7



### and that is attributed to the fact that we miss

- guessed 8



### how much we needed to put in the feed, given the reduction 9



### in food consumption that was occurring as a result of the 10



### dosing. So it was our best attempt to achieve equivalence 11



### of dose. We were slightly under in that particular case. 12

13



### DR. DANIEL SCHLENK : Okay. If there are quick questions we can 14



### go. My plan is that we would like to finish. We have one 15



### more presentation to go, and then if you guys are 16



### available tomorrow, which I am sure you are, that we could 17



### begin to tomorrow morning with questions as well because 18



### obviously we've had a lot to ponder. So if you can hold 19



### it to tomorrow that would be great. If you'd rather go it 20



### now we can go ahead. Okay. Go ahead, Dr. Greenwo od. 21

22



### DR. RICHARD GREENWOOD : Going back to slide 30, an explanation 23



### for the sort of behaviour if those areas really are 24



### similar, is that it's not total areas under the curve but 25



### area under the curve over some sort of critical threshold. 26



### Is there any evide nce that there is a critical threshold 27



### for this action of atrazine? 28

29



### DR. CHARLES BRECKENRIDGE : It's a very attractive hypothesis. 30



### We haven't yet figured out how to test that hypothesis. 31



### You move from correlation to causation, and that, as you 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### know, is always a difficulty and we haven't yet got there. 1



### Thank you. 2

3



### DR. DANIEL SCHLENK : Okay. So let's go ahead. Again, we will 4



### have an opportunity tomorrow morning. You guys will be 5



### first off in the morning, if that‟s okay with you. And if 6



### anyone has ques tions over this evening to come back to the 7



### team, I'm sure that they would be happy to answer those. 8

9



### DR. RICHARD GREENWOOD : Okay. And I'll move through this quite 10



### quickly and I'll try to setup a framework in which you can 11



### be able to understand the resul ts that we are now going to 12



### be showing to you. 13

14



### So we're using the model to

-- and I'll go to the 15



### schematic on the following page

-- we're using the model 16



### that we've generated, and which Dr. Clewell has describe, 17



### to provide a mechanism of calculating in ternal plasma 18



### concentrations following human exposure to atrazine and 19



### drinking water. So, the water consumption records that we 20



### see on the bottom effectively represent the details that 21



### Dr. Hendley spoke of. That is to say we have intermittent 22



### exposures t o different concentrations as the DEA, DIA and 23



### DACT in atrazine and water. 24

25



### We've taken those systems that were the most highly 26



### exposed, the 17 CWSs that were selected by the strategy 27



### that he described, and we coupled that schemograph intake 28



### profile with a survey of water intake record. 29

30



### There were 885 individuals that were part of a 7

- day water 31



### intake survey whereby they reported on an hourly basis 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### their water consumption records. And so, we took those as 1



### inputs into the PBPK model and derived from ther e, tracked 2



### the individual metabolites but calculated the total 3



### chlorotriazine concentration. 4

5



### At the same time, we took a point of departure from the 6



### animal model, such that was described by Dr. Rodriguez, 7



### and converted into an internal plasma concentra tion for 8



### TCT. So now we have a reference point of no effect 9



### compared to exposure, and that magnitude difference is a 10



### margin of exposure, so it's a ratio of those two numbers. 11



### And we will be reporting throughout those data. 12

13



### I won't go through this tiere d strategy, but let me just 14



### say that we're actually using the 99.9th percentile of the 15



### MOE distributions. For each simulation we had roughly 16



### 10,000 iterations of the calculations of the MOE. We do 17



### that in the one hand by using a standard case with 28 18



### sub jects calculating a rolling 4

- day average, 19



### sequentially, through the entire year. So there's 362 20



### values, and from there you calculate distributions of 21



### MOEs, and we are going to report to you the 99th 22



### percentile of those distributions. 23

24



### The standard case that we used was chosen as a point of 25



### reference so that other points of departure could be 26



### considered and we did a series of sensitive analysis. 27



### I'll try to move quickly through this. This is the 17 28



### CWSs that we selected, the most highly exposed CWSs, an d 29



### we are reporting now. In the top part you'll see the 30



### distributed dose NOAEL we picked from our feeding study 31



### that had no effect on the LH surge, 50 milligram per kg. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### We used two metrics for characterization. One was a TCT 2



### peak and the other was TCT a rea under the curve. The 3



### second one you see is a bolus dose NOAEL from our Sprague

4



### Dawley rat LH study. That was 10 mgs per kg. The next 5



### dose higher than that was 12 mgs per kg and we had an 6



### effect at that level. 7

8



### We were pretty confident that we had i solated the point of 9



### break between effect and no effect on the LH surge. And 10



### the third endpoint was the EPA proposed point of 11



### departure, 2.56, based on the bolus dose experiment, 12



### Cooper in 2010. 13

14



### So we selected those three different endpoints and 15



### compare d or did the margin of exposure calculation. And 16



### here you see for the 17 CWSs, those margins of exposures; 17



### the mins, the maxes and the averages. 18

19



### We then proceeded to investigate the sensitivity of those 20



### margins of exposure to the interpolation of peaks such as 21



### that was described by Dr. Hendley where between two 22



### measured peaks, seven days apart, and synthetic peak was 23



### inserted and we ran those chemographs through the model 24



### using

-- on the left hand panel of the green bars, you'll 25



### see the linear model

-- t hat‟s the linear interpolation 26



### between measured values

-- and then, on the right

- hand 27



### side you'll see the synthetic peak and the impact of that 28



### on the margin of exposure calculation. You can see there 29



### is an obvious reduction. It's roughly a three

- fold 30



### re duction in the margins because, in fact, it was roughly 31



### a three

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### In any case, that adjustment factor that he applied was 2



### approximately three

- fold and we confirmed that. If you 3



### want to look at that on the right

- hand s ide you'll see the 4



### MOEs are less in the other circumstance where we didn't 5



### have that interpolated peak. 6

7



### In the next slide, we looked at the

-- well, this is just 8



### the same information showing in a variety of different 9



### ways, and I'll slide through that. 10

11



### In the next slide, we asked the question what would be the 12



### impact of calendar year, a year

- to

- year variation so that 13



### from the highest peak that was observed in a particular 14



### year to a year that had the lowest peak, so that‟s what 15



### this comparison is doing. 16

17



### You should realize that when we do the simulation in a 18



### standard case, we pick that year which has a highest 19



### value, and in this particular instance we compared it to 20



### the year that had the lowest value for the TCT in drinking 21



### water. 22

23



### And you can see th at there's about on average a ten

- fold 24



### difference between the variances from year to year and 25



### that‟s due to environmental factors that drive residue 26



### concentrations in water. The CWS

- 96 actually we know was 27



### an off

- labeled use
, so that one year that maximum 28



### difference that was observed is attributed to, in fact, 29



### that high value. But overall there are generally very 30



### large margins, and in some years those margins falls below 31



### 10,000. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### The next slide, we asked the question

-- and all of this 2



### is in the form of sensitivity analysis and you can see the 3



### standard case we're comparing to the 10 mg per kg NOAEL 4



### using TCT area under the curve. 5

6



### We asked the question, what would happen if you modify the 7



### rolling average duration over which you're trying to 8



### integrate the internal dose; so one day of dose, two days 9



### of dose, three, four, seven, 14, 21, 28 and 90 days. You 10



### can see that it's virtually no impact of modifying the 11



### duration of the averaging period until you get past 28 12



### days, and then there's a modest increase in the margins of 13



### exposure as a result of averaging over a longer period of 14



### time when you're simulating from the CWSs. 15

16



### The next slide tests the question of; well what is the 17



### magnitude of the difference between the distributed dose 18



### versus the bolus does, so this is comparing the 50 19



### milligram per kg dose translated into an internal dose 20



### metric for the rat ; a nd comparing then the exposures of 21



### those individuals in the CWSs between those two metrics. 22



### You can see there's roughly a five

- fold difference in 23



### terms o f if you chose to use, for regulatory purposes, a 24



### bolus dose versus a distributed dose, and that implies a 25



### conservative judgement then that leads to a more 26



### conservative risk

- assessment. 27

28



### The next slides show the impact of choosing between a 29



### particular str ain of animals versus another strain of 30



### animals. So the Sprague

- Dawley rat, we did an extensive 31



### and clear characterization of the LH suppression following 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### four days of atrazine administration and the NOAEL was 10. 1



### Dr. Cooper's point of departure was 2.56 and you can see 2



### the magnitude of that choice of animal strain, relative to 3



### point of departure, is about a 3.6 fold difference in 4



### regard to the impact on the margins. 5

6



### The next slide shows, well, what's the impact of actually 7



### using the peak versus the are a under the curve, and this 8



### is kind of coming to the question of, well, what is the 9



### appropriate dose metric. If we don't know, at least we 10



### can measure what the consequences of choosing one versus 11



### the other. Intuitively, area under the curve makes some 12



### se nse. Area under the curve above a critical 13



### concentration probably makes more sense, but we are just 14



### trying to determine the magnitude of that impact. It 15



### looks like, in fact, if you use area under the curve you 16



### are slightly more conservative by an order o f 1.5 fold. 17

18



### Then we assessed a number of other variables that actually 19



### did not make much difference. All of these standard 20



### models were done with females aged 13 to 19 using 21



### databases from CSFII, the Continuing Food Intake Survey 22



### for Individuals. The wa ter consumption records, some body 23



### weight records, and so on, came from there. The frequency 24



### of water intake and the amount of water consumed came from 25



### a Bayer survey that had been embedded in those models for 26



### assessing the risk. 27

28



### But as you can note the re, at that age there is hardly any 29



### consequence between choosing 13

- to 19

- year

- olds versus 30



### 20

- to 49

- year olds, so that variable didn't seem to make 31



### much impact. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### We also evaluated the consequences of just including 2



### direct water where people reported hav ing consumed 3



### directly water versus, in some of these other databases 4



### there is information about indirect water. That is to say 5



### if you cook food in water that has atrazine in it, that 6



### could get incorporated in your food and you'll get 7



### indirect water consum ption through your food. By adding 8



### that variable, you can actually, again, decrease margins 9



### of exposure because you are effectively increasing 10



### exposure to the compound. So that was a sensitivity 11



### analysis around that aspect. 12

13



### And finally, we did two type s of simulation. The standard 14



### case was where we took 4

- day rolling averages and we just 15



### moved that rolling average day

- by

- day throughout the 16



### entire year, so we generated 362 samples or margins for 17



### the individual we were simulating. Those are dependent 18



### MO Es, obviously, because what you see in the last on is 19



### not related to what you are going to get in the next one. 20

21



### There was a certain desire by a staff at EPA to have that 22



### continuity of exposure so that that is what individuals 23



### will do in the real world. They will have a water supply 24



### and they will get residues that are coming through. 25

26



### The other approach was to actually randomly draw from the 27



### CWS 4

- day averages and just calculate the margins so it is 28



### a random draw, and that has an impact. It actually ma kes 29



### the analysis more conservative, as you can see, 4,000 30



### versus the 1,700. So those were the forms of sensitivity 31



### analysis we have done, and we have done a lot of other 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### interesting things relative to predicting the kinetics in 1



### relationship to the dynamic s. 2

3



### We have not had a great insight out of all of that yet. I 4



### am kind of enamored by my modeling friends here, because 5



### what takes me six months to do an experiment, it takes 6



### them

-- although Bob Silken (phonetic) will disagree with 7



### me

-- it takes him h alf a day to do an experiment. So, in 8



### that sense we can do sensitivity analysis and actually 9



### find out things that might be useful for us to measure in 10



### experiments. 11

12



### So to sum up, I would just say that all of the highly 13



### selected 17 CWSs, in terms of this MOE distribution 14



### analysis at the 99.9th percentile, we note in general that 15



### the MOEs are large and higher than a thousand. We note 16



### that there is roughly a three

- fold impact of the synthetic 17



### chemographs on those MOE distributions. We note that the 18



### MOE dis tribution seem to be insensitive to the duration of 19



### the averaging period up to about 28 days, and then after 20



### that it makes a significant difference, or it at least 21



### increases those margins. 22

23



### We believe that this modeling exercise can be used to 24



### inform the risk

- assessment process. We are not making a 25



### risk

- assessment here. We presented it in a neutral way by 26



### just discussing margins of exposure. And individuals and 27



### people who are responsible for those interpretations can 28



### judge the extent to which the facto rs that we have studied 29



### in our sensitivity make a difference or should be 30



### incorporated in such a regulatory decision. 31

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### We do note though, however, that as one makes 1



### progressively sequential judgements of conservative 2



### nature, you're effectively concatenati ng the margins or, 3



### shall I say, the protective factors. And in this way, we 4



### can actually quantify what you are doing by means of those 5



### judgements when you pick this animal strain versus that 6



### animal strain or this endpoint versus that endpoint. And 7



### really that was the purpose of that investigation was to 8



### assess in a quantitative way the impact of those 9



### judgements. 10

11



### So I think, with that, I will stop and we could take 12



### whatever questions you want relative to this simulation 13



### part or anything else that you would wish to discuss. 14

15



### DR. DANIEL SCHLENK : Thank you, Dr. Breckenridge. Just by a 16



### show of hands, how many actually have questions right now? 17



### Did I intimidate everybody? Okay. So what we'll do, if 18



### you don't mind, we'll start off with you in the mornin g 19



### and let the panel incubate a bit over the information that 20



### they've gotten. And then we'll hit you guys first thing 21



### in the morning with some questions if they're around, and 22



### then we'll move on from there. 23

24



### DR. CHARLES BRECKENRIDGE : Thank you, Mr. Chai rman, on behalf 25



### of Syngenta. 26

27



### DR. DANIEL SCHLENK : Okay. Thanks. With that, let me turn it 28



### over to Joe. And the panel is going to meet for a few 29



### minutes in the coffee room afterwards. 30

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### JOSEPH BAILEY : Actually, I just want to thank everybody. I 1



### have no other closing comments. Just note that the 2



### meeting tomorrow morning starts at 8:30, so we'll be here 3



### then. 4

5



## July 27, 2011

- 8:30 a.m. Day 2 6



### JOSEPH BAILEY : Good morning everyone, just want to welcome 7



### you back to the second day of the FIFRA Scientific 8



### A dvisory Panel. This is the Re

- evaluation of the Human 9



### Health Effects of Atrazine: Review of Non

- Cancer 10



### Effects, Drinking Water Monitoring Frequency and Cancer 11



### Epidemiology. 12

13



### Just want to make a note about public comment; you are 14



### getting some handout this morning. Syngenta is going to 15



### have a few clarifying slide on questions that were raised 16



### yesterday. There was one other comment that was in the 17



### docket from the Physicians for Social Responsibility; you 18



### should have that now. There is one comment from Tri azine 19



### Network; we may have additional handout for them, I am 20



### not sure at this point. 21

22



### Finally, there is the Center for Regulatory 23



### Effectiveness‟s comments that you should also have. Just 24



### a reminder, please state your name into the microphone 25



### when you ma ke any comment, and with that I will turn it 26



### over to Dr. Schlenk. 27

28



### DR. DANIEL SCHLENK : Thank Joe. Let‟s go around the room one 29



### quick time, just have each panel member introduce 30



### themselves, where they are from and their area of 31



### expertise, for the general public. I will begin; my name 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is Dan Schlenk. I am a Professor of Environmental 1



### Toxicology at the University of California Riverside. My 2



### expertise is in Fate and effects of Emerging contaminants 3



### and Pesticides and aquatic organisms. 4

5



### DR. KENNETH PORTIER : Good morning, I am Ken Portier, Managing 6



### Director, Statistics and Evaluation at the American 7



### Cancer Society in Atlanta. I am a Bio

- Statistician. 8

9



### DR. JANICE CHAMBERS : I am Jan Chambers, with the College of 10



### Veterinary Medicine at Mississippi State Un iversity. I 11



### am a Pesticide Toxicologist and a member of the permanent 12



### panel. 13

14



### DR. STEPHEN KLAINE : I am Steve Klaine, Clemson University. I 15



### am an Aquatic Ecotoxicologist and I am a member of the 16



### permanent panel. 17

18



### DR. ELLEN GOLD : I am Ellen Gold. I am from U. C. Davis where 19



### I am a Professor of Epidemiology. 20

21



### DR. FRANK BOVE : I am Frank Bove. I am with the Agency for 22



### Toxic Substance and Disease Registry. I am a Senior 23



### Epidemiology in the Division of Health Studies. 24

25



### DR. HEATHER YOUNG : I am Heather Yo ung, George Washington 26



### University, Department of Epidemiology, specializing in 27



### cancer reproductive outcomes. 28

29



### DR. NELSON HORSEMAN : Nelson Horseman from the University of 30



### Cincinnati in the Department of Molecular and Cellular 31



### Physiology and I am an Endocri nologist. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. JAMES MCMANAMAN : Jim McManaman, University of Colorado, 2



### Department of Obstetrics and Gynecology. 3

4



### DR. DANIEL GRIFFITH : I am Daniel Griffith, Ashbel Smith 5



### Professor of Geospatial Information Sciences , University 6



### of Texas at Dallas. I am a Spatial Statistician. 7

8



### DR. HERBERT LEE : I am Herbie Lee, University of California

, 9



### Santa Cruz where I am a Professor of Statistics and the 10



### Vice Provost for Academic Affairs and my research areas 11



### includes spatial statistics and deterministic Computer 12



### Mode ling. 13

14



### DR. ROBERT GILLIOM : Bob Gilliom, U. S. Geological Survey. I 15



### direct our pesticides studies for the National Water 16



### Quality Assessment Program and my expertise is in 17



### primarily the hydrology and water quality monitoring 18



### aspects of this problem. 19

20



### DR. R ICHARD COUPE : Richard Coupe with the U. S. Geological 21



### Survey out of Mississippi Water Science Center and I am a 22



### researcher on the fate and transport of agricultural 23



### chemicals. 24

25



### DR. SUSAN AKANA : I am Susan Akana. I am currently at City 26



### College of San Fra ncisco, which is my second career. I 27



### have retired from the University of California

– San 28



### Francisco where I had a career as a research physiologist 29



### in stress and energy balance. 30

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### DR. KEVIN O'BYRNE : My name is Kevin O‟Byrne. I am from 1



### King‟s College Lond on. I am a Professor of Reproduction 2



### and Endocrinology and I am passionate about what controls 3



### luteinizing hormone secretions. 4

5



### DR. KATHERINE ROBY : I am Kathy Roby from the University of 6



### Kansas Medical Center and my expertise is reproductive 7



### endocrinolog y. 8

9



### DR. BARRY TIMMS : I am Barry Timms, Professor of Basic 10



### Biomedical Sciences, Sanford School of Medicine, 11



### University of South Dakota with a specialty in 12



### reproductive biology and prostate biology. 13

14



### DR. TRAVIS JERDE : I am Travis Jerde, Indiana Universit y 15



### School of Medicine, Assistant Professor of Pharmacology, 16



### Toxicology and Urology and I specialize in prostate 17



### biology. 18

19



### DR. PENELOPE FENNER

- CRISP : I am Penny Fenner

- Crisp, private 20



### consultant living in Charlottesville, Virginia and a 21



### member of the state‟s Pesticide Control Board. My area 22



### of expertise is toxicology and human health risk 23



### assessment. 24

25



### DR. BETTE MEEK : I am Bette Meek. I am at the McLaughlin 26



### Center of the University of Ottawa and my background is 27



### in regulatory risk assessment and toxicology. 28

29



### DR. RICHARD GREENWOOD : I am Richard Greenwood. I am an 30



### Emeritus Professor at the University of Portsmouth and my 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### expertise is in mode of action of pesticide and 1



### pharmacokinetics. 2

3



### DR. WILLIAM HAYTON : I am William Hayton, Professor Emeritus, 4



### College of Pharmacy at Ohio State University, expertise 5



### in pharmacokinetics. 6

7



### DR. DANIEL SCHLENK : Thank you everyone, I appreciate that. 8



### We are going to start out this morning; we have the 9



### Syngenta team up again this morning. They have provided 10



### some additional sl ides as Joe had mentioned. What I 11



### would like to do if it is okay, if we can maybe in five 12



### minutes go though a list of what those additional slides 13



### are and then open it up to the panel for additional 14



### questions. I think there were some follow up questions 15



### maybe that you may have and we will go from there. So 16



### Dr. McFarland if you can provide the list of the 17



### additional material that would be great. 18

19



### DR. JANIS MCFARLAND : Thank you Dr. Schlenk and good morning 20



### everyone. Thanks again for all the time yesterda y. We 21



### have three areas of clarification, based on questions we 22



### received yesterday afternoon, in the very brief handouts. 23



### The first area is some of the questions on food intake. 24



### The second area is on the pharmacokinetics

– slide 30 25



### questions with the are a of under the curb. The third is 26



### areas of water from assessment of the upper centiles 27



### concentration in finished drinking water. 28

29



### Attached to that are some of the reasons for a very few 30



### number of daily monitoring samples that were missing from 31



### the dail y monitoring assessment that was provided to the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### panel. So out of over 500 samples the reasons, for 1



### instance when the power went off at a particular site. I 2



### will turn it over to Dr. Breckenridge to quickly go 3



### through the slides on food intake. 4

5



### DR. CHARL ES BRECKENRIDGE : Good morning ladies and gentlemen, 6



### my name is Charles Breckenridge. I am a toxicologist 7



### with Syngenta. There were some questions yesterday 8



### afternoon relating to the impact of atrazine on food 9



### intake and body weight. 10

11



### I selected one s tudy to represent that impact; this was a 12



### multi

- generation reproduction study in atrazine. It is a 13



### guideline study. The schematic of the study is laid out 14



### here where you see the animals beginning dosing early 15



### young adult, male and female F 0 

### generation. They are 16



### treated for several weeks and they are mated in driving a 17



### second generation. 18

19



### So in those kinds of studies we track body weight and 20



### food intake on a weekly basis. This graph is a 21



### representation of food consumption in the male animals in 22



### F 0 

### and F 1 

### generation. You will note that there is an 23



### immediate and sustained impact on food intake in the 500 24



### part per million (ppm) dose group at 40 mg/kg. The 50 25



### ppm dose group has no affect on food intake in the male 26



### or F 0 

### and F 1 

### . The same data is shown he re for the female 27



### animals. Those asterisks below the data sets are 28



### indicating statistical significance, and again the 500 29



### ppm group is having an effect whereas the 50 ppm is 30



### comparable to control. 31

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### There is a consequence of that relative to body weight 1



### progression over the course of that treatment interval, 2



### and you can note on the left

- hand side there is a 3



### progressive slow separation of treated animals from the 4



### controls at the 500 ppm where there is significant 5



### reduction in body weight gain throughout t he course of 6



### that continuous feeding regimen ; f or the males F 0 

### and F 1 7



### generations and the same is observed in the female‟s. 8



### The indication where the elevation occurs, where the 9



### females are mated and they are developing a litter. So 10



### that body weight gain is associated with that event. 11

12



### So in summary then, the continuous feeding

- type studies 13



### suppressed body weight, suppressed food intake, and the 14



### same experience occurs with respect to gavage dose. The 15



### gavage dose is instantaneously on a day of treatment

, 16



### impact food intake and body weight progression. Those 17



### effect and no effect level for those kind of studies are 18



### documented in probably the short

- term experiments. The 19



### best one would be the CODAR study 0639081. If the panel 20



### is interested in seeing those data summarized, we could 21



### quickly do that and provide it to the panel as a handout 22



### later. But for now let‟s just say that there is clearly 23



### affects on body weight and food intake of atrazine and 24



### there is clear dosage that have no effect as well. I 25



### will s top there and pass the topic over to the kinetic 26



### question, unless there are any questions about that 27



### particular data set. 28

29



### DR. DANIEL SCHLENK : Okay, any questions we have. 30

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### DR. SUSAN AKANA : I am interested in the group that had a 1



### lower body weight, lower food intake. It is likely their 2



### body composition is going to be different. Have you 3



### measures of Leptin for instance? 4

5



### DR. CHARLES BRECKENRIDGE : No, we have not measured Leptin in 6



### any of those studies. 7

8



### DR. DANIEL SCHLENK : Okay, let‟s go ahead and move on. 9

10



### DR. HARVEY CLEWELL : Harvey Clewell, from The Hamner 11



### Institutes. I just was going to show a couple of slides 12



### about the question regarding the AUCs, because we did not 13



### have the quantitative information yesterday; I could not 14



### remember the details. 15

16



### T his is that same study that I described yesterday with 17



### the three gavage and three dietary dosages; and this is 18



### the slide that I showed. This is a slide I did not show 19



### and it shows the area under the curb versus dose with red 20



### being gavage, blue being die t. The DACT is on the right. 21



### The area under the curb is similar, slightly lower for 22



### the diet but then the mg/kg per day dose for diet was 23



### slight lower than the gavage. What you may not be able 24



### to see is the Y

- axis on these. The DACT is about sixty 25



### time s higher area under the curb compared to the DIA, and 26



### DEA and atrazine are even smaller . S o the DACT really 27



### dominates the area under the curb exposure for these four 28



### compounds. 29

30



### As I suggested yesterday, the area under the curb 31



### exposure in these dieta ry and gavage studies was pretty 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### similar and what the most striking difference is the 1



### pulsatile nature of the gavage exposure as opposed to 2



### more stable concentrations achieved with the dietary 3



### intake and the very striking differen ce in the LH 4



### suppression w ith the diet versus gavage is possibly

, we 5



### think

, associated with this more pulsatile nature and the 6



### higher concentration achieved. 7

8



### DR. DANIEL SCHLENK : Okay, thanks. Any questions related to 9



### that? 10

11



### DR. SUSAN AKANA : Yesterday there was some discussion o f the 12



### fact that the atrazine and their compounds can bind to 13



### red blood cells and to albumin. Have you attempted to 14



### look at free circulating, unbound compounds in the 15



### experiment you just showed? 16

17



### DR. HARVEY CLEWELL : That is what was reflected; there were 18



### free compound, not covalently bound compound, so that is 19



### what was measured, yes. 20

21



### DR. SUSAN AKANA : A nd not bound to albumins, so totally free. 22

23



### DR. HARVEY CLEWELL : That is correct. I mean the binding is 24



### covalent and so when you do the analysis

, you don' t get

- 25



### - the coloring is gone, it doesn't come off. 26

27



### DR. DANIEL SCHLENK : Okay, last but not least, we have Dr. 28



### Hendley. 29

30



### DR. PAUL HENDLEY : Okay, thank you very much. Good morning, 31



### Paul Hendley, Syngenta. There are just a couple of quick 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### slides here, thankfully. The first one is just pulling 1



### one of the tables from Dr. Mosquin's report of April. 2



### This is really just pointing out the raw and finished 3



### data from the Safe Drinking Water Act and the frequent 4



### monitoring VMP and AMP. Just simply to give you some 5



### reference values of what those high centile concentration 6



### were in raw and finished from over 48,000 finished water 7



### samples, frequent monitoring. That 99.9 centile; it is 8



### 22.66 and the report will also show you what the bounds 9



### around that are. 10

11



### Th e other thing we wanted to point out, one of the panel 12



### members had asked the question

– very incredibly 13



### observantly

– about some of the missing data. What we 14



### normally do when we submit data and we pull data together 15



### is, we have a spreadsheet of values and in this case, it 16



### is 500+ raw, and 500+ finished. We have another 17



### worksheet that says metadata, and the metadata includes 18



### this table. In the report, because it is only a 19



### preliminary data report because there are more samples 20



### being collected, we have not put the metadata statement 21



### in the appendix. Had it been the full year‟s report, you 22



### would have seen this table and I believe the question s 23



### were focus on June 29 th 

### , an auto

- sampler failure . These 24



### auto

- samplers are sitting in water treatment plants and 25



### s om etimes folks either turn off the water streams to them 26



### or the electric sockets. 27

28



### But just for the record that stretch in the middle for 29



### number 54 came from that dreadful period when the levees 30



### were being opened and that is why it was not just a minor 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### fl ood on the road; there was a foot of water shifting 1



### around. 2

3



### So for the record, there was a good reason why those 4



### samples were not taken. Thank you. 5

6



### DR. DANIEL SCHLENK : Okay, any questions for Dr. Hendley? Any 7



### final questions for the Syngenta team and the panel as a 8



### whole? 9

10



### DR. RICHARD COUP: Can I ask a PRZM question from yesterday? 11



### It has to do with kind of how you scale it up to larger 12



### watershed size. Now, my understanding is this is an 13



### edge

- of

- field model. So you have a 500 square mile basis 14



### and you are treating that 500 square mile as an edge

- of

15



### field now. So everything is instantaneously transported 16



### in like one day to a point that you are using as your 17



### measurement. How would you ever account for transport 18



### through streams and hydrology or a re you planning on 19



### scaling it up so you can go larger. 20

21



### DR. PAUL HENDLEY : I think this is why I said this was the 22



### outstanding issue that maybe needs to be tackled, because 23



### it was originally a technology design for the ecological 24



### monitoring program where w e were thinking of watersheds 25



### that were 10 to 50 square miles. We found it is fine 26



### working with some of the AMP watersheds, the smaller 27



### ones. But the challenge is working out exactly where 28



### some sort of routing comes in or w eather. 29

30



### I was trying to mak e the point yesterday , i n fact, the 31



### moment you get to an area where averaging starts taking 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### into account a lot of what is going on in the 1



### environment, w hether regression approach may be easier in 2



### terms of a simple way forward. 3

4



### So we are still looking a t how to account for the 5



### routing. You may have notice in one of the tables we did 6



### put time of concentration in for the various sizes of 7



### water bodies, which is exactly why we are looking at that 8



### problem. So work in progress and it is a good question 9



### and i t needs to be address. But if you remember from 10



### many of the key watersheds the dominant, for example, 143 11



### static watersheds are small, less than 50 square miles. 12



### And to be blunt, those are the ones that tend to have the 13



### highest residue so those are the o nes that I think are of 14



### primary interest at the moment. 15

16



### DR. JAMES MCMANAMAN : This is a question for Dr. Breckenridge. 17



### This is on the feeding question. So I notice that during 18



### pregnancy, there is really no effect of atrazine on food 19



### intake during pregna ncy, but there is a difference in 20



### weight gain. Do you think that is significant? If you 21



### could comment on that please. 22

23



### DR. CHARLES BRECKENRIDGE : We see an impact at higher doses on 24



### the weight gain in the mothers and it also finally 25



### reflects itself in th e up weight at birth. There has 26



### always been a question in my mind about the food 27



### utilization efficiency that perhaps in periods of high 28



### demand that consequence on food intake becomes more 29



### important to the animal. So I cannot really say much 30



### more than tha t
, but we do know that for the same amount 31



### of food in consumption, the relative body weight gain is 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### proportionally less. That is to say, food efficiency is 1



### less in atrazine treated animals. 2

3



### DR. TRAVIS JERDE : This question is probably best addressed to 4



### Dr. Simpkin. You showed a slide yesterday where serum 5



### and therefore probably tissue concentrations of atrazine 6



### metabolite, particularly DACT, can reach levels of a 7



### micro

- molar to ten micro

- molar after a dose. But the 8



### doses you gave are fairly high, 3 mg /kg to 50 mg/kg and 9



### water exposure is about a hundred or less, but you only 10



### gave one dose. Are you planning studies to look at lower 11



### and repeated dosage and tissue concentration of what are 12



### metabolite gains ? Because when you start to get to 1

- - 13



### 10 micro

- molar concentration that is the concentration 14



### where pharmacologic and toxicological effects can happen

. 15



### I am just wondering what your thoughts are on that. 16

17



### DR. JAMES SIMPKIN: That is a Syngenta research planning 18



### question and I think it is best handled by Dr. 19



### Breckenridge. 20

21



### DR. TRAVIS JERDE : Okay, that is fine. 22

23



### DR. CHARLES BRECKENRIDGE : When we go to quantification and 24



### the presence of analytes in plasma or tissue, we run into 25



### limits of the quantification issue. So as we roll down 26



### to really low er dosages, we start to now not be able to 27



### measure. And I think that our intent

, relative to the 28



### monkey study
, is in fact to try a 20 part per million 29



### administered dose so we will achieve relatively low 30



### concentrations in plasma. 31

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### We think we will be able to measure DACT at that point

, 2



### but we doubt we are actually going to detect the mono, 3



### the acolytes or the parent with that low level of an 4



### inputted dose. But we are trying to move down the region 5



### of relevance to actual possible human exposure and that 6



### is even a thousand

- fold higher than the average of two 7



### part per billion. 8

9



### So in some ways we start to run into analytic sensitivity 10



### questions as we are trying to quantitate a small dose 11



### entering a volume of distribution with rapid metabolism. 12

13



### DR. RICHA

RD GREENWOOD : Yesterday you talked about two phases 14



### of elimination of DACT. One, which was rapid with a 15



### half

- life which was in hours and the slower process, was 16



### tens of hours which you put down to the time to turn over 17



### the plasma protein . T hose figures must have been derived 18



### from the in vivo data, I guess. 19

20



### DR. CHARLES BRECKENRIDGE : I will take a first answer at this 21



### and then Dr. Clewell can comment more on the modeling 22



### part. But those observations came from two types of 23



### studies. One was the 14 

### C stu dy in monkeys where we are 24



### looking for the urinary elimination rates and we note 25



### just that you can do a one compartment model

, but in fact 26



### it seems like a two compartment model is better to 27



### characterize that. And that was also observed in the 28



### modeling of the human urinary elimination with the single 29



### .1 mg / kg dose as an input dose for those individuals. 30

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### So I believe that it is a matter of how to best 1



### characterize the rate of elimination. It seems like it 2



### fell into two different compartments. 3

4



### DR. HARVE Y CLEWELL : I just wanted to add that the work at 5



### Colorado State was some years ago while with Tammy 6



### McMullin is what identified the nature of the longer 7



### half

- life being the plasma binding. S imulation was used 8



### in order to come up with the timeframe for th at and it 9



### does coincide close to the turnover rate for plasma 10



### albumin but it has not been completely demonstrated I 11



### would say. 12

13



### DR. RICHARD GREENWOOD : Just to follow up on that. So you 14



### have evidence from the monkey study but also the previous 15



### study in ra ts. And again you had sufficient data and 16



### details to get a good fix on that, I take it. 17

18



### DR. DANIEL SCHLENK : Any other questions. 19

20



### DR. SUSAN AKANA : A general point I hope you can clarify. 21



### With the atrazine, on one hand what I understand it is 22



### not that soluble in water so it is difficult to 23



### administer in fluids or to inject. On the other hand, 24



### when we talk about the metabolism of it, the patrician 25



### coefficient, if I recall correctly I think Dr. Rodriguez 26



### said it is a patrician coefficient of what. And t hat the 27



### one compartment model was appropriate; that there was 28



### not, for instance, a preferential uptake or storage of 29



### the atrazine compounds in fact. 30

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### Now, can you recount those two facts? One
, that it is 1



### not very soluble in water; on the other hand you have a 2



### one compartment model ? 3

4



### DR. HARVEY CLEWELL : A problem with the one compartment model 5



### is that the half

- life

, the plasma kinetics is clearly not 6



### single compartment because of that long terminal half

7



### life. And so there is a transition from the rapid 8



### clearance of the compounds themselves, which is reflected 9



### in the total radioactivity and then the longer half

- life 10



### for clearance of the albumin adducts. S o it is not 11



### actually a good candidate for single compartment 12



### modeling, if you are using the total ra dioactivity data. 13

14



### You might be able to use a single compartment model for 15



### the total chlorotriazines. I have not really tried to do 16



### that. We started with the PBPK approach, but the problem 17



### with that is that does not consider the flow limit ed 18



### metabolis m in the liver. So you would not correctly 19



### describe the presystemic clearance of the compounds in 20



### the liver before reaching the blood. So it is a good 21



### candidate for more physiological descriptions. 22

23



### DR. WILLIAM HAYTON : That previous question triggers this 24



### thing that I wonder about, and that is the one 25



### compartment kinetic parameter value. Following the 26



### d istribution numbers are, I think up around five or six 27



### liters per kilo. And I believe I heard you say, Dr. 28



### Clewell, that the distribution is fairly un iform across 29



### all of the tissues . I am wondering if there is any 30



### reconciliation of that. 31

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### DR. HARVEY CLEWELL : That is an artifact of the use of the 1



### terminal half

- life, which is really based on one very 2



### small portion of the total radioactivity that does no t 3



### really reflects the distribution of the vast majority of 4



### the compound. So that is the trouble with volumes of 5



### distribution of course, is they do not have a 6



### physiological meaning. So I think that that very high 7



### level is just because you have a very slow clearance and 8



### low blood level s and so then you have to impute a very 9



### high volume of distribution in order to put it into a one 10



### compartment description. So I think it is just 11



### artificial. 12

13



### DR. DANIEL SCHLENK : Okay, thanks to the Syngenta team; 14



### appreciate that. Our next public commenter will be 15



### Wendelyn Jones from CropLife America. Dr. Fenner

- Crisp ? 16

17



### DR. PENELOPE FENNER

- CRISP : While they are changing folks 18



### around, I have a question Joe. Will the presentations 19



### that have been made by the agency and the co mmenters be 20



### available on regulations.gov during the course of this 21



### meeting? 22

23



### JOSEPH BAILEY : They should be actually. I think they are on 24



### docket now; they are just waiting to be posted. The EPA 25



### presentations... yes. 26

27



### DR. PENELOPE FENNER

- CRISP : Since Har vey reminded me it is 28



### hard to see some of those numbers. My eyes are getting 29



### kind of old and I would like to blow them up. 30

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### JOSEPH BAILEY : I looked last night and the docket had not 1



### posted. 2

3



### DR. PENELOPE FENNER

- CRISP : They were not there last night. 4

5



### JOSEPH BAILEY : Yes, but they are there, we just need to get 6



### to the docket and tell them to please put it up. So we 7



### will get a note out to them and they should be available 8



### very shortly. 9

10



### DR. PENELOPE FENNER

- CRISP : Thank you. 11

12



### DR. DANIEL SCHLENK : Do you have a presentation? 13

14



### WENDELYN JONES: You know, t here are no slides. 15

16



### DR. DANIEL SCHLENK : Amazing. 17

18



### WENDELYN JONES: There are no reading materials. 19

20



### DR. DANIEL SCHLENK : Okay, thanks. 21

22



### WENDELYN JONES: Good morning, I am Wendelyn Jones and I am 23



### here to day to represent CropLife America, and on behalf 24



### of our organization, we respectfully encourage the 25



### EPA/OPP and the SAP to remember their science background 26



### and ensure a science

- centric path such that decisions are 27



### made on valid and reproducible science. CropLife America 28



### is a not

- for

- profit trade organization representing the 29



### nation‟s developers, manufactures, formulators, and 30



### distributors of plant science solutions for agriculture 31



### and pest management in the United States. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### We are committed to the safe and responsible use of the 2



### industry‟s products in order to provide safe and abundant 3



### food as well as control for insect and plant disease 4



### vectors for the protection of human health and providing 5



### valuable benefits back to the consumer. Crop protection 6



### prod ucts require extensive data development for initial 7



### and continued registration. We respectfully note that 8



### this is the 11 th 

### SAP on atrazine since 2000. Atrazine was 9



### reregistered in 2006 based on a 12

- year EPA review and 10



### the input from multiple SAPs. 11

12



### This current SAP is part of a series scheduled by EPA 13



### beginning in 2009 to reevaluate atrazine. Both Syngenta 14



### and EPA have responded to this reevaluation of atrazine 15



### by providing many additional studies to characterize the 16



### toxicological characteristics an d exposure potential. A 17



### robust scientific data base supports the continued use of 18



### this valuable product. A valid and reproducible sound 19



### science should always lead EPA‟s decision making. 20

21



### The atrazine safety package represents one of the most 22



### advance sciences for the acquisition of hundreds of 23



### thousands of drinking water samples, detailed mode of 24



### action studies, and cutting

- edge pharmacokinetic 25



### pharmaco

- dynamic characterizations. Such a rich database 26



### should provide confidence in the safety of this pro duct. 27

28



### We encourage EPA/OPP to lead the way in utilizing advance 29



### scientific approaches such as evident by atrazine 30



### research being reviewed at this SAP. Such leadership 31



### would align with two recent NAS reports, T oxicology 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### T esting in the 21 st 

### C entury and S cience and D ecisions : 1



### C alling F or a M ajor S cientific C hange in H ow T oxicology 2



### and R isk A ssessments A re D one. 3

4



### Among the cardinal principles of regulations of drinking 5



### water under SDWA, is providing the public with accurate 6



### and informative human healt h risk information and 7



### avoiding unnecessary public alarm by false allegations of 8



### threats to the safety of its drinking water. As 9



### respected scientists, we ask that the SAP exercise clear 10



### judgment in the report and recommendations that it 11



### provides in order to help assure that the work reflects 12



### the best scientific principles and avoids creating 13



### unwarranted public concerns. 14

15



### Additional ly , we encourage the EPA and the SAP to 16



### carefully consider the mode of action studies and the 17



### pharmacokinetic studies. EPA defines mode of action as a 18



### sequence of key events and processes
, starting with the 19



### interaction of an agent with a cell

, proceeding through 20



### operational and anatomical changes and resulting in the 21



### adverse affect. 22

23



### Previously the agency has noted in certa in experimental 24



### rodent strains, that atrazine induces changes in 25



### luteinizing hormone secretion without any adverse 26



### consequences on reproduction. Within the white paper for 27



### this SAP, the agency is proposing to continue to use the 28



### change in LH secretions as the basis of the atrazine risk 29



### assessment. 30

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### We also note that the duration of exposure is an 1



### important parameter considered in evaluating the 2



### relationship between dose and attenuation of the LH 3



### surge. The ability to confidently compare dose response 4



### a nd exposure in rats to human s is extremely important. 5



### We are therefore very encouraged to see that the agency 6



### has paid particular attention to the elucidation of the 7



### pharmacokinetic behavior of atrazine. The integration of 8



### this understanding and other ne w studies is key to enable 9



### OPP‟s leadership and we encourage for the refinement of 10



### this approach. 11

12



### Lastly, we would like to highlight a recent paper that 13



### was issued as part of the Agricultural Health Study. The 14



### AHS is a long

- term research project that has been 15



### tracking the health of nearly 90,000 people, certified 16



### pesticide applicators and their spouses in Iowa and North 17



### Carolina since 1994. 18

19



### The report recently published in environmental health 20



### perspective concluded that overall there was no 21



### consist ent evidence of an association between atrazine 22



### use and any cancerous site. No one cares more about the 23



### safety of crop protection products including pesticides 24



### than the farmers who use them on their crops and soils 25



### where are own children play. Farmers ha ve an important 26



### stake in keeping their land, rivers and ponds safe for 27



### their families, their neighbors and their communities. 28

29



### If valid reproducible sound scientific research finds 30



### that any agricultural pesticide cannot be used safely, we 31



### will be the fi rst to agree with increased regulations. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Sound science has found repeatedly that atrazine i s safe 1



### when used responsibly and according to label 2



### recommendations. The comprehensive dataset on atrazine

, 3



### over the years, including the more recent research, 4



### rea ffirmed the safety of atrazine. Thus, COA supports 5



### this product as it helps us raise our crops affordablely 6



### and sustainablely. Thank you for your time and 7



### attention. 8

9



### DR. DANIEL SCHLENK : Thanks. Any questions from the panel? 10



### Okay, thank you very much. Our next public commenter 11



### will be Scott Slaughter. I believe there is a handout 12



### associated with the comments. 13

14



### SCOTT SLAUGHTER: I have been here before and it is always a 15



### pleasure to appear before the Science Advisory Committee. 16



### Hi, my name is Scott S laughter and I am commenting today 17



### on behalf of the Center for Regulatory Effectiveness. I 18



### will be citing a number of documents. There are links to 19



### all the documents I refer to in the written materials you 20



### have. And I would like to first address the Coo per Study 21



### on LH surge. EPA has validated at least four tests for 22



### measuring the effects of atrazine on LH surge. Dr. 23



### Cooper‟s LH attenuation study differs significantly from 24



### the four LH tests that EPA has validated. 25

26



### One difference is that the Cooper S tudy only tests Long

27



### Evans rats. The four validated tests only use Sprague

28



### Dawley rats. The Cooper Study on Long

- Evans rats is also 29



### inconsistent with EPA‟s standard procedures for assessing 30



### potential endocrine effects of all pesticides including 31



### atrazine . In its Endocrine Disruptor Screening Program, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### affectionately or unaffectionately known as EDSP, EPA 1



### used Sprague

- Dawley rats to validate tests for potential 2



### pesticide endocrine effects on female pubertal 3



### development. The endpoints of these validations test in 4



### EDSP included vaginal openings and estrous cycling. 5



### Atrazine was utilized as a control in the validation of 6



### this EDSP assay. 7

8



### EPA‟s report for this validation study adopts Sprague

9



### Dawley rats as the strain to use in testing pesticide 10



### endocrine effects on development and reproduction. And I 11



### quote from EPA validation study in the EDSP as follows, 12



### “In summary, EPA is aware of the potential for 13



### differences between strains and therefore expresses a 14



### preference for standardization using Sprague

- Dawley rat.” 15



### If EPA still wants to rely on Dr. Cooper‟s study and its 16



### non

- standard use of Long

- Evans rats to regulate the 17



### endocrine effects of atrazine, then we ask that EPA first 18



### validate that study. 19

20



### Validation of the Cooper Study on LH attenuation should 21



### comport with first, EPA‟s guidance for validating 22



### endocrine disruptor tests; second, EPA‟s Information 23



### Quality Act Guidelines; and third, guidance produced by 24



### the NTP Interagency Center for the Evaluation of 25



### Alternative Toxicological Methods ( NICEATM ) and the 26



### Interagency Coordinating Committee on the Validation of 27



### Alternative Methods ( ICCVAM ) . Among other things, the 28



### validation process should determine whether Dr. Cooper‟s 29



### study results are reproducible by other independent 30



### laboratories. 31

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### As EPA noted e arlier, Syngenta submitted studies that 1



### generated different results on LH attenuation than Dr. 2



### Cooper‟s study. The validation process should determine 3



### whether the NO A EL and LO A EL from Dr. Cooper‟s study are 4



### reproducible by other independent laboratories. The 5



### validation process should also determine whether the use 6



### of Long

- Evans rats in tests for potential endocrine 7



### disrupting compounds is scientifically justified. If so, 8



### the EPA should reconsider it s Endocrine Disruptor 9



### Screening Program. 10

11



### I would lik e to briefly now address some of these 12



### specific charge questions. I am not going to repeat all 13



### of the comments in my written testimony, in the interest 14



### of saving time. Please I refer you all to those. 15

16



### The next subject I would like to address is on pa ge four 17



### of my written comments, which are Mode of Action and 18



### Adverse Outcome Questions, which I identified, perhaps 19



### incorrectly, as five, six, seven, eight and nine to the 20



### SAP. 21

22



### To begin with EPA‟s Issue Paper, which was presented to 23



### you for this SAP st ates, and I quote EPA. “This Agency 24



### is using the 33% LH surge attenuation after a 4

- day 25



### exposure as a precursor event to protect for other 26



### adverse outcomes including estrous cyclicity disruption, 27



### and delays in sexual maturation occurring at higher doses 28



### i n laboratory animals.” 29

30



### Using the 33% LH surge attenuation after a 4

- day 31



### exposure, like EPA proposes to do, is not based on any 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### adverse human health effect. In fact, the September 2010 1



### SAP explained in its written minutes that 33% surge 2



### standard is not based on any adverse rat event. And I 3



### quote from the minutes of the 2010 SAP, “Greater than 80% 4



### attenuation of the LH surge

, in any given 4

- day estrous 5



### cycle
, would be needed to observe deleterious effects in 6



### the reproductive system s in rats.” And anoth er quote 7



### from the 2010 SAP minutes, “Attenuation of the LH surge 8



### has no adverse effect on reproductive function and does 9



### not prevent ovulation until about 80% attenuation. 10



### Therefore, the proportion of animals and the latency to 11



### exhibition of delayed cycle s might constitute a better 12



### endpoint or ' adverse response ' for determining the effect 13



### of atrazine than is attenuation of the LH surge.” 14

15



### There are other quotes from the 2010 SAP minutes, which I 16



### will not repeat here but they are in my written 17



### documents. And it is quite clear that what EPA proposes 18



### to do is not directly connected to any adverse health 19



### effect that has been observed in a rat or a human. 20

21



### I would like to close briefly by pointing out another 22



### quote from the September SAP. The introductio n part is, 23



### Members of the September SAP “expressed the opinion that 24



### there doesn‟t seem to be strong evidence of adverse 25



### health effects from atrazine exposures at the levels 26



### found in surface waters; because of this, these Panel 27



### members believed it was unfai r to ask the registrant to 28



### increase their sampling efforts.” We agree. I will try 29



### to answer any questions you might have now. 30

31



### DR. DANIEL SCHLENK : Any questions from the panel. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### SCOTT SLAUGHTER: Thank you very much. 2

3



### DR. DANIEL SCHLENK : Thank you Mr . Slaughter. The next public 4



### commenter will be Jere White from the Triazine Network 5



### and I believe there are several folks involved in that 6



### one. I think there are some slides. 7

8



### JERE WHITE: Good morning Mr. Chairman, members of the panel, 9



### my name is Jere White. I am the executive director of 10



### the Kansas Corn Growers Association and the Kansas Grain 11



### Sorghum Producers Association

. I serve as Chairman of 12



### the coalition that was formed in 1995 somewhat in 13



### response to the initiation of the special review of the 14



### atrazine. The goal of the Triazine Network, since its 15



### formation, was simply to see a scientifically based 16



### conclusion to the special review. We obviously are a 17



### coalition that represents the user community, if you 18



### will. And as such, we obviously have a k een interest if 19



### there are safety issues related to the use of the 20



### product. We represent over 30 commodities grounded in 21



### over 40 states and certainly commodities grounded in 22



### almost every state that has agricultural production, 23



### which is obviously most of th e states in the country. 24

25



### We believe the scientific weight of evidence continues to 26



### show that atrazine is both safe and effective and that is 27



### certainly the kind of tool that a farmer needs to have. 28



### We do look forward to a science based conclusion of th e 29



### review of the use of atrazine on our farms. And it is 30



### not because of their uncertainty with the product but 31



### because of seemingly continuous review of the product has 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### literally surpassed the career of many at EPA; I assume 1



### probably some on the SAP and ce rtainly several of our 2



### growers. In fact, I am wondering if it will surpass my 3



### career as well. This is also, as noted earlier; it is 4



### the 11 th 

### SAP since 2000. Network members have 5



### participated in every SAP since the special review began. 6



### Quite frankly at this point, Joe Bailey and I have 7



### observed a longer relationship than I have with my wife 8



### and I think she is starting to ask questions. 9

10



### JOSEPH BAILEY : You did not need to state that publicly Jere. 11

12



### JERE WHITE : As you know atrazine has been used for som e 50 13



### years by farmers; it has been used by more farmers in the 14



### US than any other herbicide. It is used on over half of 15



### the corn, 2/3 of the sorghum, 90% of the sugarcane. It 16



### is an important product and I think that has been well 17



### established

, but it still bears repeating I guess 11 18



### times since 2000. We use it because it is efficacious 19



### for wheat; it is cost effective; we believe it is safe. 20



### It is also a key tool that farmers use in conservation 21



### tillage and controlling soil erosion. 22

23



### So we are here agai n today, and our sense is that much of 24



### the activist clamor that led to this re

- review post 2009, 25



### has been properly vetted out by the agency and the SAP, 26



### and that we are moving on. However, we simply cannot 27



### disregard some of our specific concerns with cert ain 28



### Agency positions that are being discussed at this SAP. 29



### And that is why we have asked Dr. Lamb to join us again 30



### as he did in 2010. We certainly have shared concerns 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### with the SAP regarding some of these studies and Dr. Lamb 1



### will address those again. 2

3



### We were pleased but not really surprised that the new 4



### version of the Agricultural Health Study adds further 5



### confidence to with the EPA has already established, that 6



### atrazine is not likely to cause cancer in humans and 7



### indeed other organizations and gover nment agencies from 8



### around the world have concluded much the same. 9

10



### In some of the previous discussions on, I guess what we 11



### commonly refer to as the Cooper Study
, there were 12



### discussions about the appropriateness of the strain of 13



### rats, the appropriatenes s of the gavage technique. And I 14



### guess one of the things I took away from the earlier 15



### discussions was this whole issue of solubility and it 16



### seems pretty basic, it is the concept of saturation I 17



### guess is the same concept that we learn as elementary 18



### kids ma king rock candy. You super saturate the liquid 19



### and it forms the sugar crystals. It just seems like a 20



### basic concept that if you cannot get that much product 21



### into the water, then the exposure to humans or normally 22



### even to animals would be through the water and we are 23



### talking about regulatory discussion of water that is kind 24



### of a basic concept. Probably my understanding is limited 25



### to making rock candy, but hopefully Dr. Lamb can help 26



### communicate some of our concerns and I think others have 27



### addressed that. 28

29



### Monitoring results clearly indicates that atrazine 30



### levels, even when they are detected in drinking water, 31



### are extremely low; do not exceed thresholds for human 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### health effects. F inished drinking water, in our opinion, 1



### should be the only water used in dr inking water 2



### assessment, not raw water. This is the same requirement 3



### for all other potential contaminants including many with 4



### known health concerns at levels possible in the 5



### environment, again, not limited by solubility issues. 6



### There is no scientific jus tification to single out 7



### atrazine as being unique or different. 8

9



### In addition, the use of Eco sites such as M issouri O

- 1 10



### for risk assessment is just simply not appropriate . I 11



### believe in past SAPs there has been a lot of pictures 12



### shown of the Missouri O

- 1 si te . One time it was a 13



### construction site and those of you that served for years 14



### on the SAP will remember the pictures of earthmovers in 15



### action. 16

17



### There is simply no basis to assume that you could derive 18



### a minimum safe yield from the se sites, it woul d be 19



### appropriate to site them for community water systems. 20



### There is no reason to believe that M issouri O

- 1 in and of 21



### itself would be appropriate for water supply and 22



### moreover, if you were to consider that you would build a 23



### reservoir . B y doing so you would change the 24



### characteristics of what the exposure pattern would be 25



### from that water. 26

27



### At this point, I would like to have Dr. Lamb share a 28



### review that he continued to do for us on behalf of the 29



### Triazine Network looking at the Cooper work and its 30



### appropria teness for this use. 31

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### DR. JAMES LAMB: Thank you Jere. Some of you, it is good to 1



### see you all again. I appreciate your taking the time to 2



### hear me, really I do. I am Jim Lamb, I am Director of 3



### Toxicology and mechanistic Biology and Exponent and I am 4



### here on behalf of the Triazine Network. I am going to 5



### comment specifically on the use of the Point of Departure 6



### that is proposed, which is the suppression of the LH 7



### Surge in the Long

- Evans rats. 8

9



### There are several major issues; this is going to be quite 10



### di fferent actually, than the last time I spoke where I 11



### got into some of the nuts and bolts of the study. This 12



### is more about the science policy and the use of this 13



### endpoint and the use of the Long

- Evans rat, the bolus 14



### dose, the LH surge for risks assessment purposes, which 15



### is really an important part of your charge. Should the 16



### reduction in LH be treated as an adverse effect? And I 17



### have got some bullets here but I am going to go into them 18



### more detailed further in the study, so I am not going to 19



### read them to you now. 20

21



### I would contrast the study with the typical risk 22



### assessment study and the studies that already exist on 23



### atrazine, for which we all know there is a huge database. 24



### Specifically, this particular study, meaning the Cooper 25



### Study on the LH surge, i t is an unusual selection of 26



### animals in this study design in order to measure very 27



### specifically effects on the LH surge. This was designed 28



### by Dr. Cooper for a specific mode of action purpose; it 29



### was not really designed to be a risk assessment study and 30



### yo u can see the way he designed and conducted the study 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### that that really was not the intention of this study. 1



### And for many reasons I do not believe it is appropriate. 2

3



### It is a collection of three blocks of animals based on 4



### several requisitions of animals over a course of a year. 5



### It is a large complex study; it involved gavage 6



### administration for four days so that they could very 7



### precisely evaluate

, in a subpopulation of animals

, a 8



### change in the LH surge. And it required a group of very 9



### precise selection criteria. There is in addition, a very 10



### precise two

- hour window in that surge, and you can see 11



### from his data how this is set up. It is not a 12



### conventional design; it is not validated; I do not expect 13



### as a study design there is any need that it ever would b e 14



### validated. But I think some form of replication is 15



### critical if it is going to be used in a risk assessment. 16



### And for many reasons I do not believe there are serious 17



### issues with waiting to see that replicated, if indeed it 18



### is going to be used. And I wil l talk too about some of 19



### the questions about whether or not it even should be used 20



### for risk assessment. 21

22



### I mentioned exclusion criteria... basically this study 23



### protocol call ed , at the beginning, for about 1000 24



### animals; of which 359 were used. And the exc lusion 25



### criteria, first and foremost was if the animals did not 26



### have a regular 4

- day estrous cycle over the course of a 27



### couple of week, two or three weeks, they were not to be 28



### used in the study. So more than half of the animals or 29



### about half of the animals were eliminated from that 1000 30



### at the very beginning of the study. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Then at the time of kill, after the 4

- day dosing and the 1



### collection of tissues and samples and measurement of 2



### hormones, three additional criteria were applied. Did 3



### the animal have a pro estrus smear; was there an increase 4



### in uterine weight, beyond a half of gram; was there 5



### elevated progesterone ? All of these had to be satisfied 6



### to include the animals in his evaluation. So you go from 7



### 1000 to approximately 500

– I will have the numbers i n 8



### just a second ; a nd then from that 500 to 359 on that 9



### second set of criteria. Again, this is after four days 10



### of bolus dosing and he did not dose the animals that did 11



### not have a regular cycle. And then sample collection was 12



### every two hours you could not use an animal more than 13



### once because you were killing them every two hours. 14

15



### I apologize for the size of the numbers on here, but this 16



### is a listing, by requisition, of the animals in the 17



### study. Go to the bottom line where it says total; there 18



### are 861 a nimals that we could identify in the information 19



### o n the docket. The protocol call for 1000 but I never 20



### could figure out exactly how many animals started in that 21



### last group. And also could not tell how many were 22



### excluded after dosing. So there are some q uestion marks 23



### here that you need to be aware of. So this numbers, 24



### especially the 861, is the total end is low. There are 25



### other animals because ultimately out of that group 31 26



### were used, which you can see in the last group. 27

28



### So you have total number yo u start with, followed by how 29



### many of those actually had the 4

- day regular cycle and 30



### how many then were excluded after four days of gavage 31



### dosing and necropsy. So after the data is in hand, how 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### many did you then excluded and the total number included 1



### at t he end, that we could calculate, was 359 animal. 2

3



### It is an extreme design for a very specific purpose, and 4



### that is to answer questions particularly about Long

- Evans 5



### rats. Dr. Cooper has done a tremendous of important work 6



### on atrazine and Long

- Evans rat s and his hypothesis, as I 7



### understand it, was to explore that mode of action. So 8



### this had a very particular design. But one thing that 9



### happen ed is, by removing animals after the data are 10



### collected, you are eliminating some of the variances in 11



### the study. The variance is still reasonably high in the 12



### included animals but if you

, again, before you yell at me 13



### that this is unreadable, I am going to pull out part of 14



### this slide. What this is, is this is each of the seven 15



### groups, control and six treatment groups from the study 16



### and what are called exclude d animals. These are excluded 17



### after dosing; this does not include the animals, which 18



### were eliminated for lack of an estrous cycle. 19

20



### T hen
, included animals are on the last chart. I am going 21



### to just show you th e control data from this and since you 22



### have the entire chart in the file, you can look at it at 23



### your leisure, which I am sure you will enjoy doing. You 24



### can see that the times for collection were

– I guest 25



### Ralph calls it “rat time”

– 1200, 1400, 1600, 1800 and 26



### 2000. And you see the variance in the animals excluded. 27



### Again, these are excluded after they have collected the 28



### data. 29

30



### So he has LH numbers on these but they did not meet his 31



### criteria. Most of the animals were eliminated because 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### their uterine we ight was below a half of gram. The other 1



### two criteria really came into play much less often. But 2



### you can see the variance in looking at the standard 3



### deviation versus the mean; in the included animals, it is 4



### much lower. If he had had to include these oth er 5



### animals, which he had removed for a purpose and through 6



### criteria, the variance would have been much higher. So 7



### you have a really well selected subpopulation of a 1000 8



### animals. 40% of those animals

-- less than 40%

-- 35% 9



### ended up being used in this st udy. So this is not a 10



### study that represents even the entire population of Long

11



### Evans rats, much less other rats or humans, for various 12



### reasons. 13

14



### I do not believe this study is really designed to set a 15



### point of departure. I also think there are serious 16



### problems with the bolus exposure to these animals and the 17



### precisely timed sampling if you want to use this for risk 18



### assessment purposes. Other studies support the use of LH 19



### suppression as an endpoint, but probably at higher dose 20



### levels or longer exposure . There are various effects, 21



### vaginal opening, preputial separation, and other effects 22



### that indicate that some effect on LH may be a sentinel 23



### effect. I am not sure that the effect on LH surge in the 24



### Long

- Evans rat though is a good sentinel effect for a 25



### hu man risk assessment. 26

27



### This really repeats the point just made that you can link 28



### LH suppression

, but probably the pulsatile LH suppression 29



### to adverse effects. The mechanism is really not that 30



### well sorted out at this point but on water exposure and 31



### solub ility, an issue that has come up several times , t his 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### chart shows a line and that is the limit of solubility, 1



### thirty parts per millions, of atrazine in water. And the 2



### reason you cannot do a drinking water study is because 3



### the top dose is actually right abo ut where the current 4



### point of departure is, two and a half milligrams per 5



### kilogram per day. That does not even consider whether 6



### they are palatability problems or other reasons that they 7



### would not consume this water. So that is the highest you 8



### could go, t heoretically it may be higher than you really 9



### could go in running the study. So we are sort of trapped 10



### back into either dietary or gavage studies. 11

12



### As far as mode of action, the mode of action for the LH 13



### surge was described really well yesterday and it is 14



### dramatically different in the Long

- Evans rats compared to 15



### humans. In rats atrazine does affect, in Long

- Evans 16



### rats , the pre

- ovulatory

-- and probably Sprague

- Dawleys 17



### as well

-- the pre

- ovulatory surge of LH, by blocking 18



### GnRH secretion in the hypothala mus. Ralph has shown this 19



### in his Long

- Evans rat studies; I think this is very real; 20



### it is true for the Long Evans rat. That surge occurs 21



### over about two hours. But it does not alter the ability 22



### of the rat pituitary to respond or to produce LH; it 23



### really is a hypothalamic effect. And the in vitro study 24



### shows that atrazine does not seem to affect the response 25



### of the pituitary to GnRH. 26

27



### Now, effects of atrazine then for the GnRH surge

, appear 28



### to originate in the hypothalamus. In humans though, that 29



### is n ot really relevant. The pre

- ovulatory surge, first 30



### of all, is two or three days not two or three hours. It 31



### is not triggered by GnRH surge. You have pulsatile GnRH 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and estradiol positive feedback have been identified as 1



### resulting in that surge of LH. Th e atrazine exposure 2



### that inhibits the LH surge in certain strains of rats, 3



### whether it is Long

- Evans
, but not Fischer 344 , b asically 4



### this is not relevant to other strains rats and this mode 5



### of action is not relevant to humans. 6

7



### Again, the timing in this study was very precise; it was 8



### gavage. You saw pictures of basically, even when you 9



### look at DACT, the saw

- tooth pattern of daily gavage on 10



### the concentrations of DACT in these animals. It is not a 11



### steady state; it is not even really much of a pseudo

12



### stead y state. It is highly variable numbers based on 13



### daily gavage; they go up, they go down fairly quickly. 14



### Using the bound atrazine as noted by Harvey Clewell and 15



### the information he showed changes dramatically how steady 16



### you think this pseudo

- steady state ma y be. 17

18



### Also, human drinking water exposure is not like gavage. 19



### It is not modeled well by gavage; it includes many use s 20



### of tap water intake throughout a given day. It is not a 21



### single dose for most of us. Temporal considerations that 22



### I think are also imp ortant are

– dosing is daily, but we 23



### are talking about through the 4

- day cycle. It was not 24



### four days necessarily because of the cycle; it was again 25



### coming back to that pseudo

- steady state as I understand 26



### it. But they did treat for the 4

- day cycle and if it 27



### were relevant to humans, it should be compared to the 28

- 28



### day human cycle. 29

30



### When you look at an effect on a two

- hour surge, well the 31



### LH surge is 48 hours, so if you are comparing the timing 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### of the effects you need to make some adjustments. 1



### Really, th e 4

- day study may relate better to a human 28

- 2



### day exposure. But susceptibility is really depend ant on 3



### the mode of action, and they are different between rats 4



### and humans. Humans are unlikely to be susceptible to 5



### changes in the GnRH surge. Typically, in a conventional 6



### risk assessment we are going to use a no observed adverse 7



### effect level or a lower confidence of a benchmark dose, 8



### or some equivalent number in a guideline study. But 9



### mechanistic studies do play a significant role in risk 10



### assessment. They ty pically do not involve the selection 11



### of a subpopulation, which this study does. 12

13



### The re are various endpoints relevant to adverse effects 14



### that have been studied over the years for atrazine . A nd 15



### no observed adverse effect levels have been established. 16



### I n the end, the design of this study limits its 17



### usefulness in risk assessment; it was done for a very 18



### particular scientific purpose, and he answered his 19



### question. But such changes should not be treated as 20



### adverse effects relevant to humans. Other data are 21



### really already there that are more important for the 22



### atrazine risk assessment, but if EPA is going to regulate 23



### on such an unusual research study, it really needs to be 24



### independently replicated. That there is time to do this 25



### in that all the margins

– we d o know, you heard from 26



### Syngenta, you heard from EPA, the margins of exposure are 27



### sufficient. If you need to repeat or replicate this 28



### study, there is time and there are mechanisms by which 29



### EPA can demand that the study be done, and I have had 30



### great experie nce in the past working with Dr. Mendez and 31



### Dr. Cooper and others on unusual study designs for 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### regulatory purposes. There are ways to get these 1



### repeated if this is an endpoint that really is going to 2



### be used for risk assessment. With that, I will conclud e, 3



### pass it back to Jere, or answer any questions. Thank 4



### you. 5

6



### DR. DANIEL SCHLENK : Do you have any further comments Jere? 7

8



### JERE WHITE : No. 9

10



### DR. DANIEL SCHLENK : Any questions from the panel? 11

12



### DR. PENELOPE FENNER

- CRISP : Okay Jim, so if you were tasked t o 13



### do the atrazine risk assessment, and you have available 14



### the current dataset that exists, what would you select as 15



### the appropriate dataset and study to derive a NOAEL and 16



### LOAEL or benchmark dose to use at the point of departure? 17

18



### JIM LAMB: Good question, and I think I would rely on vaginal 19



### opening or preputial separation, which have no observed 20



### adverse effect levels point of departure at about six and 21



### a quarter milligrams per kilograms per day. 22

23



### DR. DANIEL SCHLENK : Any other questions? 24

25



### JIM LAMB: Th ank you very much. 26

27



### DR. DANIEL SCHLENK : Thank you. Our next public commenter 28



### will be Sarah Gallo from the National Corn Growers 29



### Association. We also have a handout for that. 30

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### SARAH GALLO: Good morning. My name is Sarah Gallo. I am the 1



### Director of Pub lic Policy for the National Corn Growers 2



### Association, and I appreciate the opportunity to be here 3



### this morning. I am providing comments on behalf of the 4



### National Corn Growers Association, which represents more 5



### than 3600 members in 48 states, and 47 affili ated state 6



### organizations with more than 300,000 corn farmers who 7



### contribute to state check

- off programs across the 8



### country. 9

10



### Our members are proud to be a part of a sector that is 11



### one of the few bright spots in our country's balance of 12



### trade. USDA fore casts agricultural exports to reach a 13



### record $137 billion for this fiscal year

– including a 14



### $44 billion trade surplus, which is the highest it has 15



### ever been. Our corn farmers represent an important part 16



### of these economic strengths. The United States is the 17



### world's largest producer and exporter of corn, and one of 18



### the key inputs that makes that possible is atrazine. 19

20



### For more than 50 years, corn farmers have relied on 21



### atrazine to fight weeds effectively and affordably. It is 22



### applied on well over half o f all corn acres in this 23



### country. By EPA's own estimate, atrazine saves corn 24



### farmers as much as $28 an acre and has reduced herbicide 25



### costs and increased yields. 26

27



### Our confidence in this vital tool for corn farming has 28



### been bolstered by more than 6,000 studies and nine 29



### reviews conducted by the EPA. Just this past May, 30



### atrazine got another "all

- clear" from a comprehensive 31



### study. A new report from the Ag Health Study

- a massive, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### government

- sponsored epidemiological study of 1



### agricultural workers that has been on

- going since 1994, 2



### found no association between atrazine worker exposure and 3



### any form of cancer. 4

5



### This latest report studied more than 57,000 licensed 6



### pesticide applicators from 1994 to 2007. It is just the 7



### latest in a series of studies conducted by governments 8



### and international organizations that have found that 9



### atrazine is not a health risk. In 2007, the World Health 10



### Organization reviewed atrazine and concluded it is "not 11



### likely to pose a carcinogenic risk to humans." The World 12



### Health Organizat ion is so confident of the safety of 13



### atrazine, in fact, that in 2010 it raised its acceptable 14



### drinking water recommendation from two parts per billion 15



### (ppb) to 100 ppb. That's far higher than the EPA limit of 16



### three ppb. 17

18



### Over the past ten years, atrazin e has been reviewed all 19



### over the world, in Britain in 2000

- 2003, Canada in 2004 20



### and again in 2007, Australia in 2008, and the state of 21



### Minnesota again last year. In all of these cases, it has 22



### been favorably reviewed from a human health standpoint. 23



### Of cours e, the EPA itself re

- registered atrazine in 2006, 24



### after a 12

- year review. 25

26



### The safety of atrazine, to people and the environment is 27



### clear. It has been verified by thousands of studies. The 28



### economic importance of atrazine is just as clear. It has 29



### been vouched for by corn farmers all over America. At a 30



### time when so much of the US economy is struggling, we 31



### cannot forget that agriculture is one of the few areas 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### that is competing better than ever ; creating good 1



### American jobs right here at home in the heart land of 2



### America. Rather than do anything that would hurt our 3



### farmers' ability to compete, we should do all we can to 4



### ensure that America's farm exports remain strong in world 5



### markets. Atrazine helps us do that. Thank you. 6

7



### DR. DANIEL SCHLENK : Any questi ons from the panel? 8

9



### DR. KEVIN O’BY RNE : What is your major concern , anxiety ? 10

11



### SARAH GALLO: What is m ine personally? We just want to make 12



### sure that this is a product that our producers are able 13



### to continue to use and just want to convey how important 14



### i t is as an important tool for our growers. 15

16



### DR. KEVIN O’B YRNE : So where is the stumbling block? What is 17



### causing the anxiety in your members? 18

19



### SARAH GALLO: I think just the concern that there would be 20



### something that would prevent them from using the pr oduct. 21

22



### DR. KEVIN O’BYRNE: Coming from what source? 23

24



### SARAH GALLO: Nonscientific data or unwarranted concern. 25

26



### DR. KEVIN O’BYRNE: Is that from government agencies or is 27



### that just... 28

29



### SARAH GALLO: I am not entirely sure, I can... 30

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### DR. KEVIN O’BYRNE: Or is it from anxiety within the general 1



### population that have little or no understanding of what 2



### goes on in the fields. 3

4



### SARAH GALLO: Well, sir, yes of course that is a concern of 5



### our, that people are misinformed. 6

7



### DR. KEVIN O’BYRNE: So does your organizati on do anything to 8



### educate the general public? 9

10



### SARAH GALLO: Yes, absolutely. 11

12



### DR. KEVIN O’BYRNE: What is the nature of that? 13

14



### SARAH GALLO: Both nationally and within all of our state 15



### organizations, Jere being one of them, we certainly have 16



### public outrea ch campaigns to education people about corn 17



### farming, about kind of the modern practices that our corn 18



### farmers have adopted to reduce herbicide use and 19



### transform their practices to be both economically and 20



### environmentally beneficial. 21

22



### DR. KEVIN O’BYRNE: Th ank you. 23

24



### SARAH GALLO: I have no personal anxieties

– I‟m good. 25

26



### DR. DANIEL SCHLENK : Thanks Ms. Gallo. Any other questions 27



### that relate to the panel charge questions? Let me ask 28



### that. Any questions related to the charge questions we 29



### have been given? O kay. Thank you very much. Our next 30



### public commenter is Tyler Wegmeyer from the American Farm 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Bureau Federation. And we do have a handout as well for 1



### this. 2

3



### TYLER WEGMEYER: Good morning everybody. My name is Tyler 4



### Wegmeyer and I am Director of Congress ional Relations for 5



### the American Farm Bureau Federation. I am also a fourth 6



### generation farmer, growing mostly specialty crops in 7



### Western Loudoun County, Virginia. 8

9



### The American Farm Bureau Federation is the country's 10



### largest general farm organization. Farm Bureau members 11



### grow, produce and raise the food and fiber and energy 12



### sources that feed, clothe and fuel the U. S. and the 13



### world. Our farms and ranches are found in all 50 states 14



### as well as Puerto Rico, and we represent producers of 15



### every size and sca le of operation. 16

17



### The American Farm Bureau Federation welcomes this 18



### opportunity to speak to the benefits of atrazine and what 19



### it means to the American farmer. Having access to 20



### important crop protection products is vital to the 21



### success of providing a sa fe and abundant food supply. I 22



### appreciate this opportunity to be able to express our 23



### views before this Scientific Advisory Panel. Atrazine has 24



### been in use for more than 50 years and has proved to be a 25



### safe, valuable and a cost

- effective herbicide that 26



### far mers across the country use to manage the spread of 27



### weeds that rob crops of nutrients. 28

29



### Today, US farmers safely and successfully use this 30



### herbicide on over 50% of co rn , 90% of sugar cane and two

31



### thirds of sorghum acreage. Co rn is a base commodity for 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### inumerab1e food products, and co rn and sorghum are key 1



### feedstocks. If these sectors are undermined, the 2



### repercussions would be felt throughout the US food 3



### industry, including weakening the economic health of the 4



### America's farmers and ranchers. No degree of economic 5



### dependence would matter if atrazine were a problem, but 6



### it's not. We believe sound science shows it to be safe 7



### for use. 8

9



### Atrazine has been the subject of intense scrutiny since 10



### it has been on the market and has been the Subject of 11



### eleven SA Ps since the year 2000 by the E PA

. R ecently, as 12



### you know, the Ag ricultural Health Study, a large 13



### government

- sponsored study of agricultural workers

, going 14



### on since 1994, found no association between atrazine 15



### worker exposure and any form of cancer. 16

17



### In addition, the World Health Organization raised its 18



### acceptable drinking

- water recommendation from two parts 19



### per billion (ppb) to 100 ppb, far higher than the EPA 20



### limit of three ppb. Atrazine has been examined by the 21



### international organizations and countrie s including the 22



### World Health Organization, the United Nations Food and 23



### Agriculture Organization, the governments of Great 24



### Britain, Canada and Australia, and the state of 25



### Minnesota, which have all deemed it safe for use. 26

27



### The American Farm Bureau Federat ion has participated in 28



### every scientific advisory panel convened to examine 29



### atrazine's safety since the first special review in 1994. 30



### More than 6,000 studies on atrazine have been 31



### commissioned since its introduction to the market, and it 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is one of the mos t complete scientific databases of any 1



### crop protection product. Our members look at EPA's 2



### recent actions with dismay and frustration. Farmers are 3



### deeply concerned that this process will result in an 4



### unjustified restriction or elimination of an important 5



### crop protection tool. 6

7



### At a time of continuing high unemployment, and enormous 8



### trade deficits

, agriculture is providing a much needed 9



### bright spot in our economy. And yet, we find ourselves 10



### fighting off ill

- considered proposals, such as the one 11



### before t his panel, that have the potential of making 12



### farming more difficult, less efficient and more 13



### expensive. 14

15



### We hope that this atrazine review process is not being 16



### subjected to an unseemly rush to take unwarranted action 17



### and we urge that you ensure that the principles of sound 18



### science remain our way forward. Again, we appreciate 19



### this opportunity to submit our comments. Thank you. 20

21



### DR. DANIEL SCHLENK : Again, any questions that relate to our 22



### charge questions. 23

24



### DR. HEATHER YOUNG : I just want to comment sinc e this is the 25



### second public commenter that has made the comment about 26



### the Ag Health Study ; have you reviewed the 2011 Beane

27



### Freeman study that show the four

- fold increase risk with 28



### thyroid cancer? Because, you are stating here that they 29



### are showing no ass ociation with any forms of cancer and 30



### we have the 2011 study that shows us the four

- fold 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### increase risk with thyroid cancer

. I am wondering what 1



### your thoughts are on that ? 2

3



### TYLER WEGMEYER: Thanks for bringing it up. I have not looked 4



### at that specifically but I will. 5

6



### DR. DANIEL SCHLENK : Any other questions? Thank you

, Mr. 7



### Wegmeyer. The last public commenter that I have on my 8



### list is Stephanie Whalen from the Hawaii Agriculture 9



### Research Center. I believe she has a couple of slides. 10

11



### STEPHANIE WHALEN: My name is Stephanie Whalen. I am the 12



### Executive Director of the Hawaii Agriculture Research 13



### Center, and some of you may be wondering

, what is someone 14



### from Hawaii doing here. And so I thought I would put 15



### that a little in perspective. 16

17



### HARC, our organ ization is over 100 years old. It is a 18



### private agricultural organization that supports 19



### agriculture in Hawaii. It began with a dominant 20



### agriculture product of sugarcane and then pineapple

, 21



### along came coffee, macadamia nuts, papaya and now more 22



### vegetable p roduction. Currently we have very little 23



### sugar left and our work is involved with the diversity, 24



### which includes those that I named, plus herbs, se ed 25



### products, cac a o tea, et cetera. 26

27



### O ur organization has been focus on scientific based 28



### information and te chnologies to transfer to our client, 29



### essentially the farmers in Hawaii. W e have been 30



### delivering that type of information and it has been very 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### science

- based . We are an organization that is very focus 1



### on science

- based information. 2

3



### My personal responsi bility

, throughout my almost 40 years 4



### with the organization, has been a background in pesticide 5



### residue work and I was around at the beginning of EPA 6



### when it was transferred over from HEW , a nd was involved 7



### in their original training operations. So that is where 8



### my background comes from
, basically pesticide residue 9



### work, which then involved working with all the chemical 10



### manufactures throughout my last 40 years. 11

12



### I also then was responsible, as EPA developed in more 13



### regulatory areas in air, water, clean w ater act, safe 14



### drinking water act, non

- source pollution and then 15



### chemicals with pesticides, and manufacturing them, 16



### basically because the sugarcane industry was vertically 17



### integrated from the field to the table , s o all those 18



### regulatory statues affected ope rations. T hat has been my 19



### history in terms of why I am here. 20

21



### I t is very obvious why I have been involved in the 22



### atrazine process; because of my history and my 23



### responsibility to the industry in Hawaii. And so I have 24



### been involved in all of the SAPs, I believe, except one. 25



### I provide the comments for

-- I think it was the 1988

-- 26



### where the special review was first announced by EPA, and 27



### they asked for comments and got over 80,000 comments for 28



### that. I think that was the highest in their history up 29



### to tha t point. 30

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### A little bit about sugarcane in Hawaii , we were a 250,000 1



### acres in its history; we are now down to 40,000 acres. 2



### Partly or mainly due to the stable price for the last 3



### three decades while the input cost increased over that 4



### time, and regulatory being just one of those cost and 5



### atrazine being a major concern. 6

7



### In Hawaii, we estimate there is about 10% loss on 60% of 8



### our acres if we were to lose atrazine; that works out to 9



### be $130 per acre or about $2.3 million. Using Hawaii‟s 10



### numbers and then take that across the nation to 11



### Louisiana, Florida and Texas; their cost would be about 12



### $280 an acre and they are looking about a $90 million 13



### loss if we lost the use of atrazine. O ne reason of why 14



### there are more restrictions maybe the manufacture would 15



### sa y , Okay, we are going to just get rid of the sugarcane 16



### t olerance or the ability to use it for sugarcane because 17



### corn and sorghum maybe higher and therefore, we will give 18



### the agency sugarcane and that is why we have been at the 19



### table from the very beginning with the manufactures also, 20



### making sure they save our use as well as the more major 21



### uses. 22

23



### And just to let you know that as new chemistry are found 24



### we, part of our role has always been testing all of the 25



### new chemistries for the industry in Hawaii, and so far we 26



### have always had to add and most of the new products have 27



### a little bit of atrazine still left in them to make them 28



### at least equivalent to the regular effective use of 29



### atrazine. There just has not been one that came along 30



### that could totally substi tute for it. 31

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### I was going to talk a little bit about the Agriculture 1



### Health Study, but I think you have heard enough about 2



### that so I am not going to do that. So I will look at 3



### that first slide, because the National Corn Growers 4



### Association and the Farm Bureau talked about other 5



### countries and I thought it might be useful for you to 6



### have that in a table format, and so there it is. It is 7



### just put in a nice format that you can look at to see 8



### what the other countries have done about atrazine. 9

10



### Then the b ottom row there is for the water levels. Just 11



### to emphasis those; in Europe it is 14 parts per billions, 12



### that is a health

- based standard; Australia 40 parts per 13



### billions. And institutional research center there is not 14



### applicable; they do not set that. US EPA has the 15



### lifetime MCL at three ppb. And I was very involved in a n 16



### early period b efore that and it was 25 parts per million

. 17



### I t was a health advisory a nd we happen to have an area in 18



### our state that was close to three and so we voluntarily 19



### stopped the use of that compound in that particular area 20



### because there was this concern which was not fully 21



### fleshed out that three would be the new level set, which 22



### it eventually was. Though we did not hit the three; we 23



### were always at two and went down from there, bu t we are a 24



### very conservative industry when it comes to environmental 25



### issues. 26

27



### A lso under the US EPA they have the DWLOC of 12.5, which 28



### is regulated under now to 68 parts per billion. World 29



### Health Organization, which was pointed out already, went 30



### from t wo from prior to 2010 to now 100, based on the same 31



### data that is being reviewed here. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So my next slide, I just out of curiosity did a little 2



### calculation based on some of the data that has been 3



### presented in the last couple of days. Anyway, so I did a 4



### c alculation for the 2.56 milligrams/kilograms/day which 5



### was the number that came out of the Cooper Study, and 6



### converted it to ppm in water for adult females, 60 7



### kilograms instead of the 70 kilograms male and then the 8



### consumption rate of 2 liters per day. 9

10



### I f you put those numbers in

-- and then for the 11



### uncertainty factor on the bottom there

-- that is the ten 12



### times ten for the standard intra and interspecies safety 13



### factors. T hen three has been talked about here for the 14



### FQPA number and then the two liters per day. And you 15



### will get a level of 256 parts per billion and it is my 16



### understanding is we have see n some of the monitoring 17



### data, which we did some of ours ourselves very early on, 18



### no numbers have even come near that. I think the highest 19



### in the communi ty water system is something like in the 20



### high 60‟s to 70‟s. 21

22



### The only other thing I wanted to say was that since I do 23



### really have a long history with EPA in terms of just 24



### paying a lot of attention to regulations and statues that 25



### are done by C ongress, I wanted to express the agriculture 26



### community‟s appreciation of the deliberative and 27



### transparent and open process that now allows dialog and 28



### input from all of the stakeholders. 29

30



### Now really almost previous to the atrazine thing, the 31



### growers just sat back a nd let the EPA, the Agency and the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### registrant just do their thing and come out with the 1



### numbers and then we followed the labels. But, in the 2



### atrazine, it was really hitting many of the growers hard 3



### in that they had worked with this compound 50 years

-- or 4



### back then it was probably only 40 years or 30 years, 5



### since we have been doing this for almost two decades

-- 6



### a nd felt that, gee they are really the first target of 7



### any toxicity that comes about. S o they were very 8



### concerned about this and wanted to follow the process a 9



### whole lot more than we had in the past. 10

11



### So we are pleased to be able to be at the table as a 12



### stakeholder in this process and we are glad that the 13



### process has developed to that, because that is not where 14



### it was before. So we recognize th e hard work and long 15



### hours everybody involved has put into the regulatory 16



### process, including yourself, and regardless of the topic, 17



### not just about pesticides but all the environmental 18



### statu tes

. And we appreciate that through the open 19



### process the Agency ma y often feel like a bull‟s eye, 20



### which everyone is taking shots at. And surely we have 21



### heard some of that this morning but all of you are 22



### scientists, you go to the conferences and workshops and 23



### that is where we have dialog and we are able to talk 24



### about exp erimental designs and the rest of it , a nd this 25



### is really the process that is set up for regulatory 26



### things, which does not allow that same kind of stuff that 27



### the scientists do. And so unfortunately this is the way 28



### that we can have scientific discussion and although it 29



### may be difficult sometimes, you feel that people are 30



### being critical unfairly , u nfortunately, this is the 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### process we have and we are glad that we have some 1



### process. 2

3



### So again, I want to express the growers‟ gratitude to you 4



### folks and to the Agency that opens up the process for 5



### input. In the end, we believe that we will get to a fair 6



### and reasonable policy and safe and effective pesticide 7



### use that is based on science. Thank you. 8

9



### DR. DANIEL SCHLENK : Thank you. Any questions, clarification? 10



### Thanks. This concludes our public commenting period and 11



### I would like to thank each of the participants in that 12



### for coming forward with their comments. At this point in 13



### time what we would like to do before the break, if 14



### possible, if we could have the age ncies come forward . W e 15



### mentioned yesterday that we would have them come forward 16



### for those of you that have any questions that sort of 17



### came up over the evening from the plethora of 18



### presentations that took place yesterday . And, give you 19



### guys the opportunit y to ask one final sort of batch of 20



### questions or clarification if you had any. So I thought 21



### it would be good before we got into the charge questions 22



### that we could ask any questions or clarification if 23



### anything came up through some of the oral presentation s. 24

25



### DR. HEATHER YOUNG : I think the epidemiology group would just 26



### like some clarification to make sure that we are on the 27



### same page. One of the charge questions that we are being 28



### ask is to look at the descriptor for the cancer risk 29



### assessment and so last night we looked online and we 30



### found that using the 2005 classification. And so I 31



### wanted to make sure that our choices would be inadequate, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### not likely, suggestive; are those the categories that we 1



### are making recommendations as to? 2

3



### DR. ELIZABETH MENDEZ : W ith regard to cancer classification 4



### within the Agency, that is indeed how we do it, 5



### suggestive, not likely, et cetera. 6

7



### DR. HEATHER YOUNG : Okay. Thank you. 8

9



### DR. DANIEL SCHLENK : Dr. Greenwood... 10

11



### DR. RICHARD GREENWOOD : I wonder if you could give me a litt le 12



### bit of help on some of the pharmacokinetic data because I 13



### have not been able to get hold of some the original 14



### reports. It is just about the methodology, if you could 15



### just help me. I wonder can you tell me whether when they 16



### measured the total radiolabe ling in the plasma, was that 17



### just taken at spinning down the red cells and then 18



### combusting the plasma or was it whole blood? 19

20



### DR. CHESTER RODRIGUEZ : Yes, that is my understanding. So the 21



### cellular component of blood like it was removed, like it 22



### was spin d own , like you said

, to actually isolate a 23



### plasma component. I should also mention that the 24



### Simoneaux 1995 study that you requested it was sent to 25



### Joe Bailey so he should be able to provide that. 26

27



### DR. RICHARD GREENWOOD : Thank you for that because I think 28



### interpreting the data, the methods that we used from the 29



### fraction that was actually counted I think you will 30



### realize there is a big difference. 31

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### DR. DANIEL GRIFFITH : For the monitoring group, why did you 1



### choose GEOEAS for your semi

- variogram modeling? 2

3



### DR. NELSON THURMAN : This is Nelson Thurman. I am going to 4



### let Jim Hetrick who used GEOEAS come up and explain why 5



### he chose GEOEAS. 6

7



### DR. JAMES HETRICK : It's a simple answer actually. We used it 8



### because that is the software package we had available. 9



### How is that? 10

11



### DR. DANIEL SCHLENK : Any other questions or clarification. 12

13



### DR. KEVIN O’BYRNE: I just have one, yesterday you were 14



### talking about the pseudo plasma steady state levels ; in 15



### the rat it is four days and it has a 4

- day cycle and it 16



### takes four da ys of atrazine to reduce LH secretion. Then 17



### in the human, it takes 28 days and they just happen to 18



### have a 28

- day cycle. It all seem terribly simplistic to 19



### me. Is that because women are bigger than rats? It is 20



### body weight that leads to that? 21

22



### DR. CHESTE R RODRIGUEZ : Basically, the 28 days comes from a 23



### range of values. For a human body weight of 60 24



### kilograms, we came up with an estimate that ranges from 25



### 21 to 30 days based on allometric scaling or the rat 26



### elimination rate constant. So we decided to just use the 27



### value within that range and it just makes sense to use 28



### 28, which just happens to be the human menstrual cycle. 29



### So that was our thinking. But it was a range it was not 30



### 28 days exactly. 31

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### DR. KEVIN O’BYRNE: Yes, but in your slide you had 28. It's 1



### just terrible emotive. If we turn the clock back and 2



### think about the mammoths, assume they are like elephants; 3



### then what would you predict for them? 112 days? 4

5



### DR. CHESTER RODRIGUEZ : The scaling that we have done is based 6



### on body weight, and that is the best information we have 7



### available. In the absence of specific human information, 8



### that is the best choice we have. 9

10



### DR. TRAVIS JERDE : This question is for Dr. Cooper, regarding 11



### mechanism of action. It seem most of the research has 12



### been on luteinizin g hormone and some on GnRH, and yet 13



### there is also affects on prolactin and the description 14



### has been that we have differing modes of action 15



### potentially. But one could also imagine that there would 16



### be a single or similar mode of action at the molecular 17



### leve l. I am wondering what kind of studies are being 18



### undertaken or proposed to look at signaling mechanisms or 19



### imprinting mechanisms, changes in DNA, things of that 20



### type that might help us assess more subtle effects 21



### particularly in the low dose range that see m to be 22



### overpassed in a lot of these studies. 23

24



### DR. RALPH COOPER : There have been a number of them 25



### undertaken, not by us but by different laboratories, both 26



### in academia and elsewhere. And we still get bits and 27



### parts
, but I can speculate a little bit on the 28



### suppression of prolactin by atrazine. 29

30



### It is curious that in the ovariectomy estrogen

- treated 31



### animal you can see a clear affect on prolactin 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### suppression. I t is also clear that prolactin regulation 1



### during nursing, there is an effect. T he reason tha t we 2



### even evaluated it, at the time I was reviewing a 3



### manuscript depicting the unique control of prolactin 4



### during lactation. However, when you go back into the 5



### cycling animal it is difficult for us to see

-- under 6



### this condition that we have examined prol actin

-- to see 7



### changes in the intact animal prolactin release. 8

9



### Then the last part of that question is if there is a 10



### common mechanism. The one thing that we see consistently 11



### in the brain

-- although I am not a big believer in the 12



### catecholamines drivin g any of this

-- is under the acute 13



### experiments anyway, there is an increase in dopamine. 14



### T hat one possibility would be that it could influence 15



### GnRH neuronal activity, especially at the axonal level 16



### for the GnRH neurons , and then also of course dopamine 17



### b eing a prolactin inhibiting factor. 18

19



### I am not aware of other studies looking into that. We 20



### are in our lab looking at other peptides in those things 21



### but we have limited resources. 22

23



### DR. PENELOPE FENNER

- CRISP : I guess this is for Dr. Rodriguez, 24



### since y ou were the one that raised the issue about the 60 25



### kilogram person; what was the selection criterion for 26



### that? 27

28



### DR. CHESTER RODRIGUEZ : None actually , it was just a typical 29



### body weight that we selected . B ut the good thing is that 30



### you can use any body w eight that you think is appropriate 31



### for an adult human. It was just arbitrary. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. PENELOPE FENNER

- CRISP : Once upon a time, it was estimated 2



### that the average female weighed about that, but if you 3



### look at the CBC data and the recent NHANES data, the 4



### av erage female in the US now weighs 74 kilogram. So the 5



### question becomes if you used the current average female 6



### as your sentinel for determining a number, it may not be 7



### 28 days anymore. 8

9



### DR. DANIEL SCHLENK : All right, well thank you. We will go 10



### ahead an d take a break now and begin the charge questions 11



### after the break; let‟s be back at 10:30. 12

13



### DR. DANIEL SCHLENK : Everybody please take a seat. We are 14



### going to get started on our 14 questions. Before we get 15



### started, I think Dr. Fowle has a few comments. 16

17



### DR. JACK FOWLE : Yes, I just wanted to just kind of review the 18



### biding for the purpose of the Scientific Advisory Panel. 19



### I admit I could be reading this wrong

, but my sense of 20



### hearing some of the comments we heard this morning is 21



### basically that we are pres enting with you a final risk 22



### assessment. 23

24



### I just wanted to note that we are not coming to you 25



### today, to the Scientific Advisory Panel, and not sharing 26



### with the public, frankly, because we do not have it yet, 27



### this is not a final risk assessment. It is n ot even a 28



### preliminary risk assessment. We will not have a 29



### preliminary one until late 2012 or 2013. 30

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### What the purpose of this is to come to the Scientific 1



### Advisory Panel and share with you some of the conclusions 2



### we are coming to ; s ome of the methods an d models that we 3



### will be using and these will be inputs into the risk 4



### assessment that we will come up with. So we are coming 5



### to you to try to get your scientific advi c e and guidance 6



### as to our thinking; are we on the right track, or are 7



### there other things that we should be considering what you 8



### view as the tools; the strengths and weaknesses of tools 9



### and models and the types of endpoints we are thinking 10



### about right now. 11

12



### A lso
, with respect to the epidemiology, we are really not 13



### asking for a judgment of th e overall epidemiology risk. 14



### Basically what we are doing is saying, in terms of 15



### thinking about the considerations we have that go into 16



### our evaluation of the various studies

, and think about 17



### how we might come to an overall judgment of the 18



### epidemiology data ; also
, more importantly

, how we might 19



### integrate that with the toxicity information to come up 20



### with an overall weight of evidence approach. 21

22



### We have tried to share with you

, as best we could
, what 23



### our thinking is, our line of reason, our logic and that 24



### kind of things. We would like your feedback on that. 25



### Also, to the extent that we are trying to move

-- as some 26



### of you heard in May

-- we are trying to move more towards 27



### implementing the toxicity test ing in the 21 st 

### century
, 28



### " Approach to T oxicity ". We me ntioned it would not happen 29



### fully for 15, 20, perhaps more years, but we try to do 30



### this incrementally as we went along. 31

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### We are using an adverse outcome pathway as a basis to try 1



### to lay out what we know, however much or however little 2



### in terms of toxici ty, kind of use that as a framework. 3



### So we have given you

, as best we could
, what we know 4



### about atrazine in that context. So if you could give us 5



### feedback about that as well, that is the kind of thing 6



### that we are looking for in these charge questions, no t a 7



### risk assessment, per se. 8

9



### DR. DANIEL SCHLENK : Thank you very much. With that we will 10



### go ahead and start the reading in of the questions and as 11



### we discussed, if it is okay with you guys we are just 12



### going to read the letters of the questions rather tha n 13



### the whole question. Nelson, you are going to read the 14



### questions. 15

16



### DR. NELSON THURMAN : Given the example dataset, we presented a 17



### matrix approach for deriving bias factors. So the 18



### questions we have related to that approach. 1. a) Given 19



### that the factors are likely to vary based on watershed 20



### size and water

- body type, please comment on the level of 21



### detail we would need to develop for that. In other 22



### words, flowing water versus reservoir , and small versus 23



### medium versus larger watershed area. How many datas ets 24



### would we need to analyze to provide a reasonable 25



### representation of a bias factor for each category? Then 26



### part b) Please comment on the advantages and 27



### disadvantages of deriving bias factors based on analyses 28



### of individual sites and years compared to ta king 29



### percentiles of averages across sites and years. 30

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### DR. DANIEL SCHLENK : I guess you guys have the choice of doing 1



### this separately or together. Did you want to separate 2



### them into a and b or did you want to do them both 3



### together? 4

5



### DR. ROBERT GILLIOM : I have it all together. I mean it is a... 6



### b, but it is sequential. 7

8



### DR. DANIEL SCHLENK : Okay, so lead discussant on that is Bob 9



### Gilliom. 10

11



### DR. ROBERT GILLIOM : So at risk of being a bit more boring 12



### because I read this, I would like to get it all down as I 13



### w rote it; so bear with me. 14

15



### As a context for answering this question, the bias factor 16



### approach is probably best viewed as an early step in the 17



### type of systematic process that you show in Figure 22 of 18



### the issue paper, albeit with some different methods in 19



### the different steps. 20

21



### Application of a bias factor to exposure statistics 22



### calculated from simple linear interpolation of sparse 23



### monitoring data is a potential simple and practical 24



### approach to evaluating data from a variety of monitoring 25



### frequencies to get either unbiased or conservatively 26



### high

- biased preliminary estimates of exposure metrics, 27



### depending on how the factor is derived. The approach is 28



### primarily applicable to sites with moderate frequency 29



### monitoring data, such as weekly or biweekly, so that 30



### initial biased sample estimates are more or less in 31



### statistical control. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Quarterly data, for example, would be too sparse for use 2



### for short duration sample estimates. This said there is 3



### not a simple answer to the questions posed, because there 4



### are no t enough data over an adequate range of sites and 5



### years to reliably organize the entire problem. The 6



### reality, as shown by the available calculations of site

7



### year bias factors, is that each individual site has its 8



### own characteristics that govern the adequa cy of different 9



### frequencies. And here are some observations about those. 10

11



### Each site year has a different concentration distribution 12



### compared to other sites that same year and to other years 13



### for the same site. These site to site and year to year 14



### differ ences in the temporal distribution and magnitudes 15



### of concentrations also apply to the specific exposure 16



### statistic of interest, such as a particular maximum 17



### rolling average of 4, 7, 28

- day levels. 18

19



### Both the annual maximum of specific rolling averages and 20



### the temporal distribution of rolling averages, including 21



### total area under the curve for selected intervals, may 22



### turn out to be important. The implication of this is 23



### that focusing only on a bias factor for annual maximums 24



### may not fit all the needs for fut ure risk assessment. 25



### Sparser sampling as compared to the actual population of 26



### interest, for example daily values, results in 27



### uncertainty in estimates and a tendency toward low bias 28



### for estimating high

- end statistics. 29

30



### Bias tends to be low because short

- lived high

31



### concentration events have a higher likelihood of being 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### missed with sparser sampling. Some broad differences 1



### among different types of sites are evident, such as 2



### according to basin size and reservoirs versus streams, 3



### but we really do not have ad equate sample sizes across 4



### the gradients of all these conditions to quantify the 5



### relations with a sophisticated approach. 6

7



### Potential Approaches that could be taken to address the 8



### problem include, and I will just name three. The first 9



### is evaluation of “ relatively homogeneous” groups to 10



### develop a categorical system of bias factors. And this 11



### is the approach that is really referred to in the charge 12



### question. And if there really are useful groups, as 13



### opposed to a continuum of conditions, then

– to give you 14



### a specific answer

– perhaps on the order of 30 sites per 15



### group, each with several, 5

- 10 years, worth of data, 16



### might be the kind of adequacy for approaching on that 17



### level. 18

19



### Reservoirs, however, which account for a large proportion 20



### of the community water supplies, will probably be 21



### difficult or impossible to categorize because of the 22



### highly variable characteristics, such as volume and 23



### residence time, which are not readily attainable. 24

25



### An alternate approach to this categorical one that is 26



### mentioned would be to basically use a regression of bias 27



### versus explanatory variables, such as basin 28



### characteristics and water

- body type, thus expressing bias 29



### as a continuum governed by specific characteristics. 30



### This approach could be promising for at least certain 31



### part s of the problem, such as watershed size for flowing 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### streams, but more data would be needed for multiple years 1



### at selected sites and at additional sites with 2



### intermediate basin sizes. 3

4



### A third approach is a worst case group approach, such as 5



### small basin s, to yield a conservatively high bias factor 6



### for protective screening that then would trigger 7



### monitoring. This could be a practical approach that can 8



### be used now, because we are relatively confident that 9



### flowing water sites with small basins, such as the AEMP 10



### sites and other small

- basin sites, define the worst case 11



### bias factors, both for larger flowing streams and also 12



### probably for reservoirs, at least regarding short

- term 13



### duration concentrations. 14

15



### There are a significant number of community water 16



### supp lies with the watershed size range within the range 17



### of the AEMP sites. A remaining weakness overall for 18



### these approaches is the lack of sufficient multi

- year 19



### data. This is a problem for approaches other than the 20



### worst

- case group approach above, because e xtremes do not 21



### happen every year. So that is the answer to part a). 22



### Should I stop here? 23

24



### DR. DANIEL SCHLENK : Yes, let‟s stop here and we will split 25



### them up. Dr. Coupe... 26

27



### DR. RICHARD COUPE : The only additional comment I have is just 28



### to reemphasize what Bob said was that I do not know that 29



### you could really develop categories of these community 30



### water systems. I think there are enough variables in 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### there that you would have a category of one for every 1



### water system. 2

3



### DR. DANIEL SCHLENK : Okay. Dr. Lee... 4

5



### DR. HERBERT LEE : I do not have too much to add to that, I 6



### largely agree fully. I did want to comment on one thing 7



### that Syngenta mentioned, they said “database sample 8



### number provide high confident on exposure”. I just want 9



### to add in another piece of uncerta inty that we mostly 10



### have been glossing over, which is measurement error . We 11



### do not have a good idea about what the magnitude of 12



### measurement error is. If you say go and take multiple 13



### samples at the same time, how similar did they turn out; 14



### or if you have multiple people taking samples at the same 15



### time, how similar did the turn out. And how similar is 16



### it if you have a person taking measurements versus an 17



### auto

- sampler. 18

19



### These are probably going to be relatively small compare 20



### to the big peaks, but if we are looking at extended 21



### durations of exposure, these sort of errors could add up. 22

23



### DR. DANIEL SCHLENK : Any comments from the other panel 24



### members? Okay, you want to go ahead and do b)? 25

26



### DR. ROBERT GILLIOM : So part b) to remind folks is, please 27



### comment on the advantages and disadvantages of deriving 28



### bias factors based on analyses of individual sites and 29



### years compared to taking percentiles of averages across 30



### sites and years. 31

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### My answer is the fundamental unit of exposure assessment 1



### is the site

- year co mbination. And each community water 2



### system site has a unique watershed with corresponding 3



### hydrologic behavior, pesticide use, etc. A unique 4



### population of people served, and every year is different. 5



### Generally, analysis needs to focus on each individual 6



### c ommunity water supply as a unit. The condition of 7



### greatest concern is when the maximum of a selected 8



### rolling average duration exceeds a level of concern, yet 9



### to be defined, and this tends to be more likely in high 10



### use seasons during years when runoff afte r applications 11



### is high. Commonly, the most extreme conditions happen 12



### one or more times every few to several years, as 13



### exemplified by the Honey Creek and Maumee River multi

14



### year results submitted by Syngenta. 15

16



### Bias factors, to the extent they are used f or screening

17



### level analysis, should be developed with the objective of 18



### identifying sites that merit direct monitoring. In this 19



### application, they can be biased in the conservative 20



### direction and used to identify individual sites with an 21



### unacceptable likeliho od, yet to be defined, of exceeding 22



### threshold, based on the available sparse monitoring data. 23



### These sites would then be monitored more intensively to 24



### more accurately assess the actual condition. 25

26



### The b ias factors may also be useful as a simple and 27



### tran sparent approach to estimating exposure for sparsely 28



### monitored sites for other purposes, such as for large

29



### scale risk assessments or correlation with 30



### epidemiological results. In these applications, the 31



### starting point for analysis and the endpoint of inter est 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is the individual site, not groups of sites. However, 1



### there may be certain data analysis approaches that use 2



### data from groups of sites to make inferences for 3



### individual sites. This can be done as long as the 4



### uncertainties in predictions for individua l sites are 5



### properly represented

. 6

7



### DR. DANIEL SCHLENK : Dr. Coupe... 8

9



### DR. RICHARD COUPE : I do not have any additional comments. 10

11



### DR. DANIEL SCHLENK : Dr. Lee... 12

13



### DR. HERBERT LEE : I just want to clarify that

– I agree with 14



### Bob

– but want to say that it is i mportant to look at 15



### each site by year when looking at the bias. So if we 16



### have comparison daily data and then we look at sub

17



### sampling weekly or 14 or 28 days, compute by 18



### interpellation

, compute the bias factor. You want to do 19



### that for each site for each y ear and then look at the 20



### distribution of bias factor s , say across sites or across 21



### years. And you can gain information by pooling that way. 22



### But for computing the individual points in the 23



### comparison, you want to do it by site by year. 24

25



### DR. DANIEL SCHLENK : Other panel members... All right, moving 26



### right along. Mr. Thurman

, are you clear with what you 27



### have? 28

29



### DR. NELSON THURMAN : I think we are very clear with what we 30



### have. 31

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### DR. DANIEL SCHLENK : Okay. Let‟s move on then to question 1



### two, and again you can fe el free to read the sub

- headings 2



### on that. 3

4



### DR. NELSON THURMAN : Question number two; please comment on 5



### the Agency‟s method of estimating time series using 6



### conditional simulations of variograms for monitoring data 7



### sets such as the AMP community water syste m monitoring 8



### that have 7

- day sampling frequencies. And part b) is; 9



### based on the US EPA‟s analysis using WARP with longer 10



### duration sampling intervals

, what advantages does the SAP 11



### see of including WARP modeling in this approach, i.e., 12



### better estimation of the daily maximum value? 13

14



### DR. DANIEL SCHLENK : Okay. Dr. Griffith, our lead discussant. 15

16



### DR. DANIEL GRIFFITH : I have addressed these sequentially, so 17



### I will present part a) and then part b) separately. I 18



### wanted to prefix this with two comments. On e is that the 19



### other discussants and I realize that probably some of 20



### what we will raise, the EPA scientists are fully aware 21



### of. Second, I do have tables in my report, which I will 22



### summarize. 23

24



### So, this methodology acknowledges the serial correlation 25



### latent in time series data. Note that Table D1.1 NCWQR 26



### 1995 Maumee River Data Set contains substantial temporal 27



### autocorrelation. Conventional Box

- Jenkins type ARIMA 28



### models require uniform spacing in time, but more 29



### effectively address seasonality. As an aside, the daily 30



### measures for 2011

, the Syngenta report 2001301

- 03

, imply 31



### that, for finished water, an ARIMA ( 1

, 1 ) model adequately 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### describes these data. And with those data that were 1



### released, most recently the ARIMA ( 1

, 1 ) model, the 2



### autoregressive term

, was consi stently above .9 suggesting 3



### that perhaps even differencing would be effective and the 4



### moving average term was roughly around

- .4 across those 5



### six data sets. 6

7



### Also, CWS

- 71 had a suspicious correlagram, but it could 8



### be a result of some of what we saw in t he metadata this 9



### morning. Restricting attention to the days of interest 10



### appears to handle the stationarity issue in an effective 11



### way , but the Table D1.1 sample atrazine data impl ies that 12



### Julian days 101

- 200 may be the wrong time interval; the 13



### start time s eems to be closer to Julian day 130 for that 14



### time series, and seems to go beyond Julian day 200

. 15

16



### The most recent Syngenta data support this contention for 17



### some of the other watersheds. And in fact, we saw a map 18



### presented yesterday and there was a simi lar map that was 19



### in one of the background material reports that showed the 20



### variation in latitude, which may well correlate with 21



### different start times and support this geographic 22



### variation consideration. 23

24



### The complication here may well be that different CWSs 25



### will have different Julian day time periods ; i n other 26



### words, geographic variation in the windows across these 27



### CWSs. 28

29



### Any methodology that focuses on mean responses, such as 30



### moving averages , the rolling averages

, will tend to 31



### underestimate peak atra zine concentration. Expectation 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### maximization imputations are conditional expectations; in 1



### other words, they are means. The presence of 2



### autocorrelation implies that these conditional means are 3



### locally adjusted. Substituting conditional means into a 4



### time series for missing data values suppresses variance; 5



### they only represent a trend line. This is one reason for 6



### the underestimation of a 1

- day maximum concentration

, 7



### while obtaining reasonable estimates of rolling average 8



### concentrations. 9

10



### This variance supp ression also raises questions about 11



### assuming that standard time series developed by 12



### unadjusted kriging are representative of true daily time 13



### series. Virtually all software packages report standard 14



### errors for the case of random sampling. The assumption 15



### th at they are the same for systematic or stratified 16



### random sampling, or for the observed non

- probability 17



### sample of monitored days and I think diagnostics should 18



### be performed to evaluate the assumption of a pseudo

19



### random unequal probability design, which appe ars to be at 20



### odds with their voluntary, truncated and mixed water 21



### gathering nature, may well seriously impact upon 22



### uncertainty assessment. 23

24



### In addition, assuming that un

- sampled days are missing at 25



### random seems questionable. In contrast, assuming missi ng 26



### years for any CWS are by design, and hence eliminating 27



### those years from the population of interest, seems 28



### reasonable. Perhaps assessments within the context of 29



### mixed modeling could furnish insights here. And I will 30



### come back to this in terms of poolin g of time series. 31

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### Other principle issues of concern include the following: 1



### (1) impacts of misspecification on the semi

- variogram 2



### model

– a wide range of forms should be examined; (2) 3



### impacts of assuming that atrazine concentration data 4



### conform to a lo g

- normal rather than another extreme value 5



### distribution, which can be dramatic in terms of the 6



### estimation of 95th percentiles; (3) impacts of ignoring 7



### spatial autocorrelation, which are less on mean patterns, 8



### and much more on 95th percentile estimates thro ugh 9



### effects on variance; (4) impacts of assuming a linear 10



### relationship between atrazine concentrations and 11



### covariates; again, potentially more dramatic on 95th 12



### percentile estimates, and add to uncertainty rather than 13



### improve estimatability; and, (5) impact s of not 14



### performing a sufficient number of simulations to really 15



### establish the uncertainty distributions; again, 16



### especially on 95th percentile estimates rather than on 17



### mean patterns. 18

19



### Issue (1) here is of particular concern. Empirical semi

20



### variograms e stimated with sample data can be extremely 21



### variable and unstable. Subsequent SAS 9.22 PROC 22



### VARIOGRAM results include standard error estimates for 23



### semi

- variogram model parameters . M any geo

- statistical 24



### software packages fail to report these values, because

, 25



### for example, some use visual curve fitting. Those 26



### reported here highlight this degree of variability. 27

28



### One option is to exploit spatial autocorrelation by 29



### pooling data for similar watersheds when estimating semi

30



### variograms; the subsequent discussion addresses this 31



### topic, too. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Finally, relatively large nugget effects tend to overly 2



### smooth rolling averages; in the absence of any 3



### autocorrelation, the E

- M solution is the sample mean. 4



### Kriging produces the best linear unbiased predictors, and 5



### is one wa y to deal with irregularly spaced data through 6



### time; treating it like a linear geographic landscape, as 7



### well as a time series with a sizeable amount of missing 8



### data. For instance, the selected subset of Table D1.1 9



### data has 43% of its values missing. It al so is 10



### substantially better than the simple linear interpolation 11



### used in some of the preliminary research , and I have seen 12



### it in some of the more recent research since I have been 13



### here , a lthough some substitutions, such as the one with 14



### PRZM model are condit ional. But the implemented 15



### methodology appears to suffer from a number of 16



### weaknesses. 17

18



### One drawback is considerably restricted candidate set of 19



### semi

- variogram models available in GEOEAS, which no 20



### longer is a state of the art software package. It has a 21



### few exponential Gaussian, spherical; semi

- variogram trend 22



### lines portrayed in Figures D

- 3 and D

- 27 appear 23



### unconvincing. A mis

- specified model here is another 24



### source of the nugget effect. 25

26



### In other words, you get a non

- zero intercept value 27



### arising simpl y because of specification error. The 28



### autocorrelation in the selected subset sample time series 29



### is considerable, and appears to be much better described 30



### by a Bessel function, which more directly links to an 31



### ARIMA ( 1,l ) model that is reflected in the most recent 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### data; if not a stable function, which is similar to a 1



### Gaussian function, but with an exponent other than two. 2

3



### These models, as well as other valid semi

- variogram 4



### models, can be estimated with ArcInfo's Geostatistical 5



### Analysis module, which I not e the software supported the 6



### research for Report MRID 48470008. They also can be 7



### estimated with SAS 9.22 PROC VARIOGRAM. And they also 8



### can be estimated with modules from the R project, which 9



### are free and can be downloaded. 10

11



### These two latter software p ackages furnish analytical 12



### rather than visual model estimation routines. SAS 13



### quantifies uncertainty associated with the semi

- variogram 14



### model estimation, which is alluded to in the reports, but 15



### without specificity, and differs from kriging prediction 16



### error

. 17

18



### For the log

- normal transformed atrazine example time 19



### series data; I did an estimation with SAS PROC variogram 20



### for the spherical Gaussian, which are two models that 21



### were reported, and the Bessell and the spherical clearly 22



### is not the best descriptor of the data. And depending 23



### upon criteria that you use, the Bessell and the Gaussian 24



### are competitive for that one

- time series. 25

26



### When I repeated this analysis, for the six most recent 27



### daily time series, in all six cases the Bessell function 28



### dramatically out performed the spherical and the Gaussian. 29



### So those are two tables that I am just summarizing here. 30



### And it outperformed it on both criteria that are reported 31



### for goodness

- of

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### Comparable results for other semi

- variogram models can be 2



### obtained with SAS
, PROC and NLIN

– so you can actually 3



### program these for a couple dozen possible semi

- variogram, 4



### but as I argued I think the most consistent one is the 5



### Bessell function

– and it uses weighted nonlinear least 6



### squares. 7

8



### A second weakness is the log

- norm al distribution 9



### assumption. Although the three

- parameter logarithmic is 10



### the best Box

- Cox power transformation enabling the 11



### selected subset of the Table D1.1 data to mimic a normal 12



### frequency distribution, the transformed data still are 13



### far from bell

- shaped . The Shapiro

- Wilk statistics, which 14



### are normalcy diagnostic statistics, improved from .9 to 15



### .93; so there is some improvement but there is still 16



### quite a bit of deviation entailed. This same description 17



### also applies to the six recent daily sampled CWSs. Of 18



### the six, only one achieves something that is 19



### indistinguishable from a bell shape cur ve with the three 20



### parameter log

- normal distribution. 21

22



### The log

- normal conceptualization describes an outcome 23



### that may be viewed as the product of many positive

- valued 24



### independent random variables. It has been used to 25



### analyze extreme values of, for example, rainfall 26



### quantities and river discharge volumes, and often is 27



### acknowledged as being a heavy or fat

- tailed distribution. 28

29



### One of the following extreme value distr ibutions, which 30



### mean that their probability distributions have extreme 31



### deviations from their medians, may well be more 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### appropriate: the Weibull, the generalized extreme value, 1



### Gumbel, and the Frechet. The selected subset of Table 2



### D1.1 data better conforms to a Weibull distribution than 3



### a log

- normal and slightly better conforms to an extreme 4



### value distribution, but the difference between the latter 5



### two is not very much. 6

7



### Nevertheless, in all three cases, evidence exists 8



### suggesting that the empirical dist ribution still differs 9



### significantly from their counterpart‟s theoretical 10



### distributions. The largest extreme value goodness

- of

- fit 11



### appears to suffer from too many low values in the 12



### beginning of the selected subset time series. I think 13



### one of the reasons these goodness

- of

- fit are not coming 14



### out better is because there was a set day 101 that the 15



### time series started and if you inspect the time series, 16



### what you see is that that varies quite a bit. Which is 17



### what I was talking about earlier, a variation in the 18



### stationary part of the time series start and end date. 19

20



### One stated ultimate goal of the methodology is to be able 21



### to predict values greater than those sampled. The 22



### Weibull, or perhaps another extreme value distribution, 23



### offers more potential for doing this than does the log

24



### normal distribution. The most recent Syngenta report 25



### T001301

- 03 furnishes data for an additional six CWSs, and 26



### these data yields, almost across the board, support for 27



### the Weibull distribution over the log

- normal distribution 28



### althou gh there are some cases in which the log

- normal 29



### distribution does slightly outperform the Weibull 30



### distribution. 31

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### These findings support the contention that atrazine may 1



### be better described by a Weibull distribution. They also 2



### suggest that such a charac terization may be watershed 3



### specific. A third weakness is the overlooking of spatial 4



### autocorrelation. This is somewhat surprising because 5



### geo

- statistics was developed to handle this data feature, 6



### and because of the extensive relevant discussions in 7



### Repor t MRID 48470008. 8

9



### Many geographically distributed variables within a 10



### watershed exhibit spatial autocorrelation. Time series 11



### for different watersheds also may be correlated. 12



### Depending upon such parameters as planting timing and the 13



### occurrence of storm events, watersheds of similar size 14



### and similar characteristics may well generate similar but 15



### perhaps lagged time series of atrazine concentration. 16

17



### If so, information can be borrowed from one time series 18



### to help complete another time series. And, infor mation 19



### in comparable time series may be pooled to better 20



### estimate the semi

- variogram models. 21

22



### Planned research apparently seeks to address a forth 23



### weakness, namely the use of covariates, which are called 24



### soft data in the reports. Co

- kriging allows inclu sion of 25



### additional information. One concern here is the 26



### assumption of linear relationships between atrazine and 27



### selected covariates: scatterplots appearing in Figures D

28



### 23 and D

- 24 do not support this assumption. The 29



### furnished reports state a number of R square values 30



### without including scatterplots: a random scatter of n

- 1 31



### points of approximately the same coordinate pair 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### accompanied by an extreme outlier can produce similar 1



### results. 2

3



### Some linear regression analyses involve too few points

. 4



### L inear regre ssion with four, eight, or 15 observations I 5



### think tend to yield questionable results. Results have 6



### been obtained with analytical routines from Microsoft 7



### Excel; various analysts have shown many Microsoft Excel 8



### routines to be unreliable. 9

10



### Conditional si mulations are an efficient and effective 11



### way to produce confidence intervals for the atrazine time 12



### series. A fourth weakness, which is easily remedied, 13



### pertains to these simulations. Simulation experiments 14



### exploit the Law of Large Numbers and the Central Limit 15



### Theorem. Those based upon 10,000 replications should be 16



### sound. Those based upon 1,000 replications could be 17



### bolstered. Those based upon ten replications, for 18



### instance Figures D

- 28 and D

- 29, are unacceptable. Except 19



### in extenuating circumstances, the number of replications 20



### should be the same across all simulation experiments. 21

22



### DR. DANIEL SCHLENK : Wow... Thank you Dr. Griffith. Dr. Lee, 23



### anything to add to that? 24

25



### DR. HERBERT LEE : Not much, he has already incorporated pretty 26



### much what I had to say . I do want to just get on to the 27



### record a conversation I had with Nelson Thurman‟s group 28



### yesterday, after his presentation. 29

30



### I think they are estimating an overall mean when they are 31



### doing what they are calling ordinary kriging, and that it 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is skewing their results. The particular data structure 1



### here, when nothing is happening it returns to zero rather 2



### than to some overall mean level that is nonzero, which 3



### would be the normal case with spatial patterns. But here 4



### it returns to zero and so if there is a way to set the 5



### mean to zero, rather than estimating the mean, I think 6



### that will improve their results especially for the 7



### confidence bands. 8

9



### For example, on their slide 16, looking at the Maumee 28

- 10



### day results; those are sort of wondering around and th ey 11



### just have the wrong mean there I think is the main 12



### problem. On the 4

- day average simulation on slide 19, 13



### for the Maumee and then the daily 4

- day, 14

- day averages 14



### for the Missouri

- 01, you see these weird bubbles that 15



### show up early on in the confidence bands and the 16



### confidence bands tends to be stretching higher than I 17



### think they really should be. And I think that is all 18



### because of having a mean that is nonzero; and that moving 19



### the mean to zero will help with a lot of the results. 20

21



### DR. DANIEL SCHLENK : Thank you. Dr. Portier... 22

23



### DR. KENNETH PORTIER : I should point out that we did 24



### communicate on Dr. Griffith‟s report before the meeting 25



### and so it really represents the three of us kind of 26



### thinking through this and we iterated it a couple of 27



### times. 28

29



### I j ust have one additional issue that I want to bring up 30



### at this point, with using a 1D geospatial approach to 31



### model what is essentially a non

- stationary time series. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### And that is the assumption is made with the geospatial 1



### approach that observed data are know n without error. And 2



### the impact of this assumption is most evident in figure 3



### 27

- A, where the 95 th 

### and 5 th 

### percentile cur ves from the 4



### conditional simulations, coincide every seventh day at 5



### the known sample points. And if you look at the curve it 6



### is kind o f weird; it goes up and than down... up and down. 7

8



### We know in fact that these values are really estimates; 9



### for grab samples, they are simply snapshots of 10



### concentration at the time of sampling in the location 11



### that is actually being sampled. Looking at the actual 12



### data from, for example, NCWQR 1995 Maumee River dataset 13



### in Appendix D, section 1.1, we see that for some dates 14



### multiple samples were taken and that there is substantial 15



### variability evident in these estimates. 16

17



### I think, although I am not certain of this

– I did talk 18



### to my colleagues and I think they agree

– that this 19



### variability is over and above the variability modeled by 20



### the nugget effect in the kriging model; this kind of 21



### needs to be confirmed and then incorporated into the 22



### model. Doing so wil l add additional variability to the 23



### simulations making 95 th 

### percentile curbs higher and 5 th 24



### percentile curbs lower and having variability at the 25



### sample points. 26

27



### DR. DANIEL SCHLENK : Any other panel members want to weigh in 28



### on this? 29

30



### DR. ROBERT GILLIOM : I did not directly collaborate on the 31



### answer and I wanted to add that I think in this panelist 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### member‟s view I do not think kriging is the way to go to 1



### fill in this and a lot of the problems brought up maybe 2



### reinforce that. 3

4



### I still feel that the bett er approach is to use a 5



### statistical time series model that links the temporal 6



### patterns of occurrence to some predictive factors like 7



### precipitation and stream flow and so forth, which is 8



### exemplified by the SEAWAVE model that was talked about in 9



### previous SAP s and recommended for this purpose. And I 10



### think, if I understood it right from the comments in the 11



### issue paper, it was kind of too much in the timeline to 12



### really get to that and try it. But my encouragement 13



### would be to still try that approach as a way to fill in 14



### data. 15

16



### And the advantage it may have is an addition to being 17



### able to produce realistic time series that are unbiased 18



### for sampling frequencies like seven days and so forth. 19



### It can also be spread across wider sampling frequencies 20



### and more variab le conditions with one tool. So you would 21



### have the advantage of having one singe tool be able to be 22



### used across a much wider range of circumstances where as 23



### with kriging you are going to have to have 7

- day or 24



### better data probably to make it work. Thanks. 25

26



### DR. DANIEL SCHLENK : Dr. Portier... 27

28



### DR. KENNETH PORTIER : Bob, I was thinking kind of the same 29



### way . T he only problem is the real non

- stationarity of 30



### these time series, the fact that they have this jump up 31



### patterns and then decline for an event. And that is kind 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### of hard, unless you have a factor in the environment that 1



### mimics that kind of effect; say like stream flow, which 2



### we are going to talk about in a few minutes . I t is going 3



### to be very hard to capture that with traditional time 4



### series modeling , and I do not know of any kind of 5



### approaches that would easily do it. But, in general, I 6



### kind of agree with you. The kriging is nice and it is 7



### taking into account all of this temporal autocorrelation, 8



### but like you I am kind of not convinced, and I think we 9



### wi ll get to that in the subsequent questions. 10

11



### DR. DANIEL SCHLENK : Anyone else in the panel on this? Okay, 12



### let‟s go ahead and go to b). 13

14



### DR. DANIEL GRIFFITH : The WARP, which is the watershed 15



### regression on pesticides model, furnishes predictions of 16



### the d istribution of atrazine concentrations in specific 17



### watersheds. Its input includes the following variables: 18



### atrazine use intensity, precipitation and rainfall 19



### intensity, a soil erodibility factor, percent runoff, and 20



### watershed size. 21

22



### Competing models i nclude: PRZM, which is the pesticide 23



### root zone model, EXAMS, which is the exposure analysis 24



### modeling system, and mass

- balance. WARP model

- generated 25



### output synthetic data for a 1

- day temporal resolution 26



### would allow the use of co

- kriging to secure missing 27



### atrazine concentration data imputations in a time series. 28

29



### These supplemental data would need to be properly 30



### integrated with monitoring data . T he reported experiment 31



### reveals that conditional simulations of merged WARP 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### model

- generated and sampled monito ring data are highly 1



### dependent on the WARP

- based imputations. If these data 2



### are equivalent to conditional expectations, then the 3



### associated imputations will have considerably less 4



### variability; in other words, the varian variation is 5



### suppressed, which give n the large percentage of missing 6



### values, could overweight these portions of a time series. 7

8



### In other words, WARP estimates do not really add the 9



### additional variability that would be expected in ambient 10



### measurements. Potential impacts include compromis ing the 11



### upper percentiles of observed concentrations, as well as 12



### reducing the likelihood of observing 4

- day, or any x

- day, 13



### rolling averages of concentration above some threshold 14



### value. 15

16



### Perhaps one way to temper this effect is to add random 17



### noise to the deterministic values in such a way that they 18



### are indistinguishable from the observed monitoring data. 19



### One ultimate goal is to establish an upper percentile 20



### threshold that is not excessively conservative, in other 21



### words, orders of magnitude beyond the obs erved data. 22

23



### The final percentile should furnish adequate protection, 24



### but not far more protection than is necessary, which 25



### could cost society benefits of atrazine while really not 26



### significantly improving the likelihood of avoiding 27



### adverse health effects . Within the context of this goal, 28



### error propagation merits evaluation to see whether or not 29



### compounding occurs, with this evaluation being balanced 30



### against returns on an investment of resources in such a 31



### study. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Conceptual arguments in terms of plausi bility may be 2



### sufficient to dismiss some propagation possibilities. 3



### Sources of error meriting consideration range from 4



### merging spatially gridded field data that are 4 x 4 5



### kilometers for rainfall with 85 x 74 kilometers for 6



### temperature, to raster images of rai nfall totals from 7



### historical radar weather data

– all of which may involve 8



### raster

- to

- polygon conversions

- to the numerous 9



### assumptions employed by model

- based imputat ion , f or 10



### example, the 1:1 relationship between relative 11



### percentiles of flow and atrazine i n the WARP model. 12

13



### One concern expressed in the reports is the need for a 14



### priori knowledge about reasonable upper limits for peak 15



### concentration estimates. Although such figures furnish 16



### checks for synthetic results, percentages of these peaks 17



### are not b eing estimated. Furthermore, because 18



### imputations are conditional means, estimation of extremes 19



### is unlikely. Replacing a log

- normal probability model 20



### with an extreme value probability model may help 21



### remediate this situation. 22

23



### Research establishing a va lid auto

- Weibull type of model 24



### might be useful. For example, the autocorrelation trend 25



### in the specimen atrazine data suggests a Weibull 26



### distribution with a shape parameter of roughly 3.2, which 27



### implies that it approximately mimics a bell

- shaped curve

. 28



### Th is may be one of the reasons why, for that specimen 29



### dataset, the log

- normal distribution performs well. 30

31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### With an accompanying scale parameter of 2.3 and a 1



### suitable autocorrelation factor, which was estimated from 2



### the observed data, the resulting daily t ime series 3



### resembles the observed atrazine time series. Based on a 4



### simulation with 10,000 replications of 100 draws from the 5



### auto

- Weibull distribution; the average almost perfectly 6



### replicates the base time series. And the approximate 95% 7



### confidence inter vals based on 10,000 replications of 100 8



### draws gives an up ward bound of roughly 23.5 for the 9



### maximum observed concentration value of 14.058. This 10



### latter result supports the need for a priori knowledge of 11



### reasonable upper limits for peak concentration esti mates, 12



### as well as indicates that imputations based upon a 13



### deterministic model, such as the WARP model, combined 14



### with an extreme value distribution, such as the Weibull, 15



### could allow prediction of values much greater than those 16



### sampled. 17

18



### This example also illustrates that imputed values tend to 19



### be highly dependent upon the deterministic model 20



### predictions. In this case the synthetic temporal 21



### autocorrelation component employed accounted for roughly 22



### 87% of the variance in the observed time series, allowing 23



### m uch less variability for the stochastic component. 24

25



### In closing, recognizing that EPA seeks reasonable 26



### estimates of exposure to atrazine from limited data, 27



### fine

- tuning of the Agency's current approach may yield a 28



### number of benefits, whereas diminishing r eturns in 29



### additional accuracy of atrazine estimates almost 30



### certainly will set in as the complexity of its 31



### methodology increases. Furthermore, as methodological 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### complexity increases, chances of user error also 1



### increase . The final methodology needs to be 2



### i mplementable by various EPA scientists with a diverse 3



### set of expertise. In other words, EPA must establish 4



### acceptable trade

- offs between the theory and the practice 5



### in these assessment too. 6

7



### DR. DANIEL SCHLENK : Dr. Lee... 8

9



### DR. HERBERT LEE : He has already i ncorporated all of my 10



### remarks. Thanks. 11

12



### DR. DANIEL SCHLENK : Dr. Portier... 13

14



### DR. KENNETH PORTIER : I just wanted to make one more point. 15



### Discussion of these fill

- in models has centered on the 16



### potential of producing series with maximum closer to the 17



### single

- day expected maximum. WARP PRZM combined models 18



### could help inform the estimate of the single

- day maximum 19



### concentration in those sampling situations where the 20



### maximum has a low chance of being observed in the sample. 21

22



### There was relatively little, if any

, discussion in the 23



### white paper, on the ability of these simulated series to 24



### recreate the distribution of what I will call “durations 25



### of time exceeding a specified threshold”; in other words, 26



### estimating the likelihood that the concentration series 27



### produces a pattern with x

- days in a row above some 28



### threshold concentration. 29

30



### This to me seems to be a much more important statistic 31



### than the single

- day daily maximum. Primarily because it 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is more directly related to the regulatory decision, as 1



### we have had disc ussions about area under the cur ve and 2



### days of exposure. 3

4



### Concentration time series with WARP PRZM infills, seem 5



### much more likely to more accurately estimate this 6



### distribution then would be simply using weekly samples or 7



### just modeling from the sample da ta rather than taking 8



### into account the basin and meteorology data that WARP and 9



### PRZM would do. It remains to be seen whether a running 10



### average time series properly scaled would produce a 11



### better estimate of this distribution than would a WARP 12



### PRZM infill s eries. And I think that remains an area of 13



### research. 14

15



### DR. DANIEL SCHLENK : Thank you. Any other input from the 16



### panel? 17

18



### DR. ROBERT GILLIOM : So I guess in further comment on the 19



### application of the WARP model is that I view it as its 20



### most valuable role as in applying to sites that you have 21



### no monitoring data for or data that is so sparse that you 22



### cannot fit a time series model or equivalent fill

- in 23



### method. In that role what it is doing is simply giving 24



### you a prediction of the central tenancy of a chosen 25



### concentration statistic for all similar basin in a 26



### region. 27

28



### So it give you an approximation of what to expect for 29



### that basin that could be used as has been mentioned to 30



### reconstruct a synthetic time series for sites with no 31



### data, basically. If you have actual data, just to stress 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### again, it should be used as opposed to trying to use the 1



### WARP regression model. 2

3



### I guess the last thing I would say is that as the target 4



### statistic of interest get refined, such as a 4

- day moving 5



### average or 14

- day moving ave rage or whatever, you can 6



### pretty readily refit a model like the WARP model to make 7



### that the dependent variable and just directly predict it. 8



### and directly predict the 4

- day max based upon the 9



### watershed characteristics

, and put confidence bounds on 10



### it and t hen that gives you a direct way to get right to 11



### the problem rather than having to reconstruct the whole 12



### time series. That is basically how we have applied it to 13



### date . S o I will just leave it at that and we can follow 14



### up later if you like. Thank you. 15

16



### DR . DANIEL SCHLENK : Any other input from the panel on this? 17



### Okay, we will go back to Nelson. Did you have everything 18



### you need on these? Do you need clarification at all? 19

20



### DR. NELSON THURMAN : I think we have what we needed. Well... 21

22



### DR. JAMES HETRICK : I guess I want a little bit of guidance 23



### here. Because I am hearing that if we are going to 24



### continue down this path of doing variogram analyses we 25



### have to upgrade our software, correct? 26

27



### DR. DANIEL GRIFFITH : I think so. You can do it with R if you 28



### wish. 29

30



### D R. JAMES HETRICK : Okay, that is fine. The other thing is I 31



### would like to just maybe in a little bit more plain 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### English here ask the question, are we on the right track 1



### as far as the conditional simulation approach? 2

3



### DR. DANIEL GRIFFITH : I think you are. One of the concerns 4



### that I see is that if you do the imputations and use 5



### those

– I saw several statements in the background 6



### materials that were completing a time series and now we 7



### have this time series of atrazine values. Well, all of 8



### those imputations are like the trend line and so you 9



### tremendously suppress the variance especially if in most 10



### of these cases you are estimating nearly half of the 11



### data. 12

13



### And I realize that if you go into the spatial domain, 14



### that will estimate 90% of the data and there is 15



### controversy in the spatial domain about using that as 16



### well. So if you look at the missing data literature, 17



### people like Schafer, what they do is they then sample 18



### from

– if it is a Weibull distribution, I would take this 19



### as my mean now that I have and I wo uld draw a sample from 20



### it, with that mean. And then you might do that so many 21



### times to get some idea of the variability. 22

23



### What I did in my example simulation, was I did 10,000 24



### replications and so I had the basic imputed time series 25



### that was the trend l ines and so I was sampling at each 26



### point from a Weibull distribution with that auto

27



### correlated mean and then I get my upper and lower bounds. 28



### So it is a conditional simulation in that sense. 29

30



### But I think that if you just impute and than use those 31



### imput ations as though they are real values, you have 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### dramatically underrepresented the variation that you have 1



### in an actual time series. And you can even compare that 2



### with these daily time series that are available now; 3



### would give you some sort of benchmark to get an idea 4



### about that with. 5

6



### DR. DANIEL SCHLENK : Dr. Portier and then Dr. Lee. 7

8



### DR. KENNETH PORTIER : I think you are and as I was looking at 9



### what we were talking about, what you have not done here 10



### is really helped us split out uncertainty in variabilit y. 11



### And it is something we keep coming to in front of the 12



### panel. But we are dealing with a time series and 13



### typically there we are talking about variability, right. 14



### We are trying to really explain that variability, the 15



### auto

- correlation structure, making s ure that we are not 16



### losing sight of the fact that yesterday‟s estimate has 17



### some information on what we expect today. 18

19



### The other thing is the uncertainty. We are sampling from 20



### these systems. We are fitting models; the models 21



### themselves have uncertainty . Some of what Dr. Griffith 22



### talked about is uncertainty in estimating the semi

23



### variogram, which has a big impact as it propagates 24



### through the model predictions. And probably in the next 25



### iteration of this, you really need to be kind of laying 26



### that out may be a little bit more clearly. When are you 27



### addressing variability, which is a model component, and 28



### when are you addressing uncertainty, which is really a 29



### component of this simulation; to a certain extent, what 30



### you are capturing in the simulation. 31

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### DR. HER

BERT LEE : As much as I really like kriging in general, 1



### in this particular case, as we have discussed, there is a 2



### lot of uncertainty. So I want to ask explicitly, are we 3



### getting any better results then just doing a linear 4



### interp o lation and using a bias fa ctor in terms of being 5



### able to predict accidence over a certain threshold of 6



### time. 7

8



### It may be that in terms of the accuracy of our results, 9



### because of all of the uncertainty, we may be able to do 10



### just as well with the linear interpellation and the bias 11



### factor; that would be a lot easier and a lot simpler and 12



### probably cheaper to do in practice. And so I want to ask 13



### explicitly, is it worth the extra effort to do the 14



### kriging

– as much as I like kriging in general. 15

16



### DR. DANIEL SCHLENK : Okay, did you get yo ur clarification? 17

18



### DR. JAMES HETRICK : Yes, I think we are on the right track and 19



### I know where we need to go at least. 20

21



### DR. DANIEL SCHLENK : Great. All right I think we have time 22



### for maybe one more question we can move in through here 23



### to get to lunch. Le t‟s move on to charge question number 24



### three. And Nelson I will let you decide how much you 25



### want to read of that one. If you do not want to read the 26



### whole question, or just the subheading that is fine. 27

28



### DR. NELSON THURMAN : This question is relating to so me of the 29



### modeling approaches and methods we looked at applying to 30



### less frequent sampling intervals. And hopefully some of 31



### this is a spillover from what was discussed earlier. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Please comment on these additional modeling approaches, 1



### that we have presented both in the background paper and 2



### in our presentation, for interpreting sparse monitoring 3



### sets; in other words, sampling less frequently than 4



### weekly. 5

6



### DR. DANIEL SCHLENK : Lead discussant on that, Dr. Lee. 7

8



### DR. HERBERT LEE : So in some ways this is a conti nuation of 9



### the previous question but it has some different flavor to 10



### it. I do want to repeat when the data is sparse, you 11



### just cannot fit a variogram; you cannot get accurate 12



### results solely from kriging or from linear interpolation. 13

14



### S o various approac hes have been explored; one of them is 15



### to use flow as a covariate. But the initial result has 16



### not been particularly promising. There are more complex 17



### relationships than just a simple linear relationship with 18



### flow; it depends on also the application timin g and it is 19



### about transported materials rather than just the outright 20



### flow. So instead of think ing about flow itself, one 21



### direct improvement is to think about WARP, which is 22



### actually developed to model the situation; and so it 23



### makes more sense to use WARP rather than try and reinvent 24



### WARP. 25

26



### Alternatively, we have looked at some other approaches. 27



### Syngenta‟s approach using PRZM appears promising. 28



### Looking at infilling points particularly around 29



### precipitation events; filling that in and using that to 30



### pred ict peak areas. You could set up a fairly 31



### conservative approach using PRZM. They also looked at 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### some methods using sort of the three times infilling, 1



### saying you expect a point, as a conservative approach
, 2



### probably not more than three times what is observ ed 3



### nearby; and then you can infill using that. You can also 4



### look at building time series models or the SEAWAVE model, 5



### specifically for time series. So there are a number of 6



### different ways that this can go that I think are better 7



### than just looking at flow as a covariate. 8

9



### I want to say sort of ideally, we want to set up a regime 10



### such that sites can move between different frequencies of 11



### monitoring. Right now we have some sites that are 12



### monitored weekly, during the application season, and 13



### others that are just monitored quarterly; and that is a 14



### really big gap. And it is unclear exactly how much 15



### information we are losing in there, but on the other hand 16



### if a site has been relatively clean, it does not 17



### necessarily need to be monitored as frequently. 18

19



### So t here needs to be a good way for moving up and down in 20



### terms of frequency, perhaps with something intermediate 21



### between weekly and quarterly like monthly. And using 22



### these sorts of different models at different levels would 23



### be a way to help guide when sites needs to move between 24



### levels. When you have weekly data you can do things like 25



### kriging or linear interpellation with a bias factor. 26



### When you have monthly or quarterly data we are going to 27



### need these models to help guide, do they need to be 28



### looked at more closely. 29

30



### DR. DANIEL SCHLENK : Okay. Dr. Griffith, you are next. 31

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### DR. DANIEL GRIFFITH : The WARP, watershed regression on 1



### pesticides model, furnishes predictions of the 2



### distribution of atrazine concentrations in specific 3



### watersheds. Its input includes t he following variables: 4



### atrazine use intensity, precipitation and rainfall 5



### intensity, a soil erodibility factor, percent runoff, and 6



### watershed size. 7

8



### The PRZM predicts chemical movement in surface soil, 9



### yielding a daily time series of potential runoff event

10



### based concentrations, and requires more input, for 11



### instance temperature, land use, and soil type than the 12



### WARP model. It uses spatially specific NEXRAD radar 13



### data, requiring additional data merging. The EXAMS model 14



### predicts the fate, transport and exposure concentration 15



### in surface water by combining chemical loadings, 16



### transport, and transformation into a set of differential 17



### equations using the law of conservation of mass as an 18



### accounting principle. 19

20



### Its data inputs include fundamental chemical pr operties 21



### of atrazine, and up to 32 different segments for a given 22



### watershed, for each of which up to 28 different 23



### substances may be simulated. The EXAMS model also 24



### requires more input than the WARP model. 25

26



### Finally, the mass

- balance model, which describe s 27



### variations in atrazine concentration as a series of 28



### storm

- event associated peaks that taper off over time, 29



### produce atrazine discharge mass quantities that are often 30



### differ ent by orders of magnitude in neither a positive or 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### a negative direction. Conseque ntly, WARP appears to be a 1



### reasonable choice for obtaining supplemental data. 2

3



### Output from that model yielding the best estimate of 4



### daily atrazine concentrations should be employed as the 5



### covariate in kriging. If output for no single model 6



### appears best , perhaps a weighted average of daily model 7



### output could be utilized. Reconsidering the semi

8



### variogram models for the specimen atrazine data, 9



### including the synthetic spatial autocorrelation factor as 10



### a covariate for co

- kriging produces considerable 11



### smooth ing of the daily experimental variogram. 12

13



### In addition, the resulting goodness

- of

- fit diagnostics 14



### improve for all candidate model specifications, and 15



### furnish additional evidence that the Bessel function may 16



### be the preferred model. These results corrobor ate that 17



### imputed values will tend to be highly dependent upon 18



### deterministic model predictions used as covariates. The 19



### lack of a stochastic component for the imputations will 20



### tend to suppress variability; deterministic model 21



### predictions are similar to cond itional expectations. 22

23



### Theoretically, if no relationship exists between the 24



### model

- generated data and the observed monitoring data, 25



### then the deterministic values do not impact upon the 26



### kriged values. As the relationship between the 27



### deterministic model o utput and the monitoring data 28



### increases in strength, increasingly more information can 29



### be borrowed from the deterministic model output to 30



### complete each daily time series. 31

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### This procedure is far superior to linear interpolation. 1



### One principal weakness of using deterministic model 2



### output arises from the assumptions involved. Because 3



### values between observed monitoring points in time are 4



### unknown, they may not coincide with model output, even if 5



### the observed data perfectly align with the corresponding 6



### subset of model output. 7

8



### This weakness furnishes a strong argument to employ a 9



### time

- interval stratified random sampling design, rather 10



### than a systematic design with a random start weekday. 11



### Sensitivity analyses, especially with regard to error 12



### propagation, co uld shed light on the magnitude of impacts 13



### of certain assumptions. 14

15



### Critical ones include the following: 1. in the PRZM 16



### model 60% of atrazine is applied at four uniformly 17



### distributed major pulses, with the remaining 40% being 18



### applied uniformly across a ll other days; 2. movement 19



### through a watershed is indexed to the longest shortest 20



### path between its outlets and its headwaters; 3. growing 21



### degree days are defined by

– and they state a formula

– 22



### difference between temperature extremes divided by 2

- 50 23



### and th at is in Fahrenheit. 4. all corn and sorghum crop 24



### areas are treated; 5. for PRZM all watershed farmers use 25



### atrazine in a similar way to those in the baseline CRC 26



### survey; 6. for PRZM the atrazine use rate is uniform 27



### across all soil types; 7. watersheds exp erience no 28



### conservation practices, and have good hydrologic 29



### conditions; and, 8. the non

- random sample of monitoring 30



### data can be treated like a random sample. 31

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### Assumptions that most likely have little adverse affect 1



### on results include: 1. results for an irregularly space 2



### time series can be adjusted by weighting each value by 3



### 50% of the time distance between its preceding and its 4



### subsequent value; 2. multiple sample values for a day can 5



### be represented by their geometric mean; 3. values 6



### substituted for tho se quantities less than the detection 7



### limit; 4. designing analyses in such a way that 8



### concentration estimates tend to be conservative; and, 5. 9



### the half

- life of atrazine is 61 days in a watershed 10



### although evidence exists suggesting that it has a much 11



### longer half

- life in subsurface soils. 12

13



### In the end, a meaningful model is only as good as the 14



### ability of its assumptions to mirror the real world. One 15



### notable trade

- off is between the expenditure of resources 16



### to collect reliable sample data, in a design

- based 17



### context, and the use of model

- based techniques that 18



### require resources to assemble massive amounts of 19



### ancillary data properly and then convert them into sample 20



### data equivalences. Physical sample collection requires 21



### retrieval followed by storage of specime ns, and is 22



### plagued by instrument malfunctions as well as human 23



### error. Model generated results suffer from data 24



### availability as well as human error. One cannot go back 25



### in time to correct the former; updates followed by model 26



### re

- executions allow correction s to be made for the 27



### latter. 28

29



### DR. DANIEL SCHLENK : Okay, next discussant, Dr. Portier

. 30

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### DR. KENNETH PORTIER : Thank you. So I will start by saying I 1



### do not have a lot of experience with this kind of 2



### modeling, but that do not usually stop me from 3



### commentin g. I should say that that experience is evening 4



### worst when I sit down with Dr. Gilliom and Dr. Coupe and 5



### start talking about what PRZM, EXAMS, SEAWAVE, and WARP, 6



### really produce in getting a better understanding of that. 7



### So some of this I may have to chan ge as my understanding 8



### changes from the discussion. But I‟ll go on. 9

10



### I can only assume that the WARP or PRZM, EXAMS, or the 11



### SEAWAVE models have the potential to produce a daily time 12



### series that could be used as a covariate time series, for 13



### example, in a co

- kriging approach. That if sufficiently 14



### correlated with concentrations, would allow one to 15



### essentially fill in mean concentration pattern between 16



### sampling dates and the concentration time series. I am 17



### assuming that the estimated variogram, for the 18



### co ncentration time series, would possibly demonstrate 19



### better properties because it would not have to be 20



### accounting for as much of the total variability as it had 21



### to do without the covariate. 22

23



### So I think if we get the right predictions from these 24



### determini stic models, it is quite possible we can get 25



### much better synthetic kymographs. So that is the first 26



### thing. But I wondered, as have some of the previous 27



### discussants as I read this section a number of times, if 28



### a simpler model might result in similar resul ts and 29



### actually be easier to understand. For example, what 30



### happens if one were to simply regress the sample 31



### concentration time series on the PRZM or other model 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### predicted time series, using some kind of nonlinear 1



### function, a polynomial or something else o r use some kind 2



### of robust smoothing approach such as low est. and 3



### properly lagging these results, whether we would get just 4



### as good a prediction. I do not know if we have really 5



### looked at that. 6

7



### I f one finds that the resulting R square was pretty high, 8



### close to one, I would suggest that the PRZM model or 9



### other model would be a good predictor of the 10



### concentration time series for the un

- measurable time 11



### points. This approach might work quite well for what 12



### Syngenta referred to as the small AMP size classes

, 13



### because the smaller areas allow for only one or a few 14



### fields to be impacting the water concentration and time 15



### lags would be reasonable on the order of a day or a 16



### couple of days. 17

18



### So those small size classes where we have things that are 19



### really spiky, some of these model that might actually 20



### work because it is a close connection between what is 21



### going on in this small watershed and what is happening at 22



### that sampler in the community water system. 23

24



### For larger CWS size class areas, incorporating many more 25



### fields and longer transit time, it is more likely that 26



### the concentration time series is some kind of weighted 27



### sum of variably lag WARP model prediction for all the 28



### fields impacted by significant rainfall event. So the 29



### larger the area the more kind of ran dom of incidents 30



### occurring that you are trying to add up and integrate 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### through to get to a concentration at a community water 1



### system. 2

3



### And all I could think of is for one thing this would be a 4



### very challenging model to fit; that is a statistician way 5



### of say ing it is impossible. But then on the other hand I 6



### keep thinking this is some kind of sum of correlated 7



### series model. There must be some kind of limit theorem 8



### going on here that says when you get a number of these 9



### things happening and they are lagged , you would expect to 10



### see some kind of log

- normal type pattern or something 11



### like this. 12

13



### So for the medium to larger systems you are having to 14



### deal with less of the spikiness of the pattern and it is 15



### much more of a modulated pattern, which I would expec t 16



### from this kind of sum of correlated series kind of thing 17



### in that. So you might be really looking at two different 18



### kinds of modeling scenarios. 19

20



### This kind of regress ed time series approach do not 21



### preclude the introduction of further autocorrelation 22



### st ructure in the residuals of the model fit. So the 23



### regression is fitting kind of the long

- term pattern and 24



### then you have correlated noise around it as well and you 25



### could add that; some kind of again nonlinear ARIMA model 26



### or where the mean is not constant. 27

28



### To some extend Syngenta is taking this approach by using 29



### the modified PRZM model to fill in the extreme events 30



### between sample concentration value. But if you are going 31



### to fill in the extreme events, why not go the whole way 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and use WARP to fill in the rest of the sequence. This 1



### is not what Syngenta is doing because if you look at 2



### slide 20 of the Syngenta „Occurrence in Drinking Water‟ 3



### presentation in the meeting docket, it clearly shows they 4



### are using linear interpellation between the WARP inspired 5



### ma ximum and the observed sample points. One other issue 6



### with the Syngenta approach is that they assume an 7



### atrazine runoff event occurs between every pair of 8



### sampling days. 9

10



### So for a 7

- day sampling this essentially assumes a runoff 11



### event every week and fr om some of the date we have seen 12



### in previous SAPs, and I will have to go back and look and 13



### see whether it was the February or April 2010 SAP, where 14



### we looked at a lot of these patterns , we know that for 15



### the most part it is one or two event a season that an y of 16



### these things observes; so why would we even assume a 17



### priori a maximum every week. We really should be saying, 18



### “Oh, we will throw one somewhere in here” and that is a 19



### more reasonable model. And for small watersheds I might 20



### throw that maximum in close r at the beginning of the week 21



### and give myself time for that decay that would match the 22



### next sampling point, right; a very simple modification of 23



### their method. 24

25



### Are there other time series that could be used as an 26



### explanatory model in this kind of regre ssion approach? I 27



### think most hydrologist would agree that water flow would 28



### not be expected to be highly correlated with 29



### concentration except in possibly the very smallest 30



### basins; and even then both concentration and flow would 31



### be highly correlated with ra infall or irrigation patterns 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and all of that is assuming atrazine has been recently 1



### applied in the field. There has to be some material 2



### there to flow off. 3

4



### So if I have anything else I would say for small fields 5



### we really need to look at rainfall and irrigation 6



### patterns; that would be the only other time series that I 7



### could think of that might have any effect. And I will 8



### stop at this point. 9

10



### DR. DANIEL SCHLENK : Any other panel member have anything to 11



### add. 12

13



### DR. ROBERT GILLIOM : I guess one thing I wou ld add is that 14



### personally I would encourage the continue development of 15



### the PRZM approach and especially the underlining data 16



### that is needed to drive it at a national level. Because 17



### the transfer value from that whole methodological 18



### approach from data to m odel will have a lot of transfer 19



### value to other chemicals and it is a good investment to 20



### make I think. But, on the other hand my other comment 21



### would be is

, I would not get bogged down by holding off 22



### on all of the related decisions for a compound like 23



### atra zine while you work through the whole process, which 24



### might take a while of seeing how an edge

- of

- field model 25



### applies to different size systems and so on and so forth 26



### that we have not all got in to. So I guess I am in the 27



### camp of continuing to move ahead o n development
, but do 28



### not let it get in the way of progress. 29

30



### DR. KENNETH PORTIER : This morning we had some conversation 31



### like this. So there is the atrazine issue and then there 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is a longer term risk assessment paradigm for EPA and we 1



### see this kind of PR ZM modeling time series stuff as part 2



### of a longer term paradigm that EPA is going to need 3



### nationally to be able to make these kinds of decisions. 4



### It just happens to be you are doing it with atrazine 5



### because it has this fantastic dataset and a lot of 6



### infor mation, and you have a little bit of a push now to 7



### incorporate that. But I tend to agree with Dr. Gilliom 8



### in that we do not want that longer term goal to hold up 9



### your shorter term decision

- making process. 10

11



### DR. DANIEL SCHLENK : Any other panel input on que stion three. 12



### Okay we will go back to Nelson, do you have everything; 13



### do you need any clarification on this? 14

15



### DR. JAMES HETRICK : In our attempt to try to infill that in 16



### that example that we have in the white paper in the 17



### appendix, we use flow; flow may no t be the best covariate 18



### to use to try to take the WARP estimates and put them 19



### into a time series. Do you have any other suggestions of 20



### other covariates

– I was thinking like nitrate or 21



### nutrients that might be something to look at

– that you 22



### would suggest looking at as a covariate? 23

24



### DR. ROBERT GILLIOM : I think certain aspects of flow will work 25



### if our time series modeling is an indication. So if you 26



### are within the seasonal window and you focus on anomalies 27



### of flow conditions from normal

, for that season, then I 28



### think you will find them to be predictive; in the same 29



### vein I think daily precipitation will prove to be 30



### predictive as a explanatory variable and a time series 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### model. And then I guess those are the two main ones I 1



### think of and I can let you know i f I think of others. 2

3



### DR. DANIEL SCHLENK : All right, everybody good on number 4



### three? 5

6



### DR. KENNETH PORTIER : When I looked at the flow data and you 7



### plot it out, it is very clear you have kind of a bi

- modal 8



### thing going on. You have these periods of low 9



### c oncentration and high flow; so the stream is flowing but 10



### there is nothing in there. There is no chemical in there 11



### a nd that is because there probably was no chemical in the 12



### field or previous rainfall events washed out whatever was 13



### available to be washed ou t. But on the other hand there 14



### is a period where concentration is correlated to flow and 15



### so you kind of get this bi

- modal process going on. And I 16



### do not know how to model that because the information on 17



### how you switch between this one and that one is 18



### ess entially what PRZM is providing you. 19

20



### PRZM integrates that field level fertilizer application 21



### and stuff like that. So just kind of naively using flow 22



### is not going to help you because I think you are adding a 23



### lot of variability because of what we looked at there. 24

25



### When you look at other agrichemicals like fertilizers, 26



### clearly they are not put down at the same time as 27



### atrazine is, atrazine being a pre

- plant. Sometimes they 28



### put fertilizer down

, I guess
, for some crops; some crops 29



### they make a separate t rip at a different time through the 30



### field. I really do not know whether looking at those 31



### things are going to help you

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### When you said that I had a flashback to some time series 2



### data I looked at of North Florida nitrogen flow in th ese 3



### clay areas
, and the data was a nightmare because I could 4



### not predict when you would get these spikes. This was 5



### off of the chicken farms where they spread the fertilizer 6



### out in the pasture and then you are wondering when it is 7



### going to hit the stream. And it was not correlated with 8



### rainfall; we needed a PRZM model to begin to understand 9



### why it showed up today and it did not show up yesterday 10



### or a week ago. 11

12



### DR. DANIEL SCHLENK : Okay, any other comments on that? You 13



### guys good with that? 14

15



### DR. NELSON THURMAN : Yes, I think so. 16

17



### DR. DANIEL SCHLENK : Okay, debating on whether to go on to 18



### four, but I think since we are so far ahead I think we 19



### will go ahead and just take a lunch break until 1:00. 20



### Let‟s go ahead and do that and we will reconvene at 1:00. 21

22



### DR. DANIEL SCHLENK : Welcome back. Let‟s go ahead and move on 23



### to our next charge question which is charge question #4 24



### which is, I think, the last in terms of our water 25



### sampling section and Nelson if you want to read that into 26



### the records that would be great. 27

28



### DR. NELSON THURMAN : The preamble relates to our focus on 29



### trying to characterize year to year variability. Part A: 30



### Please comment on the sufficiency of existing 31



### atrazine/triazine monitoring data available to the Agency 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### – in particular the Atraz ine Monitoring Program (AMP) 1



### coupled with the earlier Voluntary Monitoring Program 2



### (VMP), which conceivably span from 1993 to the present 3



### for some community water systems (CWS)

– for use in 4



### characterizing the likely range in year

- to

- year 5



### variability in atr azine or total chlorotriazine (TCT) 6



### concentration. 7

8



### Part B: Please comment on the Agency‟s suggestion for 9



### using a PRZM hybrid model, calibrated on the current 10



### years of monitoring, to provide estimates for a wider 11



### timeframe by modeling additional years using weather data 12



### that span a 30

- to 50

- year period. 13

14



### And Part C: What other possible approaches can the SAP 15



### recommend for capturing year

- to

- year variability? 16

17



### DR. DANIEL SCHLENK : Okay thanks. Our first lead discussant 18



### is Dr. Coupe. 19

20



### DR. RICHARD COUPE : Thank you. This is Richard Coupe. Sadly 21



### I think everything I am going to say has already been 22



### said, at least once in our first three questions but I am 23



### going to say it anyway just because I have the floor. 24

25



### Before I address the question direct ly, though, I want to 26



### make a couple points. They have been made by other 27



### people but I kind of want to put them together. One is 28



### that atrazine is an extremely important economic 29



### chemical. The other one is that atrazine is found in the 30



### source water from a number of community water systems. 31



### Material that was supplied by Syngenta indicated that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### during the period 2001 to 2009, greater than 1.5 million 1



### of our fellow citizens were exposed to concentration of 2



### atrazine greater than 3.0 in their drinking water an d 3



### that was just from quarterly samples. 4

5



### I think these two facts are why we are here. In my mind 6



### it is right and appropriate that we discuss this. There 7



### have been some comments about how many SAP s there have 8



### been over the last 10 years or so but again , in my mind, 9



### it just shows how important the topic is. 10

11



### I want to mention that when I was first asked to be on 12



### the SAP last year, I called Bob and asked him whether I 13



### should do it or not . H e said sure, it is fun, come and 14



### watch government sausage bein g made , i t will change your 15



### life. 16

17



### So the question presuppose s that you can never stop 18



### collecting observation data. By using historical data we 19



### can characterize the distribution of atrazine in drinking 20



### water in the future or that would mean for that to happen 21



### we would have to be able to say that what happened in the 22



### past is what is going to happen in the future. 23

24



### So some of this data that we are looking at now is 25



### collected from as early as 1993 and that is getting close 26



### to 20 years old now and the qu estion that comes up is

, 27



### has anything changed over that time that would make you 28



### think that perhaps the delivery of atrazine to the water 29



### shed had changed? Of course there is a whole list of 30



### things that make that true and one is conservation 31



### tillage. We have a whole lot more conservation tillage 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### than we did before and the other one was the introduction 1



### of genetically modified crops, specifically for atrazine 2



### and some of the other crops ; I mean for corn, for 3



### glyphosate , s o this changed how atrazine is used

. 4

5



### So if you consider the drivers of what makes atrazine 6



### appear in your water, basically you have kind of three 7



### drivers. One is hydrology, one is flow path and the 8



### other one is use. All three of these work in combination 9



### to move atrazine into your ser vice water . Then the 10



### question that comes up i s, if you want to stop your 11



### sampling or if you are going to change your sampling 12



### pattern and rely on historical data i s , will these change 13



### in the future ? Well, hydrology kind of reflects rainfall 14



### and we do not have to look too far past this last May to 15



### see how much rainfall can change over time. 16

17



### All you have to do is look at some of the WEB sites and 18



### show how many sites in the Midwest during the month of 19



### May had historic periods of record in their flow. It was 20



### just tremendous. So we had a record flood in May right 21



### there in our application time period. And you can ask 22



### these question s of flow path . When we talk about flow 23



### path, flow path is how water and atrazine moves over the 24



### landscape or under the land scape ; h ow it moves into the 25



### stream and then into the drinking source . And, has that 26



### changed over time or can it change over time ? 27

28



### And then in reality it can change and it is going to 29



### change probably in the future. Conservation tillage is a 30



### big part of it. I mean, one of the big drivers for 31



### atrazine in service water is how it flows over the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### surface and so if you r conservation tillage leaves a lot 1



### more material on the surface it slows down the water so 2



### this has probably changed a little bit how the at razine 3



### appears in surface water. 4

5



### We are also now having

-- in the Midwest especially

-- we 6



### are having subsurface drainage which is being directly 7



### run to the surface of the soil. So we are having a flow 8



### path that is now changed. We are not running off into 9



### the stream now, we are running off into a low depression 10



### on the field . It is going into the service drain and is 11



### moving down through this drain and then into the stream. 12



### So that could actually elongate the distribution of 13



### atrazine in the stream. 14

15



### We could have changes in flow path. All this is just to 16



### say that we could have changes in the future. And then 17



### use; could we look at use? Can use change in the near 18



### future ? T hat is again true. If we just take a look at 19



### what happening with glyphosate now, we are having 20



### resistance appear for glyphosate for the chemical roundup 21



### and that could change how atrazine is used. The use of 22



### atrazine could increase quite a bit in the future because 23



### of resistance to glyphosate. 24

25



### A lso the biofuel‟s initiative, although it does not 26



### directly increase the amount of atrazine use, it 27



### increases the incentive for farmers to grow corn which 28



### does actually increase the amount of atrazine use. So we 29



### could be having big changes in all three of the major 30



### drivers for our flo w path. 31

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### So then the question was is do we have enough data or 1



### when will we know we have enough data. Well, you are 2



### never going to have enough data is my conclusion on that. 3



### But do you have to sample everywhere all the time. Well 4



### no, of course you do not have to. And we have this 5



### atrazine monitoring program

, which has a way into it and 6



### a way out of it which is really pretty good. 7

8



### I do not think it is completely predictive of all the 9



### systems because to get into it you look at a quarterly 10



### sampling and have to exceed

-- I forget what it is

-- to 11



### exceed
, 1.6. So we can probably use something like a 12



### WARP or a PRZM model to kind of look at places we do not 13



### have which are more vulnerable

, but we do not have 14



### exceedances in their STWA samples. 15

16



### In additi on, you could use those to move them out of AWP 17



### or the monitoring program as you can use that in 18



### combination with your sampling to indicate that 19



### conditions have change, that you will not have the issues 20



### with the distribution that you ha d . I think that was all 21



### my comments on that part. 22

23



### DR. DANIEL SCHLENK : Thanks. Bob Gilliom. 24

25



### DR. ROBERT GILLIOM : Mine are j ust a few specific things to 26



### point out regarding adequacy of the historical multiyear 27



### data. 28

29



### One is just along the lines of... and I am not trying t o 30



### par se out which ones have which, but the total 31



### chlorotriazine were not measured in all of them so that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is just one thing to keep in mind. A lso, in particular, 1



### simazine has been, as an example, some of the long term 2



### trends has been more up

- trending in us e and 3



### concentration. So those kinds of things always have to 4



### be watched out for as Richard alluded to for applying 5



### historical data to the future. 6

7



### I did think that the VMP data , the voluntary monitoring 8



### thing that is weekly but since the early 90‟s, do es 9



### present a valuable database to examine year to year 10



### trends as long as the bias and the short duration of 11



### statistics is either avoided or accounted for. It still 12



### does provide a really valuable database that has 13



### multiyear data for over 100 sites. 14

15



### In terms of sufficiency of annual data, you know, 16



### sufficiency depends on t he application; I guess is the 17



### glib way to say it. W hat we have now is sufficient for 18



### some purposes and not for others. If the objective is to 19



### estimate it conservatively, protect ive b ias factor to 20



### apply to sparse monitoring data

, and you can be 21



### comfortable with a conservatively high estimate from the 22



### data arranged, it is probably adequate. If you want to 23



### estimate actual within a narrow bound of uncertainly like 24



### plus or minus 20 or 50% , then it is not. 25

26



### I think th e reliability criteria just need to be 27



### stipulated and used to ga u ge whether accuracy is adequate 28



### or not. I think that is all I have. 29

30



### DR. DANIEL SCHLENK : Thanks. Dr. Lee. 31

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### DR. HERBERT LEE : I just want to add one quick ol d detail in 1



### that there is a lot of year to year variability but 2



### particularly in, say, if you are looking at the 3



### magnitude. There is a lot of year to year variability. 4



### I would expect the shape to be more similar year to year

. 5



### S o things like the modality, is it one peak, it is 6



### multiple peaks, what is the correlation structure as far 7



### as estimating variograms? I would hope that that would 8



### be more consistent year to year but the overall magnitude 9



### of these peaks may be highly variable depending on these 10



### other factors that have already been discussed. 11

12



### DR. DANIEL SCHLENK : Okay. Dr. Portier? 13

14



### DR. KENNETH PORTIER : I guess I tend to agree with Syngenta 15



### that for atrazine we have a very rich database, one that 16



### should provide more than adequate information on year to 17



### year variability in atrazine and TCT concentration. The 18



### issue is more how to effectively utilize this database; 19



### how to extract the necessary statistics with the 20



### appropriate models to be able to produce, what I call, 21



### less bias estimates with within year and among year 22



### variability. Bottom line, I think we have a very rich 23



### database; we just have to figure out how to use it. 24

25



### DR. DR. DANIEL SCHLENK : Okay , o ther panel comments? Yes, Dr. 26



### Griffith. 27

28



### DR. DANIEL GRIFFITH : This links back to some of t he other 29



### questions that we discussed before lunch as well. In 30



### part, when I think about... and this question, right at the 31



### beginning, characterizing overall uncertainty and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### exposure... I t seems to me that one of the critical 1



### questions

-- and I commented briefl y about it before and 2



### it was discussed in your presentation to us as well

-- 3



### o ne of the critical issues is if we start looking at all 4



### the sources of variability or error , do they compound ? 5



### How does error air propagate through all of the analyses 6



### and in pa rt there has been focus on sampling error in 7



### terms of frequency in time and to some degree in space in 8



### terms of doing the sampling. 9

10



### There is going to be, sort of, inherence stochastic 11



### variability in atrazine and that is going to be through 12



### time, that i s going to be over space and that also is 13



### going to be how it gets into the water supply

, which I 14



### think links back to the type of water shed, et c etera

. 15



### We have talked about measurement error and I have not 16



### seen anything about the degree of measurement err or in 17



### the water assay
, but certainly imputations are going to 18



### introduce measurement error and type of sampling. 19

20



### If it is the auto sampling which, at least what was 21



### described in the background material, is sort of 22



### averaging across the day because there is a little bit 23



### taken at different times of the day versus a one

- time 24



### s coop. There is going to be

, what really is measurement 25



### error there because it is a different type of sampling. 26



### And then I noted the specification error in terms of the 27



### semi

- variogram model, but specification error also could 28



### enter through, is WARP the right model to use, should it 29



### be a different type of model and so there could be 30



### specification error there. 31

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### And these are some of the basic sources of error and I 1



### think there needs to be some type of a conceptualization 2



### as to how these interact, if they interact, and do they 3



### compound so that if in the end the 95... well I guess they 4



### are 90% confidence intervals if what you are really 5



### establishing, I would prefer 95%, but 90% confidence 6



### i ntervals, if they are based just on the sampling error , 7



### are they adequate. 8

9



### If you assume that all of these actually compound, you 10



### could end up stretching those dramatically and 11



### unnecessarily. And so I think that there needs to be 12



### some consideration ab out what is going to compound and 13



### what is not in order to go back to this characterization 14



### of overall uncertainty. I think the answer to this 15



### question probably focuses a bit more on specification 16



### error in that whole topology

. 17

18



### DR. DANIEL SCHLENK : Thank s, Dr. Griffith. Any other comments 19



### on letter A, question 4? Okay let‟s go on to B. Dr. 20



### Coupe. 21

22



### DR. RICHARD COUPE : Richard Coupe. Let‟s talk about the PRZM 23



### model. I just wanted to say that I really like what 24



### Syngenta has done with it. It is a very i nnovative 25



### approach. I particularly like the process

- based work so 26



### you will incorporate whether atrazine use and the 27



### degradation characteristics for atrazine and the 28



### partitioning of atrazine and use soil characteristics to 29



### kind of predict how atrazine move s off. Their initial 30



### results certainly look promising. 31

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### On the other hand, PRZM really was not specifically 1



### developed to look at surface water runoff. It was 2



### developed as a root zone model and hydrology is really 3



### not model directly within the model so I am not sure how 4



### useful the model might be in the long run if you wanted 5



### to look at... say you wanted to look at what process was 6



### moving your atrazine along. If you do not have hydrology 7



### models specifically, you cannot really eliminate or look 8



### at it. 9

10



### And then that kind of restricts your watershed size 11



### unless you figure out a way to handle that. Otherwise, I 12



### think it is a really good and worthwhile effort to move 13



### forward with and we need to have some sort of model, such 14



### like this process base, like the WARP does or PRZM, it 15



### looks really good for future results. That is all I have 16



### for that. 17

18



### DR. DANIEL SCHLENK : Okay. Bob Gilliom. 19

20



### DR. ROBERT GILLIOM : I think the only thing that I want to add 21



### is that the added benefit of continued development of 22



### PRZM is in relation to the database that supports it and 23



### that also may help support moving into also try to SWOT 24



### the STA model
, which may have more applicability to the 25



### watershed scaling up in the long run . I think the 26



### overall effort is really good in that it is just going to 27



### enhance over time the ability to make the modeling 28



### approaches a more sophisticated addition to the tool box. 29

30



### DR. DANIEL SCHLENK : Dr. Lee. 31

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### DR. HERBERT LEE : I concur and have nothing to add. 1

2



### DR. DANIEL SCHLENK : Dr. Portier. 3

4



### DR. KENN ETH PORTIER : Sounds like a good idea if we can make 5



### it work. 6

7



### DR. DANIEL SCHLENK : Any other panel members for B? Okay. 8



### Letter C then. Dr. Coupe. 9

10



### DR. RICHARD COUPE : I really do not have much to add to this. 11



### We have been given an awful lot of ways to fill in data 12



### to kind of look at how to predict this. I do not want to 13



### overwhelm us too much. 14

15



### DR. DANIEL SCHLENK : Okay. Bob. 16

17



### DR. ROBERT GILLIOM : I would just return to the old topic of 18



### what kind of time series model to approach for fill in

. 19



### I th ink if you use a more deterministically

- based 20



### statistical model that has predictors in it like precip 21



### and flow anomalies and so forth, those could actually 22



### prove useful to reconstruct historical records from 23



### historical climate data and historical use data. T hat is 24



### one of the reason I favor that direction as oppose to a 25



### pure statistical fill in. 26

27



### DR. DANIEL SCHLENK : Dr. Lee

. 28

29



### DR. HERBERT LEE : I just wanted to add in another comment that 30



### I was trying to figure out where to fit in and this is 31



### the best pla ce I could figure to fit it. We have had 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### some discussion brought up by other presenters yesterday 1



### about quote s from previous SAPs

. I want to note that 2



### previously, for example

, in April 2010 we were asked to 3



### consider exposures as short as single day maxim ums and 4



### there was a lot of emphasis on trying to estimate a 5



### single day maximum from a weekly sample. 6

7



### And then even in September of 2010 we were considering 8



### ranges . B ut at the time that we were discussing the 9



### hydrology and the water monitoring aspects we were still 10



### keeping single day maxima within the scope of what we 11



### might be trying to estimate. And at the conclusion of 12



### t hat panel we were moving towards area under the curve 13



### for a minimum of a 4

- day moving average and that seems to 14



### be where we are movi ng now. 15

16



### So going forward I think we are interested more in time 17



### periods of four or more days. So some of what we have 18



### suggested in previous SAPs may not be as applicable 19



### anymore now that the time period has shifted. We were 20



### trying to be flexible in t he earlier SAPs depending upon 21



### what came out the biological side and it seems like there 22



### is some convergence now on the biological side that it is 23



### not really a daily maximum that is of interest to human 24



### health, maybe not conclusively, but that seems to be 25



### where we are headed

. S ome of what we said in earlier 26



### SAPs should be taken in the context that that has 27



### changed. 28

29



### DR. DANIEL SCHLENK : Thank you. Dr. Portier. 30

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### DR. KENNETH PORTIER : So kind of building on that theme, 1



### you know, all of the approaches discu ssed up to this time 2



### have centered on the full period of interest, time series 3



### or concentration, right? And the focus has been on being 4



### able to simulate this time series with all of its 5



### correlated temporal value. Well when you actually stop 6



### to think abou t it, the periods of most interest are 7



### really event related; that is those day of high 8



### concentrations that we know are related in some way to 9



### the timing of chemical application and location and 10



### duration of significant rainfall events

. 11

12



### S o what happens i f you only look at these significant 13



### events ? Forget the times of base flow where nothing 14



### interesting is happening. Let‟s look only at the 15



### significant events. I am thinking about this in terms of 16



### -- I am going to get to year to year variability but I 17



### thi nk my bottom line is

-- it's one thing to try to 18



### simulate 20 years of time series and it is another thing 19



### to think of 20 years of events, of significant flow 20



### events that are going to lead to some kind of exposure 21



### that we are going to be interested in. 22

23



### So one is a time series... 20 sets of time series and 24



### another one might be 35 events in those 20 years that you 25



### are trying to understand. Ca n we identify how many and 26



### when significant rainfall events occur in the basin of 27



### interest . With the historical mete orology data, the 28



### answer to this is likely yes. Can we identify which of 29



### these events is likely to product a concentration 30



### increase event at the monitoring station or at the 31



### community water system? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### If we can, then we are able to say something like thi s 2



### rainfall event in this area would produce this kind of 3



### schemograph at the community water center. This next 4



### rainfall event, coming say three days later, would add 5



### this additional bump to that schemograph. Those two 6



### rainfalls relate to one event that I am calling a 7



### concentration increase event. 8

9



### When we can identify each of these concentration increase 10



### events, we can use them to develop distribution such as 11



### maximum daily concentration or duration of days above 12



### threshold concentration during the season or over a 13



### period of record. Can we relate site specific weather 14



### station time series data to these significant rainfall 15



### events? We are thinking initially spatially... spatial 16



### rainfall events relate to an event that happens at the 17



### community water system. 18

19



### Now I am taking one step further back and saying, well

, 20



### really the long

- term data we have is rainfall g auge data. 21



### We have 50, 60, 70 years of daily rainfall g auge data. 22



### You kind of like to look at that in terms of year to year 23



### variability. Well that m eans you have to kind of relate 24



### this point specific rainfall gage data to some area 25



### rainfall so you can pass it through some kind of PRZM 26



### model to figure out an event at community water system
, 27



### or, some kind of regression model. 28

29



### To me that is going to be the hard thing to do, is to 30



### take that point data that we have, that rich rain gage 31



### time series data and try to relate that to something that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is really happening on a rainfall event on a basin

- wide 1



### basis. I do not know anybody who has been successful in 2



### doing that. That is kind of where being able to tackle 3



### year to year variability falls down. 4

5



### Now on the other hand, we had an SAP not too long ago 6



### where we looked at climate change impacts on risk 7



### assessment. I am sitting here thinking a lot of what we 8



### concluded there was that yesterday‟s rainfall is not 9



### necessarily tomorrow‟s rainfall in our current scenario. 10



### Maybe the 20 years of meteorological data that we have 11



### right now is a better tool for looking forward than 60 12



### years of rain g auge station dat a. Maybe we should not be 13



### wasting our time trying to think that far back and just 14



### use the 20 years

, and use that moving forward as our 15



### baseline because the last 20 years are probably a much 16



### better picture of the next 20 years than is the last 60 17



### years a p icture of the next 60 years. 18

19



### And I think I will stop at that point. That is my 20



### thinking. The basic idea being an ultimate approach to 21



### year to year variability might be not to look at it from 22



### a time series but look at it as a set of events and break 23



### i t up into how many events can happen in a year and of 24



### what magnitude and duration of those events. 25

26



### DR. DANIEL SCHLENK : Okay. Other panel members? Okay. Let‟s 27



### go back to you Mr. Thurman, do you have any questions or 28



### clarification? 29

30



### DR. NELSON THURMAN : Okay, it‟s Nelson Thurman. Actually I 31



### want to followup on a comment Dr. Portier had made about 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### using the existing database

. I think one of the comments 1



### in terms of either taking the bias out of it or 2



### accounting for the bias and you said something along the 3



### lines of we need to figure out how to use it. Do you 4



### have any suggestions on how ? B ecause we are wrestling 5



### with that, how do you use that ? 6

7



### DR. KENNETH PORTIER : You 're talking the last 20 years 8



### where we have pretty good meteorological area temporal 9



### spa tial data on rainfall from radar? 10

11



### DR. NELSON THURMAN : I am actually talking about Part A. Your 12



### response to Part A which was on the atrazine monitoring 13



### database and you were... 14

15



### DR. KENNETH PORTIER : Oh yeah, okay. Well I think that is 16



### what we have been talking about all along in question 3 17



### and 4. It is going to depend on the size of the basin, 18



### right, and in the small basins we might be able to use 19



### PRZM to really feed some information to what these events 20



### look like and as the basins get larger somehow w e are 21



### going to have to integrate that information and PRZM may 22



### not be an acceptable model for doing that kind of 23



### integration. 24

25



### I keep thinking , and my understanding from talking to 26



### Coupe and Gilliom

, is that they are really field

- level 27



### based models and so you either have to run it on every 28



### field

, which is something Syngenta showed us in a 29



### previous SAP that they could do with sufficient computing 30



### power and given enough time, they can run every field in 31



### the corn belt of the US and run it for the season and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### accumulate all that information and all I could think of 1



### at the time is more power to them. I would love to see 2



### them do that, that maybe one approach. 3

4



### And then you are god, with a small “g”, you know 5



### everything. Then you can aggregate, you can compu te, you 6



### can do everything that you want assuming the model is 7



### correct, right. Assuming the model works and you are 8



### doing all those kinds of things. 9

10



### I think that is kind of what we have talked about today 11



### and what we have talked about in previous SAPs on this. 12



### We are still working on the same premise that we need 13



### these kinds of field

- based models to do the integration 14



### for us. There is no kind of simple in between. And when 15



### you get the year to year variability that is just another 16



### level of uncertainty that we are having to factor in, and 17



### right now the only way to tackle that is year

- to

- year 18



### measurement of some type. 19

20



### DR. DANIEL SCHLENK : Okay? You have everything you need Mr. 21



### Thurman? 22

23



### DR. NELSON THURMAN : I think we have plenty. I do appreciate 24



### the thought and effort that the panel members have put 25



### into these questions. It has been helpful or us. 26

27



### DR. DANIEL SCHLENK : Fabulous. Let‟s move on then to question 28



### 5 and change out the table there. Dr. Mendez were you 29



### going to read that? You do not hav e to read that whole 30



### paragraph. You can just read the little A if that suits 31



### you. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. ELIZABETH MENDEZ : Good afternoon. So we are going to 2



### have a little bit of a shift now in the types of 3



### questions you are going to be hearing. We have been 4



### talking a lot about the drinking monitoring program and 5



### now we are going to start talking a little bit about the 6



### hazard characterization and the neuroendocrine mode of 7



### action that we have been working with for the past few 8



### years. 9

10



### Before I get started with that I wanted to reiterate 11



### something that Dr. Fowle said earlier this morning. We 12



### are at this point in time looking at these data. We are 13



### not really doing the risk assessment. What we are trying 14



### to do is come to you to seek your advice on how we are 15



### approach ing, where the approach is that we are proposing

, 16



### and how we are interpreting these data as we may 17



### eventually start applying them to our risk assessment 18



### process. So with that I am going to ask Dr. Cooper to 19



### join me at the table and then I will start askin g the 20



### questions. 21

22



### Charge question 5 has to do with the neuroendocrine mode 23



### of action and the disruptions to the HPG access that ha s 24



### been the basis of our risk assessment in the past. And 25



### the first question that we have is currently available 26



### data show th at in the rat, a brief exposure, as brief as 27



### four days to low levels of atrazine can elicit decreases 28



### in LH. Please comment on the biological plausibility of 29



### these brief changes leading to an adverse outcome taking 30



### into account typical variability and how long and how 31



### much an LH surge reduction is needed to cause the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### observed adverse effects; i.e., disruptions in cyclicity, 1



### delayed puberty and prostatitis. 2

3



### DR. DANIEL SCHLENK : Our first lead discussant on that is 4



### Dr. O'Byrne? 5

6



### DR. KEVIN O'BYRNE : First of all, I'd like to say that Dr. 7



### Timms and Jerde are not going to participate as associate 8



### discussants of this question because there is no obvious 9



### link between LH secretion and prostatitis. So they are 10



### going to convey their deliberations in charge questi on 11



### number 7. 12

13



### So we can see here that four days exposure to low levels 14



### of atrazine declines LH secretion. But if we consider 15



### what we heard yesterday concerning a paper that‟s 16



### published in 2001

, by Goldman et al. that showed that 17



### absent at 100 milligram s per kilo per day, which is 18



### certainly not a low dose by any stretch of the 19



### imagination to ovariectomized estrogen

- primed Sprague

20



### Dawley rats attenuated the LH surge by a mere 54 percent, 21



### and that was AUC. Actually the peak levels of LH were 22



### not significa ntly suppressed in that paradigm. 23

24



### I'll remind you that two

- day treatment with the same 25



### dosage had absolutely no effect on the LH surge. So the 26



### question is, might the surge reduction cause these 27



### disturbances to cyclicity and the onset of puberty. 28



### Well , we know from this historical data of laws from 2000 29



### that 50 or more milligrams per kilograms per day, 30



### starting on postnatal day 22, which is when rats are 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### usually weaned, did delay puberty. However, 12 .5 and 25 1



### milligrams per kilogram per day had no eff ect on puberty. 2

3



### And when you consider that they were being treated with 4



### 25 milligrams per kilogram per day for almost two weeks 5



### and it had no impact on puberty or cyclicity, then it's 6



### difficult to image that a 4

- day treatment at 100 7



### milligrams per kilo grams for just four days would impact 8



### on those systems. That would be unlikely, in my view. 9

10



### Now we know from the work way back in the early 70s by 11



### Everett that there is a huge variation in the levels of 12



### LH in the spontaneous surge, and I think this wa s touched 13



### on in the September meeting. And we are talking about a 14



### range here of 200 to 1000 nanograms per mil. And despite 15



### that huge range, the rate of ovulation

-- in other words, 16



### the number of ova that were expelled from the ovary was 17



### not different. 18

19



### So there is a huge redundancy within this system, and 20



### that‟s perhaps just as well because without reproduction, 21



### we wouldn't be sitting around this table discussing 22



### atrazine. Now if you think about a hypothalamic level, 23



### Fred Carr (phonetic) showed some y ears ago that you only 24



### need 10 percent of the GnRH surge to drive a full

- blown 25



### LH surge in the U ; s o again, huge redundancy. 26

27



### So perhaps this 50, 54, 55 percent reduction in LH that 28



### is seen with 4

- day treatment with a hundred milligrams 29



### per kilograms pe r day is unlikely, again, to

-- in my 30



### opinion

-- to disturb cyclicity and other aspects of 31



### reproduction. And there is a sort of slight digression. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### All a n Herb i son published a paper in 2008 where he used a 2



### transgenetic model to selectively knock down Gn RH 3



### neurons, and he showed quite convincingly that you only 4



### need 12 percent of GnRH neurons in a mouse brain to go 5



### through a normal puberty and have your first estrous 6



### cycle. So again, that‟s another example of a huge 7



### redundancy and robustness within this control system. 8

9



### But perhaps, what's more important and troubles me is the 10



### consideration, which I mentioned 16 months ago, that the 11



### toxicological doses that we are discussing are so far 12



### removed from what one would be exposed to in the normal 13



### environment unless, of course, your little rat manage to 14



### nibble it's way into the subnet atrazine in the farmer's 15



### shed. I mean, I think this is something that we, on this 16



### side of the table anyway, are quite concerned about and I 17



### don‟t know how that‟s really going to be addressed. 18

19



### I am delighted to hear that people are beginning to lower 20



### the dosage that they're exposing their animal models to, 21



### but there is a real need to think outside of the 22



### toxicological mindset. So the other point that I would 23



### like to make is t hat we saw some rather nice data from 24



### Syngenta yesterday that we simply cannot ignore . T hey 25



### showed that 50 milligrams per kilogram for four days 26



### attenuated the spontaneous LH surge by only 50 percent, 27



### again, in Sprague

- Dawley rats. 28

29



### So we've heard a lo t of discussion about Long Evans 30



### versus Sprague Dawley. Well here there are two studies 31



### in Sprague

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### it's speaking volumes to how much of a reduction is 1



### taking place in this surge

- generating mechanism, which we 2



### kno w has a huge built

- in margin of safety in terms of 3



### reproductive outcome in terms of ovulation. 4

5



### T hey also showed that 10 milligrams per kilogram for four 6



### days had absolutely no effect on the surge at all. I'll 7



### just remind you that 10 milligrams per kil ogram for four 8



### days is a whopping great dose of atrazine. So, I also 9



### feel that the spontaneous LH surge may be much more 10



### fragile and vulnerable to perturbations compared with the 11



### steroid

- induced, because in the spontaneous circumstance 12



### you‟re relying on t he ovary to release a certain amount 13



### of estrogen
, which is driven by what one can only assume 14



### as a normal functioning pulse generator ; i n other words, 15



### pulsatile release of LH, and obviously FSH. We can‟t 16



### ignore FSH as well. 17

18



### I f you contrast that with p ouring in buckets of estrogen 19



### or estrogen plus progesterone in your ovariectomized 20



### model, then I think we should focus in on those data that 21



### we saw yesterday in the gonadol intact animals. 22

23



### M y conclusion is that four days exposure at the doses 24



### that we a re considering is unlikely to have effects on 25



### onset of puberty and the ovarian cyclicity. I am also 26



### quite pleased to see that there is a move to use other 27



### models, apart from the rat, and I think Syngenta need to 28



### be highly commended for putting some money into sort of 29



### primate research. I do wonder why that has taken so long 30



### to be put into effect, because I think we do need primate 31



### data. So I think that‟s all I have to say. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Thanks. Dr. Akana? 2

3



### DR. SUSAN AKANA : I'd like to add only t wo personal points of 4



### view. One is, I totally concur with Dr. O'Byrne. 5

6



### W hat I do want to add is that it is highly unlikely that 7



### the doses we're using giv ing for four days in adult rat 8



### are going to have adverse reproductive outcomes. 9



### However, what we don‟t know is, if you go back in, say 10 10



### days later, and give them a second exposure, if they'll 11



### have an additive or interactive effect. 12

13



### So in my person view, it's important to recognize that 14



### when these animals have received such a dose and you see 15



### no apparent adverse outcome, that doesn't mean they're 16



### necessarily a normal animal from that point on. T he 17



### second personal point of view I have is, I'm very mindful 18



### from the datasets and the docket and that we've seen 19



### yesterday that very frequently animals a dministered the 20



### atrazine have a drop in food

- take immediately

, and a drop 21



### in body weight. 22

23



### In my world of physiology, this is not a normal behavior 24



### in an animal. It is something to be very mindful of how 25



### these animals are going into negative energy bal ance; 26



### their metabolism is shifting. And what's more important 27



### in this case of atrazine is they are choosing not to eat. 28



### And the results on their physiology can look similar to 29



### animals, a different cohort, where you artificially food

30



### restrict them. 31

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### So we know from some studies in the literature and some 2



### nice studies done by Susan Mo z (phonetic) here with food 3



### restriction that, yes, if you decrease food intake, you 4



### get a different metabolic shift, and they look similar to 5



### the anorexia that you might s ee with atrazine 6



### administration. But there are differences in the brain 7



### neurocircuitry and that‟s something to be mindful of as 8



### you pursue the atrazine studies. 9

10



### DR. DANIEL SCHLENK : Okay. Dr. Jerde, do you have any 11



### comments? You‟re going to delay those to seven, right? 12

13



### DR. TRAVIS JERDE : Yes. 14

15



### DR. DANIEL SCHLENK : Do you have anything on the 16



### nonprostatitis endpoints? No? Yes? 17

18



### DR. TRAVIS JERDE : Well, the only thing that I would add is, 19



### I've sort of alluded to it a little bit before. The 20



### mechanisms of action that we haven't really defined yet 21



### could turn out to be very important. I would encourage 22



### more research in this area looking at sibling mechanism, 23



### genetic imprinting and things like that that may occur

. 24



### B ecause these hormonal changes, systemic c hanges
, are 25



### oftentimes associated with those sorts of more subtle 26



### effects that probably ought to be addressed. 27

28



### DR. DANIEL SCHLENK : Thanks. Dr. Roby, next? 29

30



### DR. KATHERINE ROBY : I have no more to add. 31

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### DR. DANIEL SCHLENK : Okay. And Dr. Timms, do you ha ve 1



### anything to add? 2

3



### DR. BARRY TIMMS : At this point, no. We'll refer to our 4



### charge question. 5

6



### DR. DANIEL SCHLENK : Okay. Other panel members, anything to 7



### add? Yes, Dr. Horseman? 8

9



### DR. NELSON HORSEMAN : I want to go in the charge question 10



### here. It says that these perturbations are being 11



### considered as the basis for atrazine risk

- assessment. So 12



### I hear a lot of skepticism, and this may be just stating 13



### something that Dr. Jerde just asked in a different way, 14



### but my question is does the use of this LH surge, as a 15



### sentinel effect, plausibly capture an apparent 16



### hypothalamic mode of action that is, as yet, poorly 17



### understood at a site or molecular level, but is important 18



### to understand. 19

20



### In other words, it seems to me like we're being asked to 21



### consider whether t his effect that is hard to understand 22



### its particular physiological meaning , is telling us 23



### something else. And if that‟s what we're being asked to 24



### consider, we need to see if we can give you better advice 25



### as to how to go about finding that something else, it 26



### seems to me. And maybe that‟s a poorly worded question 27



### but maybe not. 28

29



### DR. DANIEL SCHLENK : Other comments? Dr. O'Byrne? 30

31

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### DR. KEVIN O'BYRNE : I mean, the surge generating mechanism in 2



### the rodent is a little bit odd. But nevertheless, it is 3



### a centra l mechanism and it's reasonably well understood. 4



### And if you do perturb it, then you are going to impact on 5



### the reproductive cycle because it's part of that control 6



### system. So if you don‟t have a surge then you‟re not 7



### going to have a normal estrous cycle, and that would be 8



### true in other species as well, so it is quite important. 9

10



### T he problem is the dose that is used to completely wipe 11



### this out is a hundred milligrams per kilo. So I 12



### appreciate what you‟re saying. It is important. And 13



### these guys have alre ady shown the effects of atrazine on 14



### LH pulses, and we heard a lot yesterday about LH pulses 15



### are so important. Well of course they are, but they have 16



### to give a hundred milligrams per kilo and they still 17



### don‟t see any significant effect. I'm not quite sur e 18



### when that was published and Ralph will remind us. So in 19



### the context of the pulse generator, pulsatile LH 20



### secretion, you need even higher doses. 21

22



### DR. DANIEL SCHLENK : Dr. Roby? 23

24



### DR. KATHERINE ROBY : I think your point is a good one though. 25



### I think the m easure of LH is really just a measure of 26



### what's happening upstream. I think everyone agrees to 27



### that and there are a lot of studies, although they would 28



### be difficult studies to do to look at what's changing in 29



### the hypothalamus. But I think it's also inter esting to 30



### note the studies where during the LH

- dependent portion of 31



### gestation, resorption occurs, and I wonder if those point 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### to some alternative or additional points of input of 1



### atrazine in that maybe the regulation of LH at that point 2



### is different than t he regulation occurring during the 3



### surge. But I think the point of understanding the 4



### molecular mechanism is important. 5

6



### DR. DANIEL SCHLENK : Dr. Horseman? 7

8



### DR. NELSON HORSEMAN : Okay. To come around to a different 9



### part of this , s o we've talked a lot abou t roots of 10



### administration ; and may mean gavage or in the food or in 11



### the water or whatever . B ut if the EPA is asking us to 12



### help them understand whether this apparent hypothalamic 13



### mode of action is relevant for the basis of atrazine 14



### risk

- assessment, I wonde r if we shouldn't see data where 15



### atrazine is applied to the hypothalamus. 16

17



### I don‟t know if there is any literature out there. This 18



### is a fairly straight

- forward type of ICV infusions, 19



### because

-- I'm uncomfortable with the notion, well 20



### there's a mode of action that we are hanging a general 21



### physiological toxicological affect on, but then everybody 22



### knows for sure that that particular mode of action isn't 23



### directly coupled to an adverse outcome in terms of 24



### ovulation, and I keep saying that. 25

26



### DR. KEVIN O'BYRNE : I think if you knock the LH surge 27



### sufficiently then you do impact on the other aspects of 28



### the reproductive cycle. So from that point of view, I 29



### mean, I think it is a good marker. 30

31



### DR. DANIEL SCHLENK : Dr. Akana? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. SUSAN AKANA : I had a conversation with Dr. H anda 2



### yesterday and actually almost the same conversation in 3



### the April SAP. 4

5



### In the April SAP he presented some c

- fos information in 6



### the brain and I asked him specifically, "Did you look in 7



### the paraventricular nucleus," that being my favorite p art 8



### of the hypothalamus. I n conversation yesterday he said, 9



### "They looked extensively through the hypothalamus. 10



### They're looking at c

- f os an hour after atrazine injection 11



### -- and I'm sorry I can't remember the dose

-- b ut the 12



### hypothalamus was total ly quite. 13

14



### I did ask him in April, "Check the distributed CRF 15



### system ; l ook at amygdal a ." And yesterday he told me, 16



### yes, they saw some c

- f os in parts of the amygdala. So 17



### that‟s what I know of the hypothalamus c

- f os studies. M y 18



### comment about, for instance, ICV injection into the brain 19



### is remember the solubility of this compound is pretty 20



### poor. It almost has to be a crystalant implant. 21

22



### DR. DANIEL SCHLENK : Okay. Any other input? Yes, Dr. 23



### Griffith? 24

25



### DR. DANIEL GRIFFITH : A question that I think is relevant to 26



### answers 1 through 3 questions; what would be some good 27



### dose levels to explore then if you think 100 milligrams 28



### per kilogram is too high? What would be some good dose 29



### levels, lower dose levels to explore? 30

31

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### DR. KEVIN O'BYRNE : Well, we rely on you guys to tell us what 2



### make it in the water. And my understanding is its so 3



### low, and that‟s what we should be considering, in my 4



### opinion. We should be administering the doses that 5



### replicate the maximum levels that are found in the water 6



### and it should be given chr onically or intermittently. It 7



### doesn't really matter. Those would be just part of the 8



### experimental strategies . T his hopefully will be what 9



### will be done more carefully in the primates, because when 10



### you start working with primates you control and design 11



### y our experiments exquisitely. The rat guys

-- and I'm 12



### now a rat guy

-- tend to be a little complacent. 13

14



### DR. DANIEL SCHLENK : Yes, Dr. Timms? 15

16



### DR. BARRY TIMMS : Actually, I think the answer to that 17



### question is more relevant if you consider the levels that 18



### m ay be predicted or found in humans because those are the 19



### levels at which we are exposed and those would be 20



### relevant to the dose exposure that Dr. O'Byrne was 21



### talking about. 22

23



### DR. DANIEL SCHLENK : Yes, Dr. Roby? 24

25



### DR. KATHERINE ROBY : Is also though seems to me that the 26



### experimental approach breaks down two different but 27



### important questions, and one is the biology and what 28



### happens with an exposure to atrazine, and secondly is 29



### what is the real risk factor? And one is assessing 30



### effects at realistic exposure lev els, and one is doing 31



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### DR. DANIEL SCHLENK : Dr. Horseman? 2

3



### DR. NELSON HORSEMAN : To bring in a concept from a different 4



### SAP we had recently

-- and maybe that‟s the source of 5



### this question I'm asking

-- mov ing toward the notion of 6



### an adverse outcome pathway requires understanding the 7



### biological substrates of that adverse outcome. And from 8



### the diagrams we've seen here

, you know, we give to the 9



### organism and something happens at these lower levels of 10



### organizat ions. We have no information about those other 11



### levels of organizations. 12

13



### I think the question about these relevant doses and such, 14



### also can break down. If you consider the fact that we're 15



### going to understand this toxicology or ovarian physiology 16



### from studies of a small number of animals, relatively 17



### small number of animals, but millions of people are going 18



### to be expose to this. 19

20



### So I don‟t think it's as simple as saying nothing happens 21



### as three parts per billion and only one and a half 22



### million people were exposed to more than three parts per 23



### billion. You know, that‟s you guy's problem there, 24



### essentially, but understanding the biology and from this 25



### toxicology in the 21st century notion of adverse outcome 26



### pathways and that sort of thing

, I think you‟re a long 27



### ways away from that for this hypothalamic mechanism that 28



### seems to be proposed. That‟s my only comment. 29

30



### DR. DANIEL SCHLENK : Okay. Dr. Chambers? 31

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### DR. JANICE CHAMBERS : I just want to pick up the same thought 2



### that Dr. Horseman was having. Again, the last SAP we 3



### were talking about the mechanisms involved at the adverse 4



### outcome pathways. When so little is known about the 5



### mechanism

, then it's really hard to tell whether this is 6



### a biologically plausible phenomenon in the rat compared 7



### with the human or not anyway . S o it just really seems 8



### like it's very important to try to identify some of the 9



### real mechanisms going on and find out whether those are 10



### relevant in humans. 11

12



### DR. DANIEL SCHLENK : Yes, Dr. O'Byrne? 13

14



### DR. KEVIN O'BYRNE : Well, I think the comme nts made by Tony 15



### Plant yesterday that th ere should be a focus on the pulse 16



### generator might be something that should be explored a 17



### little bit more. But I'll remind you that Ralph has 18



### already shown that LH pulses are not affected with 100 19



### milligrams per kil o. 20

21



### DR. DANIEL SCHLENK : No further comment from the panel at this 22



### point? Dr. McManaman? 23

24



### DR. JAMES MCMANAMAN : I t look s like it's 50 mgs per kg does 25



### reduce the LH surge . T his is from Syngenta data . S o I 26



### think that we're in the ball

- park of

-- and that 27



### corresponds to about 500 PPMs

-- so we're not too far 28



### off . W e're in the toxicological area

, but we're not so 29



### far . W e're getting close to the physiological area, I 30



### think. 31

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### DR. DANIEL SCHLENK : Okay, alright. So we'll throw it back to 2



### the EPA folks. Do you have comments requiring 3



### clarification? 4

5



### DR. RALPH COOPER : I just have a point of clarification, I 6



### think, for dose selection and what seems to this panel to 7



### be a disparity between environmental levels and the doses 8



### that are used in laboratory studies. 9

10



### I think it's a good thing that we're seeing this 11



### disconnect between what's needed in order to identify a 12



### potential adverse effect in the test species and what's 13



### in the environment and what's potentially exposure to the 14



### humans . A nd this didn't just ha ppen by chance with a 15



### chemical that‟s been around for 50 years

, t here have been 16



### programs to maintain low concentrations. 17

18



### I look at it a little bit differently. I think what we 19



### are looking for is, as we felt that, as we look at the 20



### mechanisms or the po tential mechanisms involved in the 21



### test species, we want to make sure we're using the right 22



### set of tools, measuring the right parameters so that we 23



### can be sure we're making a good guess as to what's going 24



### on. 25

26



### And what we're doing essentially is reinfor cing the 27



### safety factors, if you will. I mean, look at what we're 28



### talking about. We're talking about very slow or very 29



### small differences in previous LOAELs, NOAELs, points of 30



### departure that have been used for the risk assessment. 31



### We may be tweaking the t iming of those events and things 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### like that but we're pretty much still at the level we 1



### were back in 2000 when we did the six

- month evaluation 2



### and you had the 1.6 NOAEL and 3 point something LOAEL. 3

4



### What's changed maybe

-- and I don‟t think it's 5



### earthsha king. It's not an order of magnitude

-- i s the 6



### acute exposure, if you will, for four days. Previously, 7



### it's my understand ing it was 10. And we're identifying 8



### something in an intact animal

, and I certainly agree with 9



### O'Byrne. He made a very good point w hen he said, "The 10



### less contrive that you have your experimental model 11



### perhaps the better information you'll get. Study an 12



### intact animal. Study that animal at the times when you 13



### anticipate the effect to be taking place that you‟re 14



### looking for. In the int act animal you'll see lower 15



### LOAELs and NOAELs. 16

17



### When you give estradiol to an animal, you've taken its 18



### ovary out, you give estradiol to it; the rules change. 19



### You can still use it as a model and get information, but 20



### this dose response information falls apart. Secondly, 21



### when you give estradiol plus progesterone, which is what 22



### most of the registrant studies are, I've seen that 23



### totally blow out in effect that you may have seen 24



### elsewhere. 25

26



### So these are not all comparable studies. When you talk 27



### about the ovexed animal, I mean, they're just as 28



### different as the monkey and the rat . T hey're different 29



### tools and they are different approaches that you use to 30



### get at things. But the two main points is that the 31



### LOAELs that we see in an intact animal

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### concur with. It's really difficult to say that we see 1



### changes. I don‟t even recall the percent change in the 2



### amplitude of the surge of the area under the curve in our 3



### data but it certainly wasn't going to be one that John 4



### Everett or many of the people wh o later on looked at the 5



### threshold level of LH for ovulation. 6

7



### The question that always remained

-- and I worked with 8



### John Everett for years

-- and the question was, well what 9



### is the rest of that LH doing then? Is it just there as a 10



### frill or is there s ome other important function that that 11



### may ha ve? If you look at the literature on reproductive 12



### physiology, there are a lot of other things that we 13



### haven't explored. 14

15



### DR. DANIEL SCHLENK : Yes, Dr. Fowle or Steve, did you want to 16



### say something? 17

18



### DR. STEVEN BRADBURY: Yes. Along the lines of what Ralph was 19



### just saying, but also what Dr. Horseman was saying, I 20



### guess one of the things is we're at the point now is from 21



### a regulatory perspective we want our decision to be 22



### informed by the best available science. I mean our 23



### decisions must be informed by the best available science. 24

25



### However, we don‟t have the luxury of waiting until all 26



### the T's and crossed and I's are dotted. So at various 27



### periods of time we have to pull together the science and 28



### take advantage o f that best available science and make a 29



### decision at that particular point. And we have our re

30



### registration view process that‟s periodical ly come back 31



### and we keep looking at these chemicals in repeated 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### fashion in the future so we can add additional scienc e as 1



### we proceed. 2

3



### So what Dr. Horseman is saying, at one point in time, 4



### we're kind of faced with a dilemma. It's not likely 5



### we're going to be able to have a lot of new data along 6



### these lines in the next couple of years, so to the extent 7



### that we don‟t h ave data that would get at these issues

, 8



### what would really help us is what kind of guidance can 9



### you give us in terms of stitching together the best 10



### assessment we possibly can, given the science we have 11



### right now. 12

13



### So one of the things we may be hearing, and I'm not 14



### exactly sure of the clarification, how, for instance, Dr. 15



### O'Byrne, you were saying that at the environmental levels 16



### that we would encounter with respect to atrazine, would 17



### not likely have an impact on reducing the LH surge. 18

19



### We could interp ret that a couple of ways. One would be 20



### that we would need to basically sort of eliminate that 21



### surge to be able to

-- well, I might be saying this 22



### wrong. If we're not seeing the effect of the LH surge 23



### disease, environmental rapid exposures are those high er 24



### level doses where LH surge events intact might serve as a 25



### node
, which would lead to a variety of adverse impact. 26

27



### Is there any advice or guidance you'd give us for how we 28



### might use that data in the context for all the other data 29



### we have available to try to stitch together as best we 30



### can right now? What effect, if anything, atrazine might 31



### be causing? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. KEVIN O'BYRNE : I think the data we saw yesterday, for 2



### example, from Syngenta where they showed that 50 3



### milligrams caused a reduction of about 50 pe rcent of the 4



### surge is very clear and un ambiguous . And with 10 5



### milligrams there is no effect. I mean, that‟s hard 6



### evidence and I think you can work with that. 7

8



### W hat I was trying to explain to you is that a 50 percent 9



### reduction in the LH surge, in the s pontaneous LH surge, 10



### may have absolutely no impact on the ovulation and the 11



### cyclicity that is driven by that. So I think you've got 12



### some very hard data there. And so, I think that‟s 13



### important. 14

15



### The other thing is, the discussion yesterday about the 16



### pr oblems associated with the surge generating mechanism 17



### in the rat as opposed to other species, and particular ly 18



### human, is something that you ideally would like to have 19



### that data. But if you don‟t have it then you have to go

, 20



### as you say , with the best that you have. 21

22



### So perhaps in the timeframe that you‟re talking about, 23



### you are not going to get any further data but you've got 24



### hard evidence now. And when some primate data does come 25



### out on terms of pulsatility, it would be just interesting 26



### to see how that fits because there's no doubt about it

, 27



### what Tony Plant said yesterday in terms of the LH pulse 28



### generator, you don‟t have a surge unless you've got a 29



### normal functioning pulse generator. So you know you've 30



### got a normal functioning pulse generator at 10 mi lligrams 31



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### spontaneous normal surges. So I think you've got some 1



### good data. 2

3



### DR. DANIEL SCHLENK : Any other comments? Okay. Back to the 4



### agency, is this the answer that you need? 5

6



### DR. ELIZABETH MENDEZ : We've heard a lot to think about, so we 7



### appreciate the input. So if you'll allow, I'll keep 8



### going then to charge question number 6. And charge 9



### question number 6 has to do with some advice or some 10



### comments that we've heard from the panel back in 11



### Septemb er about the significance of 1

- day versus 4

- day 12



### exposure. And in response to those comments, our 13



### scientist went back to the lab and conducted some 14



### studies. And we've sort of started alluding to them in 15



### the previous question, but we are going to ask the 16



### q uestion anyway. Please comment on the potential 17



### relevance of 1

- day exposure to elicit an adverse outcome 18



### and the significance of an increase versus a decrease in 19



### LH. 20

21



### DR. DANIEL SCHLENK : Before we move on, I just want to remind 22



### the lead discussants of ea ch of these questions, it's 23



### your responsibility to summarize all of the panel's 24



### discussions for that. And I know that, based on the last 25



### question, it was somewhat widespread and unclear. So 26



### again, that‟s sort of the responsibility of the lead 27



### discussants to do that, so I just want to make sure 28



### you‟re aware of that as we go forward. So with that, Dr. 29



### Roby? 30

31

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### DR. KATHERINE ROBY : Okay. This question does, I think, 2



### segway from our discussion that we've been having. And I 3



### think to specifically address the absolute question on a 4



### 1

- day exposure, we have to go to the new data that was 5



### presented with the ongoing study, as I understand it, 6



### where the model system of ovariectomy and estradiol 7



### replacement was used in looking at a single versus 8



### multiple

- day exposur e. 9

10



### A single day exposure elicited an augmentation of the LH 11



### surge, so that‟s 1

- day exposure. So what would be the 12



### significance or outcome of that

, probably very little to 13



### nothing. An augmented LH surge, we've already talked 14



### about the excess in the LH surge in what we considered to 15



### be the redundancy in the mechanisms downstream of the LH 16



### surge. 17

18



### So probably ovulation would have occurred just as it 19



### would have if the surge had been at those "normal 20



### levels." Now, the significance of a decrease; the n ew 21



### experiment shed some additional light and I think 22



### highlights the complexity of the system. And I think the 23



### model system was appropriate to address the question. 24



### T he results, again, are interesting in the augmentation 25



### of the surge and it's relation to the progesterone that 26



### was probably secreted by the adrenal gland with the 27



### atrazine exposure. 28

29



### T hen, with the subsequent administrations and either the 30



### down regulation or desensitization of the continued 31



### exposure to progesterone each time, and then you s ee the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### attenuation of the LH surge

. I know this gets into 1



### multiple exposures , but if there were a single exposure 2



### that resulted in a decrease, to directly answer the 3



### question again, the overall outcome again would be 4



### probably pretty minimum. If the LH su rge was inhibited 5



### enough, it would result in an anovulatory cycle . F rom a 6



### practical standpoint, there is no ovulation , and the 7



### cycle would probably be extended slightly in a rodent and 8



### a couple of days maybe in a woman. But subsequent cycles 9



### would then b e normal. This is just single exposure. 10

11



### So, I guess, bottom line is a single exposure would 12



### really have minimal effect downstream of the effect on 13



### the LH surge. I think something that the study presented 14



### that goes back to the pretext to the question is; 1) is 15



### the effect on the LH surge due to the peak exposure to 16



### the atrazine or is it due to this accumulation and this 17



### potential pseudo steady state ? O r is it really just that 18



### multiple exposures eliciting those multiple increases in 19



### progesterone are

-- you need to have so many exposures to 20



### have the down regulation in response to progesterone

, 21



### which is maybe different than reaching a steady state or 22



### a pseudo steady state level. So multiple

, short 23



### exposures may still be relevant to effect. And I think 24



### th at this experiment leads to more questions, based on 25



### the result. 26

27



### The other point that is in the discussion, but is not 28



### addressed at least in the data that‟s been presented 29



### recently

-- and I think it's an important question

-- is 30



### when during the cycle i s the exposure relevant? So these 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### exposures were done at 1300, I believe, which is really 1



### basically the onset of the LH surge. 2

3



### If exposure occurred at 0900 or the previous day, would 4



### there be any effect on the surge? I don‟t know. I guess 5



### that‟s to be shown. We certainly know of other compounds 6



### that, when administered, based on time of day, will 7



### either shut down the surge or have no effect on the 8



### surge. And atrazine could be functioning through similar 9



### mechanics. We don‟t know. 10

11



### So, I think tim e of exposure is still a question that‟s a 12



### little bit open

. I think when we want to translate that 13



### then to the human, obviously the amount of time within 14



### any menstrual cycle further away from the LH surge is 15



### significant relative to the time near to the LH surge. 16

17



### I think the other question then related to pulsatile 18



### exposure versus what might be a pseudo steady state 19



### relates to the amount of time that the drug might need to 20



### be at a certain level to elicit a change in a woman 21



### compared to in a rodent, give n the different dynamics of 22



### the LH surge in women versus rodents. 23

24



### I think those are still some questions that are 25



### uncertain. Okay. So in summary, directly for the 26



### question, 1

- day exposure, I think, really will have 27



### little effect on ultimate outcomes in fertility. 28

29



### DR. DANIEL SCHLENK : Okay. Dr. Akana? 30

31



### DR. SUSAN AKANA : I have nothing to add. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Okay. Dr. O'Byrne? 2

3



### DR. KEVIN O'BYRNE : I concur with what's been said. But 4



### actually, the 2

- day exposure, I just realized, 2

- day 5



### expos ure had absolutely no effect, so that‟s quite 6



### relevant. It's giving us a little bit more information 7



### about that window that you are sort of asking about, so 8



### you've already got part of the answer. 9

10



### DR. DANIEL SCHLENK : Dr. Roby? 11

12



### DR. KATHERINE ROBY : If I could comment though; I think what 13



### we don‟t know is if that isn't due to now two exposures 14



### to progesterone and down

- regulating that system and the 15



### sensitivity or adjusting the sensitivity , s o the duration 16



### of exposure to progesterone in combination with exp osure 17



### to the drug atrazine. 18

19



### DR. KEVIN O'BYRNE : But I think one of the questions these 20



### guys were asking was if they started the treatment at a 21



### different phase of the cycle

-- you've only got four 22



### days, so I think that is relevant to the question that 23



### was being posed. 24

25



### DR. DANIEL SCHLENK : Sure. 26

27



### DR. KATHERINE ROBY : Can I also add

-- 28

29



### DR. DANIEL SCHLENK : Sure. 30

31

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### DR. KATHERINE ROBY : I did want to say that the rodent 2



### obviously is probably not the optimum model system to 3



### really look at time during the cyc le. The estrous cycle 4



### is so short. It's not a true luteal phase, for example. 5



### Probably other model systems, obviously, like the 6



### nonhuman primate would be excellent to look at what 7



### effect exposure across different times of the cycle would 8



### actually have. 9

10



### DR. DANIEL SCHLENK : Yes, Dr. Cooper? 11

12



### DR. RALPH COOPER : I understand your comments and they are 13



### right on target with the question that was asked in the 14



### September SAP. We didn't have all that time to address 15



### them, but the one question that we didn't g et to, and I 16



### think is still possible, is let's say for example you 17



### dosed on estrous only: there is a literature that says, 18



### and again goes back to Dr. Everett's lab where if you 19



### give one dose of progesterone, on the estrous early 20



### diestrous

- 1, I think it is, it would delay ovulation one 21



### day, so there is another example of timing, and timing is 22



### critical. 23

24



### O ne other point that I'd like to make is that we've done 25



### studies with other chemicals that show that if we dose 26



### the animal between the hours of two and fo ur in the 27



### afternoon, a vaginal pro

- estrous, we can get a blockade 28



### total 100, which I guess you'd consider relevant, with 7 29



### milligrams per kilogram of the chemical. But yet, if we 30



### drift back in time and give it earlier and earlier, so 31



### now the peak, the are a under the curve
, is earlier that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### day

-- so this just emphases the critical nature of the 1



### timing

-- that there would be no effect at all. 2

3



### I mean, you know, it's t ox , you like to have effects

. 4



### They are just so robust they last forever, but the real 5



### na ture of this cyclical beast, the circadian rhythm, 6



### makes it such that timing is important. And that takes 7



### me to the question of why does one guy got 50 milligrams, 8



### another guy has got 10 and another guy has got 5 9



### milligrams

, that‟s a LOAEL? Well, if you go back and 10



### look at those studies you'll see, in those cases, timing 11



### wasn't always the same, and I think that could be 12



### contributing to the part of this. That cycle, there are 13



### certain things that are sensitive at different portions 14



### of the cycle. 15

16



### DR. DAN IEL SCHLENK : Okay. The rest of the panel? Yes, Dr. 17



### Lee? 18

19



### DR. HERBERT LEE : I want to tie this back to the hydrology a 20



### little bit and ask a different question. So I hear you 21



### saying that one exposure may have a few short

- term 22



### effects
, but really no long

- term effects. But if you‟re 23



### living in a small watershed community water system area 24



### you may get a high dose once a year because there is a 25



### one peak and then it comes back down. Is there any 26



### consideration as to what happens if you have a once 27



### annual 1

- day exposure or, in a rat, maybe you want to 28



### translate this back on the length of the cycle, it'll be 29



### a lot faster than annual for a rat, but that sort of slow 30



### repeated exposure. 31

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### DR. DANIEL SCHLENK : Yes. I think we're going to kind of get 2



### to that in some of the later questions, actually. Yes. 3



### Feel free to answer, if you like. 4

5



### DR. KATHERINE ROBY : Well, I think that even a once annual 6



### exposure that
, say in worse

- case scenario complete ly 7



### inhibit the LH surge

, would still have very minimal 8



### effect on your overall reproductive capacity. You would 9



### have one anovulatory cycle. In reality, women very often 10



### have anovulatory cycles. It's not an uncommon event. 11

12



### DR. DANIEL SCHLENK : Okay. Any other comments from the panel 13



### on this particular question? Okay. Let's go ahead and 14



### break for our afternoon break here. Let's try to be back 15



### at 2:35. 16

17



### DR. DANIEL SCHLENK : Okay. Let's go ahead and get back at it 18



### if we can. Let me just remind the panel members if you 19



### do have discussions with agency folks you need to s tate 20



### that for the record kind of what you were talking about, 21



### in terms of your outcomes there. Yeah, only if it's 22



### relevant to the charge questions, of course. Don‟t get 23



### too personal there. So let's go ahead and get started 24



### on number 7 and we're going t o read that into the record. 25

26



### DR. ELIZABETH MENDEZ : This one has to do with the prostatitis 27



### findings that we ' re seeing in the rat and that we're 28



### seeing after exposure from PND

- 1 to PND

- 4. And the 29



### question that we have is, given the biological processes 30



### i nvolved in atrazine

- mediated prostatitis in rats, please 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### comment on the human relevance of these findings in rats, 1



### for the overall hazard characterization of atrazine. 2

3



### DR. DANIEL SCHLENK : Our lead discussant on that is Dr. Timms. 4

5



### DR. BARRY TIMMS : This morning we were exposed to a very 6



### sophisticated , statistical model . T his afternoon I'd 7



### like to expose you to some sophisticated anatomical 8



### models. I f I could have the slide up I'll be referring 9



### to that during our presentation. 10

11



### I'll present some backg round information and then address 12



### our responses to the agency, but I think it's important 13



### just briefly to summarize some of the information 14



### regarding prostatitis and it's relevance to the human 15



### condition. In men

, younger than 50 years of age, it's a 16



### very common neurological diagnosis. I n men over the age 17



### of 50, it's the third most common neurological diagnosis. 18

19



### What that translates into is that, in this room, 20



### approximately half the men will experience prostatitis 21



### sometime during their lifetime, so it 's not an 22



### insignificant health

- related disease. The National 23



### Institutes of Health has re

- categorized prostatitis into 24



### four types; the bacterial

, acute and chronic

, and the 25



### nonbacterial chronic pelvic pain syndrome and an 26



### asystematic histologically evident inflammation. 27

28



### So there are different types of prostatitis that‟s mostly 29



### divided into the bacterial and non

- bacterial. When we 30



### use animal models such as the Lewis, Copenhagen and 31



### Wistar rats, they are animal models that develop a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### spontaneous non

- bacte rial prostatitis with advancing age. 1



### And so they'd been used as animal models for 2



### investigation of the disease with the premise that if you 3



### increase or exacerbate that incidence or severity, it can 4



### be a reflection of a particular treatment. 5

6



### I should poi nt out that you can also increase the 7



### incidence and severity of prostatitis by treating male 8



### rats with estradiol. And a number of studies that have 9



### used these models have also shown that the spontaneous 10



### non

- bacterial prostatitis observed in rats is very 11



### s imilar to the histological profile to that observed in 12



### humans . S o it, again, is a good model. 13

14



### Come back to estrogen, and estrogen

- inducted prostatitis 15



### is partly related to the inhibition of dopamine secretion 16



### at the hypothalamus and that can result in the production 17



### and secretion of prolactin that eventually is associated 18



### with inflammation in the prostate that‟s been reported in 19



### 1993 by Tandin Lucal's (phonetic) group in which they 20



### showed E2

- induced prostatitis was correlated with 21



### increase serum prolac tin, elevated pituitary weight and 22



### that the administration of bromocriptine

, which is a 23



### dopamine D2 agonist, was effective in suppressing the 24



### pituitary weight in hypoprolactinemia and it mitigated 25



### the prostate inflammation. 26

27



### So the studies that we've be en asked to review have 28



### implicated that exposure to atrazine during the late 29



### gestation period, that‟s days 15 to 19 in the rat, just 30



### prior to birth, or the early postnatal period

, just after 31



### birth

, days 1 through 4

, in male rats can lead to 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### inflammation of the prostate. And in these studies they 1



### looked at ventral and lateral regions at later stages of 2



### post pube r tal growth. It was considered that the 3



### inflammation was a result of elevated prolactin levels 4



### and these elevated levels were through to play a 5



### sign ificant role. 6

7



### The underlying mechanisms for that cause of prostatitis 8



### are not yet defined

, but may be related to hormonal 9



### changes during what we call critical periods of 10



### development that may have subsequent adverse affect 11



### during agent. I t's also impor tant to note that all these 12



### studies have used short

- term exposure with a range of 13



### doses and different rodent species. 14

15



### So our response then with regard to these studies and the 16



### human relevance are the following : W e believe it's 17



### unlikely that exposure in these animal model systems 18



### follow the same pattern of exposure that humans are 19



### exposed to in terms of atrazine and degradates which are 20



### more likely to occur over a lifetime and at much lower 21



### levels than those used in the animal studies . T his 22



### refers to the comments that Dr. O'Byrne made earlier on 23



### about the relevance of the 100 milligrams per kilogram 24



### dose to actual human exposure levels. 25

26



### In vitro and in vivo studies which have looked at 27



### cellular and molecular expression changes in response to 28



### human exp osure levels should therefore be conducted

. I'm 29



### going to refer to this diagram here. The prostate of the 30



### rodent consists of distinct lobes, which is not the case 31



### in the adult human gland. But the prostate of the rodent 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### has been the animal of choice for reproductive biology 1



### for many, many years
, the mouse and the rat. O ne of the 2



### values of this model is that we can examine the effects 3



### of treatments, such as endocrine disruptors and observe 4



### the region or regions which have a specific sensitivity 5



### to the com pound under investigation. 6

7



### So based upon such studies, it became clear that the 8



### region of the rodent prostate exhibiting the most 9



### sensitive response to the effects of estrogen and 10



### endocrine disruptors, for example, was the d orsal lateral 11



### lobe. W hat I show here on the left

- hand side is a 12



### schematic diagram of a rodent prostate showing the early 13



### developmental stages . On the left
, it is showing the 14



### individual budding outgrowth and in the middle is a 15



### reconstruction of a late gestation day of birth 16



### approxim ately rodent prostate where all the regions of 17



### the prostate have been color

- coded. 18

19



### So you can see green, yellow and bluish grey indicating 20



### respectively the d orsal lobe, the lateral lobe and the 21



### ventral lobe of the rodent prostate. T hese are the lobes 22



### that we typically see described in these studies. 23

24



### On the right

- hand side is a 13

- week human fetal prostate 25



### showing

-- and we have shown and others have shown

-- 26



### that the green area and the yellow area are homologous to 27



### the d orsal lateral lobe in the ro dent model. And this 28



### region in the human is the one which is important 29



### because, if you notice, in the human, the human does not 30



### have the equivalent ventral lobe, and I want to make that 31



### point very significantly. The human prostate in that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### region has part icularly stromal component. So it's 1



### important for us to understand these homologies and their 2



### relationship to any studies that are done in the animal 3



### model. I'll come back to that. 4

5



### While this wasn't the primary objective of this atrazine 6



### study in the issue paper, there is some evidence that the 7



### atrazine effects may be mediated through alterations of 8



### steroid agenesis, including estrogens. I t's important to 9



### emphasis that the d orsal lateral prostate, which I said 10



### is homologous to the equivalent peripher al zone in the 11



### human, which is the zone which develops a preponderance 12



### for cancer, is an important correlation. 13

14



### Most of the studies that we reviewed have actually looked 15



### at prostatitis in the lateral lobe, that‟s the yellow 16



### region up there . The d orsal lobe
, or combined 17



### d orsal / lateral lobe have typically not been examined. O f 18



### interest in an earlier study was, as I said, that this 19



### region, the d orsal / lateral region is actually homologous 20



### to what we call the peripheral zone in the human prostate 21



### where can cer develops. 22

23



### An endpoint in the atrazine rodent studies is the use of 24



### tissue weights to determine growth and/or adverse 25



### effects. In a recent national toxicology program 26



### scientific review of an endocrine disruptor, a specific 27



### concern was raised regard ing the reliability and 28



### usefulness of this parameter as a measurement of 29



### physiological effects. As stated in that report, and I 30



### quote
, "Perhaps the most important confounding factor in 31



### all of the prostate studies is that prostatic wet weight 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### is an extreme ly poor measure of prostatic growth

, which 1



### substantially diminishes the strength of data advanced 2



### both for and against an effect of whatever substance on 3



### prostatic growth. 4

5



### So in the light of that statement, you'll notice that 6



### many of these studies repo rt on ventral prostate weight 7



### and, as I pointed out, ventral prostate really doesn't 8



### have relevance to the human, and that prostatic wet 9



### weight is a poor measure of growth parameter. 10

11



### So in the light of this, the inflammatory response should 12



### be characte rized in this model

, we feel
, using 13



### co ntemporary approaches such as BrdU

- labeling, 14



### immuncytochemistry to determine proliferation rates as a 15



### consequence of treatment, and more importantly, 16



### characterization and histological quantification of the 17



### hyperplastic or inflammatory response. 18

19



### Furthermore, there are very significant modern 20



### contemporary approaches such as tissue microarray 21



### analysis that can be performed using laser

- capture micro

22



### dissection, and these might better define the cellular 23



### mechanisms respo nsible for the region

- specific 24



### inflammatory responses. 25

26



### Based on several animal models, these inflammatory 27



### mediator induction responses would likely occur prior to 28



### and at much lower doses than histologically

- evidenced 29



### cellular inflammation. What that m eans is that, when you 30



### see the inflammation, what precedes that initiation might 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### have much more consequence in terms of an effective 1



### mechanism of the action of atrazine. 2

3



### Cytokines induction, for example, can induce a number of 4



### effects in the tissue

, mi cro environment

, which can 5



### result in hyperplasia, dysmaplasia and dysplasia. I n 6



### addition, cytokines are known to induce development al 7



### growth regulators, including IGF, TGF and FGF, which are 8



### very important growth regulators during development and 9



### growth o f the gland. 10

11



### We feel that levels of these factors should be evaluated 12



### as part of this process of understanding the mechanisms 13



### behind the initiation of prostatitis. And finally, 14



### inflammation is associated not only with that, but also 15



### with DNA damage an d loss of imprinting of certain genes 16



### and that should also be evaluated. 17

18



### One interesting aspect of the gland in the rodent

, and 19



### also in the human

, not discussed in any of the relevant 20



### publications is the fact that the prostate, and 21



### especially the later al lobe of the prostate in the rodent 22



### model, has very high levels of endogenous zinc. For 23



### example, tissue zinc levels are reported to be actually 24



### lower in prostate pathology

, benign prostatic hyperplasia 25



### and cancer. W hile we don‟t know and fully understa nd the 26



### mechanisms and the reasons for the high levels of zinc, 27



### we know it's important in fertility. It might be 28



### relevant to an understanding of why inflammation 29



### specifically develops in that region. 30

31

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### So a question might be, are the d orsal lateral le vels of 2



### zinc reduced in earlier prostate development by atrazine 3



### exposure and does this play a later role in the 4



### development of prostatitis? And we feel that the 5



### relevance of this to the incidence may be important with 6



### regard to mediators of inflammation. Zinc concentrations 7



### and their correlations with inflammatory mediator 8



### expression and cellular inflammation should be evaluated. 9

10



### To date, there's been no causal link between atrazine 11



### exposure and prostate cancer from the studies that we've 12



### heard about . However, several important questions remain 13



### unanswered and unresolved from the present literature, 14



### such as the effects of repeated life

- long exposure to low 15



### doses on both prostate cancer incidence in grade and any 16



### effects on progression to advance disea se. The causes of 17



### prostate cancer are unclear but several studies have 18



### indicated that chronic prostatic inflammation may proceed 19



### benign prostatic hyperplasia and/or cancer in humans 20



### depending, again, on the region and the zone. I n fact, 21



### inflammation is t he most tightly correlated histological 22



### anomaly to prostate cancer development. 23

24



### If the link between prostatic inflammation and atrazine 25



### exposure is confirmed, this ascends to added importance 26



### and i mplo r e s us to consider the related consequences. An 27



### ad ditional component of these studies is that treatment 28



### of Wistar dams with daily doses of atrazine on postnatal 29



### days one to four resulted in suppression of what's called 30



### the suckling induced prolactin release in offspring. 31

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### T aking the same animals and looking at them at 120 days 2



### of age, the male offspring showed increased incidence and 3



### severity of prostate inflammation in the ventral and 4



### lateral lobes. There was significant increase in ventral 5



### prostate tissue weight at the low does 6.25 mgs per 6



### kilogra m , but that was calculated as non

- significant when 7



### body weight was taken into consideration. No other 8



### weight changes were observed. 9

10



### The lateral lobes were examined using mylar peroxida se 11



### assay for looking at inflammation responses and also 12



### histology. The type of inflammation was characterized as 13



### a focal neutrophill infiltrate, and in the lumen of the 14



### glands and focal mononuclear cells in the stroma. Though 15



### in these studies, the reaction was described as a chronic 16



### inflammatory response , the authors di d not make a 17



### comparison of the inflammation with a classification of 18



### human prostatitis types that have been described by NIH. 19

20



### A major point in considering the relevance in this type 21



### of study to the human health hazard is with regard to the 22



### modus operan d i for the exposure. So in the rat model, 23



### offspring suckled from atrazine

- treated dams, so we have 24



### breastfeed pups and at PND, postnatal day 120, the 25



### lateral prostate, the right lobe

, was taken for 26



### histological examination; the left lobe was taken for 27



### myl ar peroxidase

. 28

29



### What I find interesting is that a recent report from the 30



### CDC indicates that only three out of four mothers 31



### initiate a breastfeeding regimen, and by three to six 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### months, this rate is not maintained. So the study that 1



### was reported by Stok er et al. in 1999 suggests that early 2



### lactational exposure to prolactin is important for the 3



### normal development of the tuberoinfundibular neurons. 4



### However, according to the CDC data, approximately 25 5



### percent of US babies are not exposed to breast milk 6



### pro lactin . This may pose the question as to whether 7



### these individuals are at the same risk for later 8



### development of prostatistic if they're not exposed to the 9



### mother's breast milk prolactin. 10

11



### And a question again from us is do we know or do we have 12



### an estim ate for the measured levels of atrazine and its 13



### metabolites in human breast milk. 14

15



### One other consideration is that, if you belong to the 16



### baby

- boomer generation, you‟re the ones that are going to 17



### be the most likely to be affected and subsequent 18



### generatio ns by any health hazards from atrazine exposure, 19



### given that the chemical has only been in use since the 20



### 1950s. 21

22



### Let me summarize our responses. We believe there are 23



### several unresolved questions which limit the conclusions 24



### that can be drawn regarding th e human relevance of 25



### atrazine's affect on the prostate. The results in rodent 26



### models are of limited applicability due to 27



### inconsistencies in atrazine exposure levels and 28



### methodology. 29

30



### Secondly, the inflammation atrazine causes in rodents has 31



### not been su fficiently characterized regarding molecular 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### and cellular events that may indicate critical changes to 1



### the tissue microenvironment leaving open the possibility 2



### that lower doses of atrazine could produce subtle but 3



### very biologically significant events. 4

5



### The cellular signing mechanisms involved have not been 6



### elucidated and molecular events such as DNA damage and 7



### imprinting changes may be possible at low levels, and 8



### this has been shown in other studies of low level 9



### exposure to environmental endocrine disrup tors. Such 10



### changes may accumulate during the aging process of men. 11

12



### And finally, it is unclear what effects atrazine may have 13



### on the truly relevant measures of prostate cancer 14



### effects, including grade, progression and aggressiveness. 15



### We believe further research is needed to confirm or 16



### refute a possible role for atrazine in human prostate 17



### disease. 18

19



### DR. DANIEL SCHLENK : Thank you, Dr. Timms. Dr. Jerde? 20

21



### DR. TRAVIS JERDE : Thank you. I agree with the sentiments 22



### that Dr. Timms has just presented . I wou ld like to 23



### reiterate that the data so far in both the 24



### epidemiological association of prostate cancer to 25



### atrazine exposure, as well as the animal studies, do 26



### remain inconclusive with regard to any role hat atrazine 27



### may play in disease. 28

29



### A little bit abou t prostate cancer; to my view, prostate 30



### cancer is not a disease. It's probably five or six or 31



### ten different diseases. And when you look at 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### epidemiological evidence of a disease that‟s going to 1



### affect half the population, a one or two percent change 2



### in in cidence that may or may not occur is really not 3



### going to show up. But if there is an increase in the 4



### clinically significant

, highly aggressive forms that some 5



### men get

-- and those would be the very small percentage 6



### of the men that have the disease that wi ll actually end 7



### up dying from this disease

-- that would be a more 8



### applicable measure. 9

10



### So when Dr. Timms talks in his report here about the more 11



### relevant measures, what we could be looking at are those 12



### cancers that are a Gleason 4 plus 3 or higher , t ho se 13



### cancers that occur earlier in men , t hose cancers that are 14



### faster or achieve in androgen

- independent state . Okay, 15



### those are the prostate cancers that kill people. 16

17



### S o that‟s something that I hope that the data can be 18



### extracted from in what's been pub lished so far. And I 19



### agree with the dosing regimens

, repeated dosing 20



### throughout one's life

, because that is what one sees with 21



### prostate cancer , i t's a disease of aging. 22

23



### Now if it is true that this compound could cause 24



### prostatic inflammation, particula rly as a life

- long 25



### exposure, the results of this on human health actually 26



### could be quite profound. As Dr. Timms pointed out, 27



### inflammation is the most associated histological feature 28



### associated with prostate cancer. And we have another 29



### very common disease in the prostate, the second most 30



### common neurological condition diagnosed, and that‟s 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### called benign prostatic hyperplasia or LUTS, lower 1



### urinary tract symptoms in men. 2

3



### I chaired a session as the SBUR this spring on new 4



### advances in BPH research and

, amo ng other things, one of 5



### the themes that came out of this meeting was that 6



### inflammation is the most tightly correlated histological 7



### feature to symptoms of BPH, moreso than is prostate size, 8



### in fact. And so, one thing we haven't addressed so far 9



### is the pres ence of BPH LUTS symptoms in exposed 10



### individuals. 11

12



### We have no idea what causes prost atic inflammation in 13



### humans. It is not likely to be bacterial infection. 14



### Those prostates have been cultured. We've looked for 16S 15



### ribosomal RNA; inconclusive results in those studies. 16



### And so this gives rise to all sorts of different 17



### hypotheses. And there are hormonal changes , the presence 18



### of the metabolic syndrome, type 2 diabetes seems to be 19



### correlated a little bit, lifestyle, diet, an d 20



### environmental exposures are o ne of those things, 21



### including some of the endocrine disruptors that Dr. Timms 22



### is well

- known for investigating. 23

24



### But I'll just leave you with a little bit of epidemiology 25



### that I think is quite striking and is why we care about 26



### these issues in our field. In the United States, 50 27



### percent of men will get prostate cancer. That‟s well 28



### established. In Asia it's less than 10 percent. In 29



### China it's about one and a half percent. If you look at 30



### full

- blooded Chinese

- Americans who have lived in the 31



### United States for greater than two generations, their 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### lifetime incidence is 40 percent, suggesting that a 1



### lifestyle change of whatever is a very important 2



### progression of this disease . T hat is also associated 3



### with an increase in the clinically significant deadly 4



### forms of prostate cancer. So these are the reasons why 5



### we care about this and why

-- there's a lot of 6



### recommendations for you guys to go back to your lab and 7



### say, now do these studies. But over the course of the 8



### next few years, these things continue to

-- it's like a 9



### continually evaluation process, but those are some of the 10



### important questions that need to be addressed from our 11



### end as prostate biologists. 12

13



### DR. DANIEL SCHLENK : Okay. Any other comments from panel 14



### members? Okay. Let me go back to EPA. Do yo u guys have 15



### what you need for that particular question? 16

17



### DR. ELIZABETH MENDEZ : Yes. We have a lot to think about, but 18



### we wanted to also circle back, if we may, to a question 19



### that we have as we were sitting here during break 20



### thinking about what we've hear d this afternoon. 21

22



### One of the things that, if you remember when I first 23



### started my first presentation yesterday, the 24



### introduction, and I was going through the adverse outcome 25



### pathway . T here was a bifurcation in the road of when do 26



### we see something that is just a mere perturbation, that 27



### it's not going to lead us to a biological adverse effect, 28



### and when do we trip or go over that line where 29



### perturbation does become clinically significant. 30

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### T he BND that we're working on right now that was brought 2



### to th e table, it's based on a one standard deviation. 3



### It's not a BNDL10. It's not a BNDL15. When we do the 4



### BND at one standard deviation, we're talking about a 33 5



### percent decrease in LH surge or attenuation of LH surge. 6



### And I guess, what I would like to get a little bit of 7



### clarity is, during the September meeting, we heard some 8



### comments about 80 percent being necessary for the ovarian 9



### cyclosity disruption, but there was also some comments 10



### about, well there might be something else happening at 11



### lower levels of LH attenuation and you may just not have 12



### the data and we can‟t negate that. 13

14



### I would like to get a little bit of feedback from the 15



### panel in terms of do I hear that you‟re a little bit 16



### closer to giving us a range at least between 33 or 80, 17



### somewhere in th ere, that you feel is where we trip that 18



### censor that we go from a mere perturbation to something 19



### that leads to an adverse effect, given that we have at 20



### about 12 and a half megs or 25 megs, we start seeing 21



### things in terms of apical endpoints. So I guess th at‟s 22



### sort of a question that I would like to get a little bit 23



### of clarity on. 24

25



### DR. DANIEL SCHLENK : This would probably be a follow

- up to 26



### question five, right? Yes. 27

28



### DR. ELIZABETH MENDEZ : Correct. 29

30



### DR. KATHERINE ROBY : I'll try to get the discussion start ed. 31



### I think, from last September to now, we have no greater 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### insight in the significance of depression of the LH surge 1



### to subsequent outcomes downstream. I think, still, 80 2



### plus percent needs to be reduced before you see a shift 3



### in ovulation, for example. 4

5



### I think what was mentioned last September is what is an 6



### unknown is if there were a 30 or 50 or 60 percent 7



### decrease over time, it's completely unknown

-- I know of 8



### no literature that has addressed what might be the 9



### overall effect in your lifetime ferti lity. So I think we 10



### still don‟t have a great idea of where you go from a 11



### biological modifier that you‟re measuring LH and a 12



### concrete downstream negative effect or negative outcome 13



### in regard to fertility in the female. I'm not sure if 14



### that was very clear. 15

16



### DR. DANIEL SCHLENK : Any other comments from the panel? Yes, 17



### Dr. McManaman? 18

19



### DR. JAMES MCMANAMAN : Yes. I think that you‟re asking for a 20



### tertiary affect when we don‟t even know what the primary 21



### affect is. And so I guess I would echo the sentiments 22



### tha t have been express by Dr. Horseman and others that we 23



### really begin to look at what's going on at the level of 24



### the hypothalamus because that‟s the most likely affect, 25



### because you‟re affecting not only LH but you‟re affecting 26



### prolactin. And unless somebody can explain to me how LH 27



### is causing a decrease in prolactin then I think that it 28



### looks like, I'd say, probably a global affect or a 29



### potentially global affect on the hypothalamus and not 30



### specifically on an LH affect. 31

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### DR. DANIEL SCHLENK : Yes, Dr. Mendez? 2

3



### DR. ELIZABETH MENDEZ : Just a little bit of a follow

- up then 4



### just for my own personal understanding. The way that 5



### we've been thinking about the LH surge is sort of a node 6



### from whereas some other effects may make happen that LH 7



### diminished decrease. So I understand the 80 percent for 8



### ovarian cyclicity disruption but I'd like to hear a 9



### little bit more discussion about other endpoints like the 10



### puberty onset or something along those lines as well. 11

12



### DR. DANIEL SCHLENK : Dr. Horseman? 13

14



### DR. NELSON HORSEMAN : This gets to the point that we were 15



### discussing earlier. And I think the problem and the 16



### reason Dr. McManaman is suggesting other hypothalamic 17



### effects is there is no coherent way that any of us, I 18



### thin , can figure out that this suppression of the LH 19



### surg e and these other reproductive physiological affects 20



### ranging from delayed vaginal opening to estrous cyclicity 21



### to prostatitis in the male to whatever, and then add on 22



### top of that affects on appetite that are presumably 23



### hypothalamic. 24

25



### As far as we can te ll, or at least me, there is no way to 26



### consolidate those under one umbrella at this point. That 27



### doesn't mean that there isn't a final common pathway that 28



### explains all these things, but it's just that I don‟t 29



### hear any of us saying, "Oh, yeah, we can consol idate 30



### those things under one mode of action." Thank you. 31

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### DR. DANIEL SCHLENK : Yes, Dr. Mendez? 2

3



### DR. ELIZABETH MENDEZ : One last follow

- up. I just want to 4



### make sure that I'm hearing the panel correctly. So as 5



### I'm sitting here, am I hearing you say that you‟re not 6



### entirely certain that this is a node from whence 7



### everything else comes down? Is that what I'm hearing 8



### panel say? 9

10



### DR. DANIEL SCHLENK : A nybody want to respond to that? 11

12



### DR. KATHERINE ROBY : I will. 13

14



### DR. DANIEL SCHLENK : Dr. Roby? 15

16



### DR. KATHER INE ROBY : It might be a node, but I'm not a 100 17



### percent convinced it's only the surge that is a node. 18



### And you asked a question about other downstream effects. 19



### W e measure vaginal opening as an indication of onset of 20



### puberty in a rodent. And that occurs because of changes 21



### in LH, IA, GnRH, pulse secretion around the time of 22



### puberty stimulating the ovary, increasing estradiol 23



### production, which ultimately affects the vaginal tissues 24



### and allows for vaginal opening through some mechanisms 25



### that are well

- known n ow. 26

27



### So that ties back to LH. It doesn't tie back to a change 28



### in what we call the LH surge, the ovulatory surge, but 29



### probably a change in the pulse or the increase in pulse 30



### and amplitude that occurs around the onset of puberty. 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So in the sense, that L H is still that node, but again, 1



### the mechanisms are not explored. 2

3



### DR. DANIEL SCHLENK : Yes, Dr. McManaman? 4

5



### DR. JAMES MCMANAMAN : Yes. So to follow

- up on what Dr. Roby 6



### said, it potentially could be a node, but if it is, it's 7



### not the only node . B ecause t he atrazine causes a 8



### decrease in LH, that was suggest a decrease in GnRH. 9



### Atrazine also causes a decrease in prolactin, so 10



### prolactin is regulated in a different way , s o if it was 11



### affecting the hypothalamus to affect dopamine release, 12



### decreased dopamine re lease w ould actually increase 13



### prolactin and not decrease prolactin. 14

15



### So I suggest that there's something more complicated 16



### going on at the level of the hypothalamus and not at the 17



### level of

-- I mean, LH is the secondary effect to the 18



### GnRH

-- it's just ha rd to measure GnRH, that‟s why 19



### everybody measures LH

-- but it suggests that it's at the 20



### level of the hypothalamus and not at the level of the LH, 21



### per se. 22

23



### DR. DANIEL SCHLENK : Yes, Dr. Akana? 24

25



### DR. SUSAN AKANA : Yes. I think LH is a node in the net, so 26



### it 's just one of many, and it's the one that‟s probably 27



### most manipulable and measurable for you. But on a 28



### different tact, when I study male stressed rats, the 29



### first general rule of thumb we look for an unhappy rat is 30



### a drop in body weight. Like, a 10 perce nt drop in body 31



### weight is an automatic flag, regardless of whatever the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### provocation is. Now you‟re working with a lot of female 1



### rats, which have a much slower growth rat. So I think it 2



### would be even tighter, maybe a five percent drop in body 3



### weight. 4

5



### D R. DANIEL SCHLENK : Okay. Does that clarify your question 6



### there, Dr. Mendez? 7

8



### DR. ELIZABETH MENDEZ : I think I'm starting to get an idea 9



### that we're talking about, as Dr. Akana said, a net. We 10



### may have a part of the net. We don‟t have the whole net. 11



### And I guess, at this point in time, as Dr. Fowle 12



### mentioned earlier today, we have to, from a regulatory 13



### standpoint, go with what we have in front of us but 14



### remain vigilant to what may come further down the line. 15

16



### So I guess that‟s the reality of the situat ion were in 17



### the regulatory arena, but we'll certainly keep our eyes 18



### open. Thank you. 19

20



### DR. DANIEL SCHLENK : Okay. At this point, I believe

-- no? 21



### She answered it; okay. I guess we've got that one done; 22



### awesome. All right. Well there's no further comm ents on 23



### 5, 6, 7; let's go to question number 8 then. 24

25



### DR. ELIZABETH MENDEZ : Number 8 question, the genesis of that 26



### was we had some conflicting data about rat mammary gland 27



### development that was presented during the September SAP. 28



### And some other feedback t hat we got from the panel was, 29



### well, we have these two studies; one uses subjective 30



### measures for mammary gland development, the other one is 31



### using objective measures, namely morphometrics, but we've 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### never seen the two methodologies compared side

- by

- side. 1



### Based on the feedback that we heard during the September 2



### SAP, our colleagues in the O ffice of R esearch and 3



### D evelopment tried to address that question. 4

5



### T he question is , p lease comment on the agency's findings 6



### in addressing the issues raised by the SAP d uring the 7



### September 2010 meeting. Please comment on whether this 8



### study, along with the negative studies by CODAR adds to 9



### the weight of evidence that it is unlikely that atrazine 10



### impacts mammary gland development. 11

12



### DR. DANIEL SCHLENK : Thanks. Our lead di scussant on that is 13



### Dr. Horseman. 14

15



### DR. NELSON HORSEMAN : So a simplifying answer to this question 16



### would be a simple yes. But as you might expect from the 17



### panel, you‟re not allowed to give just that. Let me read 18



### from my answer that Dr. McManaman and I hav e discussed 19



### somewhat. 20

21



### The new data presented from Dr. Cooper's study address 22



### the concern that the studies from Fenton's group and 23



### those from Hovy, contracted with Syngenta, used quite 24



### different approaches for capturing mammary gland 25



### morphology. In the former, a ranking system was used; in 26



### the latter, a set of measured morphometric variables was 27



### applied. 28

29



### While the ranking system has been referred to a 30



### subjective and qualitative, it is in fact neither. The 31



### method, when done in a blinded fashion with trained 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### application and morphological criteria is clearly 1



### objective and no less so than a morphometric approach. 2



### It is also quantitative because the established 3



### morphological criteria converted to quantities, that is 4



### ranks that can then be compared with standard statistical 5



### methods. So it is

, in effect, objective and 6



### quantitative, ultimately. Morphometric measurements may 7



### be objective, but the only objective is if the measured 8



### variables are not chosen subjectively. So it's nothing 9



### magic about these two approaches, I think. And the fact 10



### that the data come out the same then isn't too 11



### surprising. 12

13



### There's a 2009 workshop that‟s been referenced in the 14



### white paper that did a good job of summarizing best 15



### practices for using morphological variables to 16



### char acterize rodent mammary glands. So based on using 17



### both approaches, the ranking approach and morphometry in 18



### a careful manner with Sprague

- Dawley rats

-- and again, 19



### rats trained is an issue that runs through a lot of these 20



### questions

-- t he Cooper study pres ented in the white 21



### paper demonstrates, number one, that both approaches 22



### produced similar conclusions, and number two, that any 23



### effects of prenatal atrazine exposure on mammary gland 24



### development early in life

-- and I think the measurements 25



### were done at day 45, which is just after puberty is 26



### finished

-- are very subtle and are not measurable by any 27



### of these techniques. 28

29



### So while Long Evans rats might be a different case

, good 30



### arguments have been made that the Sprague

- Dawley model is 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### appropriate and adequa te, and this study is definitive in 1



### that regard. 2

3



### So to the larger questions; first the use of "mammary 4



### gland development" as an index of adverse environmental 5



### chemical effects, has been advocated based on a number of 6



### features of mammary gland growth, m orphology, 7



### pharmacology and physiology . There are several papers 8



### from the number of groups advocating this as a model 9



### system. 10

11



### These features that are used in this advocacy include the 12



### exquisite hormone responsiveness of the mammary glands 13



### and a distin ct developmental sequence s of events, most of 14



### which occur after birth and are therefore accessible in 15



### ways that some other developmental events might not be. 16



### These are compelling notions, but I would say, thus far, 17



### implementing this practically has been d ifficult and not 18



### finally proven to be that helpful. 19

20



### Given the centrality of lactation, though, in the life 21



### history of mammals, continued concern about the affects 22



### of environmental chemicals on mammary gland biology is 23



### extremely important. Therefore, i nadequacies in the 24



### literature relating to atrazine effects on mammary gland 25



### development should not deter future studies. 26

27



### So the direct answer to the charge question is that the 28



### new evidence does not provide any support for an 29



### effective atrazine on mamm ary gland morphology. In the 30



### new studies, SD rats were treated in utero with a wide 31



### range of doses. Tissues were taken for analysis on 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### postnatal day 45. Mammary gland morphology was measured 1



### by both the arbitrary ranking system and by morphometric 2



### quant ification using image analysis. And because certain 3



### morphological characters occur in a predictable manner, 4



### measurement of this presented here are taken to signify 5



### development. It's always important to remember though 6



### that development refers to processes that underlie these 7



### morphological changes, not the morphology, per se. 8

9



### So while the charge question is focused on resolving 10



### differences of experimental design, data gathering 11



### interpretation between studies primarily from the Fenton 12



### lab and those from Cooper's lab and the Davis 2011 paper 13



### and the Hovy lab, also published this year, these 14



### ambiguous findings need to be considered in large 15



### context. So stepping back, earlier concerns about breast 16



### carcinogenesis are mammary gland cancer in atrazine

17



### treated rats were resolved satisfactorily by discovering 18



### that mammary tumors came about by a process of disorder 19



### postnatal development. 20

21



### It's driven by accelerated reproductive senescence and 22



### appropriate secretion of gonadotropin steroids and 23



### prolactin and that was reviewed by Cooper et al. most 24



### recently as 2007. 25

26



### So these well

- accepted conclusions lead to the simple 27



### deduction that atrazine does have effects on mammary 28



### gland development, even if those effects did not appear 29



### unambiguously in the results from t he earl y life studies 30



### from Fentons or the other labs cited here. 31

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### So the more relevant question seems to be whether 2



### development in the rodent mammary glands early in life 3



### provides any adequately robust model in which to observe 4



### subtle adverse effects of potential environmental 5



### toxicants such as atrazine. For a variety of reasons, it 6



### seems unlikely that mammary gland morphology, standing as 7



### a surrogate for underlying developmental processes, is 8



### adequately sensitive to fulfill this role. 9

10



### One limitat ion of rodent mammary gland morphology is it 11



### is subject to wide variations among rodent strains, 12



### depending on differences in hormone secretion patterns

, 13



### the presence of endogenous retrovirus, particularly, 14



### MMTV, and on their nutrition. In addition, there are 15



### internal differences between morphological 16



### characteristics of the glands within an individual and 17



### even within regions of a particular gland. So robustness 18



### is difficult to come by there. 19

20



### The second limitation is one's ability to define 21



### differences in morphology or development as being 22



### adverse. Given that the function of the glands is to 23



### produce adequate milk for the offspring, for any change 24



### in morphology to be defined as adverse it would need to 25



### be connected in some objective way to a deficiency i n 26



### milk supply. And given that the glands are controlled by 27



### a host of intrinsic and extrinsic homeostatic mechanisms 28



### that are focused on ultimately regulating milk 29



### production, it's not surprising that subtle effects of 30



### environmental chemicals on morphology may not, by 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### themselves, perturb function sufficiently to be 1



### definitely adverse. 2

3



### Concerns remain, however, as to whether an environmental 4



### toxicant such as atrazine which affects reproductive 5



### hormones or other mammary

- related physiological variables 6



### mig ht interact in important ways with other environmental 7



### factors that predispose individuals to poor mammary gland 8



### function and ultimately to inadequate lactation and poor 9



### breastfeeding outcomes. 10

11



### In particular, obesity is a known risk factor for poor 12



### mam mary gland function in humans as well as in rodent 13



### models, and is the number one contributor to failure of 14



### breastfeeding and failure of women to implement their 15



### breastfeeding goals. It's certainly conceivable, maybe 16



### likely, that subtle affects of an envir onmental chemical 17



### will have important consequences in overweight 18



### individuals. 19

20



### In conclusions , it is true that the current data "adds " 21



### to the weight of evidence that it's unlikely that 22



### atrazine impacts mammary gland development, which is the 23



### statement i n the question. However, the evidence off 24



### effects in some studies, combined with the known affects 25



### of atrazine on reproductive hormones provides an 26



### important basis for continued concern in efforts to 27



### design better studies that would determine whether thes e 28



### hormonal effects could contribute to poor lactation, a 29



### clearly adverse outcome, in susceptible individuals. 30

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### DR. DANIEL SCHLENK : Okay. Dr. McManaman, anything to add on 1



### that? 2

3



### DR. JAMES MCMANAMAN : As Dr. Horseman said, I concur. 4

5



### DR. DANIEL SCHLEN K : Great. Thanks for working together on 6



### that. Any other comments from the panel? Okay. I think 7



### that‟s pretty clear; yes? 8

9



### DR. ELIZABETH MENDEZ : Yes. Thank you. 10

11



### DR. DANIEL SCHLENK : Okay. All right. So we're moving right 12



### along. Let's go ahead and read in charge question 9 and 13



### hopefully call it a day after that, maybe. 14

15



### DR. ELIZABETH MENDEZ : All right. Charge question 9, it 16



### speaks to the sensitivity between the adults and infants 17



### and children in the analyses that has been conducted by 18



### the agen cy regarding the studies that we have in front of 19



### us and the evidence or lack thereof of an enhanced 20



### sensitivity of the young. 21

22



### So the question is please comment on the weight of 23



### evidence analyses conducted by the agency and the extent 24



### to which the unce rtainties related to the potential for 25



### differential sensitivity of the young are addressed with 26



### the additional data. Let me clarify that b y additional 27



### data, what we mean is, all of the life

- stage data that we 28



### have that is typically not available to us. 29

30



### DR. DANIEL SCHLENK : Okay. Our lead discussant is Dr. Fenner

31



### Crisp. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. PENELOPE FENNER

- CRISP : Okay. We've crafted three 2



### questions that I think re

- characterized your request for 3



### comment, and they are as follows. 4

5



### Does the existing body of data expl oring the potential 6



### for adverse consequences following exposure of either 7



### direct or indirect at relevant life stages, in fact, 8



### encompass all of the life

- stages of interest prenatal, 9



### perinatal, pre

- and peripubertal and adult. 10

11



### Secondly, do the study des ign employed in this existing 12



### body of data allow for an adequate assessment of the 13



### potential for differential sensitivities in light of the 14



### fact that these studies do not necessarily include 15



### measurement of the same endpoint or phenomenon that 16



### currently ser ves as the basis for the quantitative 17



### characterization of hazard, in other words, the 18



### suppression of the LH surge. 19

20



### In reading the issue paper, we've concluded that chapter 21



### 5 is supposed to serve as the weight of evidence and the 22



### uncertainty analysis. So the question becomes, does 23



### chapter 5 adequately present the weight of evidence and 24



### the uncertainty analyses on the question of potential 25



### age

- related differences in sensitivity ? Let's answer 26



### this question first. 27

28



### Chapter 5 is not a weight of evidence analysis of the 29



### datasets and it does not present the uncertainties of the 30



### database as it currently exists. The truly robust weight 31



### of evidence discussion would include a recapitulation of 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the previously submitted and reviewed studies

, along with 1



### the newe r ones , so that one can understand where and how 2



### each contribute to the determination of whether or not 3



### sufficient information exist to answer the question of 4



### whether or not we know enough about differential 5



### sensitivities. 6

7



### Secondly, there seems to be l ittle or no discussion of 8



### the extent to which the uncertainties related to the 9



### potential for differential sensitivity of the young are 10



### addressed. 11

12



### With regard to the first question, it would've been 13



### helpful or enlightening to have had available either a 14



### table or a figure which summarizes all of the relevant 15



### studies bearing on this issue. Dr. Mendez included 16



### several tables in her third presentation yesterday, which 17



### could've served as a starting point for a composite table 18



### of such studies. And we had, am ong the slides presented 19



### by Syngenta, a figure that could've been useful for 20



### assembling the dataset and had visual display of the 21



### available data to help answer the question. 22

23



### Nonetheless, the panel believes that there is sufficient 24



### information available to reach the conclusion that the 25



### issue of differential sensitivity has been adequately 26



### studied if one accepts the premise that the data on the 27



### LH surge is the appropriate one for making the 28



### comparisons. 29

30



### The panel continues to agree with the agency's c onclusion 31



### that exposure during the earlier life

- stages does not 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### lead to greater sensitivity, again, when comparing with 1



### that, the BMDL

- based dataset. 2

3



### Speaking to the second question, which was the issue of 4



### whether or not the parameters evaluated in the studies 5



### put forth to assess the potential for differential 6



### sensitivity are adequate or appropriate for that purpose. 7



### There are a wide variety of studies and a wife variety of 8



### endpoints that have been evaluated in these other 9



### studies, and I guess, in gene ral, we feel that they do 10



### provide a nice variety of things against which to 11



### compare. 12

13



### I'm going to follow with what I have characterized the 14



### subgroup as mission creek. In other words, we're going 15



### to answer a question that you haven't asked . T hat has t o 16



### do with the FQPA safety factor. Selection of it is a 17



### combination of what one does or doesn't know about the 18



### science and what one applies in terms of policies . So 19



### we're sticking the toe on the water on the hook of the 20



### science side. 21

22



### As summarize d in the agency's policy guidance entitled 23



### Determination of the Appropriate FQPA Safety Factors and 24



### Tolerance Assessment, Section 40 8 (b) (2) (c) that Liz 25



### mentioned yesterday instructs the agency in making its 26



### reasonable certainty of non

- harm finding that it apply an 27



### additional 10

- fold margin of safety. I won't read the 28



### rest of that. The section for the administrator may use 29



### a different margin of safety if she wishes. 30

31

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### It should be noted that the law does not impose any 2



### directional constraints on the choic e for a different 3



### margin of safety. The different margin of safety could 4



### be greater than 10x or less than 10x. While this 5



### flexibility exists in the law, there is little precedent 6



### explicitly or implicitly for application of an FQPA 7



### safety factor greater t han 10. I'm not going to tell you 8



### what the example is. There is substantial precedent for 9



### the reduction of the FQPA safety factor to either 3x or 10



### 1x, but there is no precedent for application of an FQPA 11



### safety factor less than 1. Should note, cases wher e the 12



### FQPA safety factor has been removed equates to a safety 13



### factor of 1x. 14

15



### As articulated in the 2003 IRED, EPA retained the FQPA 16



### safety factor of 10 for atrazine and its metabolites to 17



### protect the safety of infants and children in assessing 18



### risk from dietary, that is in food and drinking water 19



### exposure, and they offer the rationale as to why. I'm 20



### not going to repeat that here. And for residential 21



### exposures, they applied an FQPA safety factor of 3x, was 22



### reduced by roughly half. 23

24



### In summary, the 10 x factor was applied in the dietary 25



### risk assessment reflecting concerns both with regard to 26



### the neuroendocrine MoA and the uncertainties regarding 27



### exposures in drinking water. And the 3x factor for 28



### residential exposure reflects concerns only with regard 29



### t o the neuroendocrine MoA. 30

31

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### The July version of the issue paper

, we have available 2



### for this meeting

, summarizes the results of a series of 3



### studies, some predating and some postdating last 4



### September's SAP meeting and concludes, although 5



### additional expe rimental toxicology studies are still 6



### ongoing to better characterize the potential adverse 7



### health outcomes resulting from atrazine exposure, 8



### including the duration of exposure that may lead to an 9



### adverse health outcome, available data do not indicate 10



### that pre

- and/or postnatal exposure leads to increased 11



### sensitivity in the young relative to the attenuation of 12



### the LH surge and serves as a basis for the atrazine risk

13



### assessment. T he panel did agree with that last fall. 14

15



### If the panel continues to agree wit h the agency's 16



### conclusion with regard to the lack of early age

- related 17



### sensitivity to the neuroendocrine effects that are 18



### driving the hazard assessment, at least two options with 19



### regard to the appropriate magnitude of a revised FQPA 20



### safety factor could be considered. In the current issue 21



### paper, the agency proposes to replace the old NOAEL from 22



### the Morseth study with the new B MD L to .56 to serve as a 23



### point of departure. Going on to note three additional 24



### studies evaluating the effect of atrazine exposure ac ross 25



### life

- stages have become available within the last few 26



### months. 27

28



### These studies reinforce the conclusions reached during 29



### the September 2010 meetings since all of the affects 30



### observed in the young in these set of studies occurred at 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### doses roughly 25 ti mes higher than the dose EPA is 1



### proposing to use as the point of departure. 2

3



### So we see two options that one might elect to use for 4



### reevaluating the safety factor in the new upcoming risk

5



### assessment. The 10x safety factor currently applied in 6



### the dietar y risk

- assessment could be reduced to 3x. 7



### Removing the 3x or reducing to 1, that portion of the 8



### safety factor addressing concerns regarding the hazard 9



### potential. The other half, which is currently applied

, 10



### because of the exposure issues

, would be revisit ed when 11



### they are resolved. The 3x safety factor currently 12



### applied in the residential risk

- assessment also could be 13



### removed or reduced to one. That‟s the more conservative 14



### approach. 15

16



### The second option is, given that one could con clude
, from 17



### the agency 's statement above about the 25

- fold difference 18



### thing, is that not only is there no differential increase 19



### in sensitivity in the young as a consequence of pre

20



### and/or early

- postnatal exposure; there is, in fact, the 21



### decreased sensitivity when compared with the adult 22



### female. O n the basis of this finding, one might argue 23



### that the 3x FQPA safety factor currently applied to 24



### account for the uncertainties are concerned around the 25



### neuroendocrine effects c ould be reduced to less than one. 26

27



### For example, on page 2 9 of the issue paper, the agency 28



### states that all of the effects and sexual maturation a nd 29



### altered androgen status reported after about 30 days of 30



### exposure occur at dose levels 5 or more fold higher than 31



### those leading to the LH surge. F urther, they say the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### dose level eliciting the increase in the incident of 1



### prostatitis in the offspring is greater than 10

- fold 2



### higher than the dose leading to the LH surge attenuation 3



### used as the basis for the risk

- assessment. This argues 4



### then
, that the FQPA safety factor co mponent addressing 5



### the hazard potential could be reduced not just to 1x, but 6



### further by at least 5

- fold. 7

8



### DR. DANIEL SCHLENK : Okay. Thank you, Dr. Fenner

- Crisp. Dr. 9



### Akana? 10

11



### DR. SUSAN AKANA : I have nothing more to add. Thank you. 12

13



### DR. DANIEL SCHLENK : How about subtract? Dr. Chambers? 14

15



### DR. JANICE CHAMBERS : Penny is a hard act to follow. I don‟t 16



### have much to add either

. I do agree that there is 17



### nothing in the evidence you provided to us that indicates 18



### that the young are more sensitive. I also agre e with 19



### Penny that there wasn't a good compilation of the studies 20



### for us to try to sort that out very easily, but the issue 21



### paper does indicate that additional studies are ongoing, 22



### so I assume that when those data are derived, they'll be 23



### looked at. 24

25



### Some of the studies that you did quote in there did show 26



### functional endpoints, in terms of looking at vaginal 27



### opening and behavior and that sort of thing, and I tend 28



### to think that those sorts of functional endpoints are 29



### more important to look at than something that may not be 30



### a true adverse effect. 31

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### DR. DANIEL SCHLENK : Dr. Meek? 2

3



### DR. BETTE MEEK : Right. Well, I agree with most of what's 4



### been said and maybe all of it if I understood all of it, 5



### so just a couple of additional points. 6

7



### I really didn't see a w eight of evidence analysis, so 8



### that was really to under score the point. I think a 9



### weight of evidence analysis of being kind of a simulation 10



### of the data looking at the consistency, the dose response 11



### concordance, et cetera . S o I didn't really see that in 12



### t he issue paper. O f course, consideration of FQPA really 13



### should be based on transparent and systematic 14



### consideration of the most important qualitative and 15



### quantitative uncertainties associated with both exposure 16



### and the effect, and we've restricted this di scussion 17



### principally to hazard ; o ur relevant to susceptible life

18



### stages, and again, I really didn't see that discussion in 19



### the paper. 20

21



### A couple of points, though I probably stated them in a 22



### slightly different manner but underscore some of the 23



### previous p oints. I think that we need to take into 24



### account the interplay between uncertainty and safety 25



### factors, and the point of departure. And we need to 26



### recognize that the point of departure in this case is 27



### likely very protected, having been based on the lower 95 28



### percent confidence interval for the benchmark response 29



### for an early precursor event rather than an adverse 30



### effect. 31

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### So I agree that, based on the data that we have been 2



### presented, there appears to be no basis for application 3



### on the factor on the bas is of hazard. So in relation to 4



### exposure, I'm just going to leave one point with you, 5



### although we haven't discussed that at this point. I 6



### wondered if any thought had been given to estimating the 7



### internal dose metric for younger age groups of the human 8



### po pulations . H uman population for consideration of the 9



### context of FQPA recognizing that the chemical specific 10



### adjustment factor for interspecies or animal to kinetic 11



### differences are likely to be less than default. So that 12



### is just something to keep in mind for future. 13

14



### O ne other point, given the interplay between the point of 15



### departure and applied uncertainty or safety factor, I 16



### think that the question gives me

-- I'm taking license 17



### anyways to raise a recommendation that I made at the 18



### September SAP meetin g. In the interest of transparency, 19



### I think it would be helpful to consider an array of 20



### points of departure for various endpoints and their 21



### biological significance with a view to bounding 22



### potentially the degree of conservatism associated with 23



### the ultimate choice. 24

25



### This would include but not be limited to the benchmark 26



### dose for the impact on the LH surge, but including also 27



### those for more traditional endpoints generally considered 28



### to be adverse. This seems rather critical as a basis to 29



### interpret the der ived benchmark dose in the context no t 30



### only of its biology significance, but also its degree of 31



### conservatism in the risk

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### use traditionally to address more severe endpoints. So 1



### again, that really builds on some of the earlier 2



### conversations that we've heard today as well, and I think 3



### I'll leave it at that. 4

5



### DR. DANIEL SCHLENK : Thank you, Dr. Meeks. Any other input 6



### from the panel? Dr. Portier? 7

8



### DR. KENNETH PORTIER : I got a question of Dr. Meek. If I 9



### understood what you were saying, when we talk about the 10



### LH surge we're talking about something really, really, 11



### really early in a process to an adverse event. When you 12



### think of FQPA factors, there's like a 10

- fold multiplier 13



### from the normal population that‟s susceptible. 14

15



### Is th at something that‟s on the table when you‟re talking 16



### about now setting an endpoint that‟s very early in some 17



### kind of process? Is that one way of addressing that 18



### susceptible individual in the population or are you 19



### thinking about something else? It just ki nd of came up 20



### in my mind as you were saying this, and I was thinking, 21



### "Is that what she thinks?" 22

23



### DR. BETTE MEEK : To me, you can‟t separate the discussion of 24



### the point of departure, its degree of conservatism and 25



### how health protective it is from the discu ssion of the 26



### uncertainty factors. Ultimately, those uncertainty 27



### factors have to be informed by the degree of adversity of 28



### the critical endpoint, the extent to which you think 29



### sensitive populations are protected, the interspecies 30



### differences in kinetics an d dynamics. 31

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### So I find it difficult to discuss a single factor outside 2



### of all of those considerations for which there is 3



### interplay. I also am not particularly fond of collapsing 4



### an entire database to one point of departure, which is 5



### why I think it's important as well to consider several 6



### points of departure in terms of the increasing degree of 7



### adversity of the effects for which you‟re trying to 8



### protect and bound those points of departure with 9



### considerations related to their adversity. 10

11



### DR. DANIEL SCHLE NK : Okay. Any other panel input? Okay. 12



### Back to the agency. Are you content with that answer, I 13



### guess? 14

15



### DR. ELIZABETH MENDEZ : Well, I have to say an FQPA factor of 16



### less than one is

-- it's one of those wow moments, but I 17



### certainly recognize what I am hearing from the panel and 18



### we'll do a better job of compiling the data for the 19



### weight of evidence. We were trying in the interest 20



### because we had presented a lot of that data in September

, 21



### w e were trying not to repeat everything again, but it 22



### appears that it would've been helpful at this point in 23



### time to do so, so we'll certainly take that under 24



### consideration. 25

26



### Other than that, no; I think you've answer our question. 27



### I am going to, for question 10, pass it on to Dr. 28



### Christensen because I think I'm start ing to lose my voice 29



### a little bit here. 30

31



### DR. DANIEL SCHLENK : We're not going to go to question 10. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. ELIZABETH MENDEZ : You‟re not going to go on to

-- 2

3



### DR. DANIEL SCHLENK : No. 4

5



### DR. ELIZABETH MENDEZ : You‟re going to call it a day? 6

7



### DR. DANIEL SCHLENK : We're going to call it a day; yes. 8

9



### DR. ELIZABETH MENDEZ : All right. In that case, any other 10



### questions? 11

12



### DR. DANIEL SCHLENK : Yes. Dr. Fenner

- Crisp, you have one more 13



### comment? 14

15



### DR. PENELOPE FENNER

- CRISP : One of your last points, Liz, 16



### about a docum ent; I see the issue papers at any one time 17



### as a living document there, and how many of them

-- at 18



### least three that gets bigger and bigger and bigger. But 19



### this one should have built on the last one and should 20



### have acknowledged the work that was done in th e earlier 21



### ones, particularly on this point. 22

23



### So it should've been brought forward into that chapter, 24



### because ultimately you‟re going to have a last one and 25



### it's going to become the background document for the 26



### risk

- assessment and you‟re going to want to have all of 27



### that there. So grow it with time. 28

29



### DR. ELIZABETH MENDEZ : Yes. We'll certainly do that. 30

31



### DR. DANIEL SCHLENK : Okay. Have a question, Dr. Griffith? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL GRIFFITH : Listening to the responses to questions 2



### 5 through 9 and linking that ba ck to the water 3



### monitoring, my impression is, there is some need to also 4



### look for the repeatability, the cyclability that‟s in the 5



### water monitoring data from year

- to

- year. Most of what 6



### I've seen has been concentrated on what's going on in a 7



### given year. B ut if there is something such as atrazine 8



### damage accumulates through time, then it would be useful 9



### to see how those time series are replicating themselves 10



### from one summer to the next. And I didn't see any of 11



### that in the background material, but it seems t o me that 12



### that might be something that need to be inspected. 13

14



### DR. ELIZABETH MENDEZ : I don‟t know if our water

- monitoring 15



### colleagues are still in the room. 16

17



### DR. DANIEL SCHLENK : Yes. That may be something we'd want to 18



### do on the last question, I believe; yes. Okay? With 19



### that, I'll turn it over t Joe Bailey and he can close 20



### this out. 21

22



### JOSEPH BAILEY : Thanks to everyone. I don‟t have any closing 23



### comments except thanks for your input today. 24

25



## July 28, 2011

- 8:30 a.m. Day 3 26

27



### JOSEPH BAILEY : Let's get st arted here. My name is Joe 28



### Bailey, and I'm with the FIFRA Scientific Advisory Panel 29



### staff, serving as designated Federal Official. This 30



### FIFRA for Scientific Advisory Panel meeting, reevaluation 31



### of the human health effects of atrazine, review of non

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### cance r effects, drinking water and monitoring frequency, 1



### and cancer epidemiology. 2

3



### I don't have any announcements to make this morning with 4



### regard to the docket or anything. The EPA presentations 5



### are there, available, and the public comments are not 6



### there yet, but they will be, hopefully by the end of the 7



### week. And that's it. I'll turn it over now to Dr. 8



### Schlenk, our Chair. 9

10



### DR. DANIEL SCHLENK : Thanks, Joe. Good morning, everyone. I 11



### think we'll skip our normal round

- robin introductions 12



### this morning since I think everybody kind of knows 13



### everyone at this point. So we're going to begin with 14



### Question 10. And, Dr. Christensen, you're going to read 15



### that into the record? That would be great. 16

17



### DR. CAROL CHRISTENSEN : Thank you. Good morning; Carol 18



### Christensen with EPA. So we are moving into cancer 19



### epidemiology portion of the meeting. So Questions 10 and 20



### 11 relate to Chapter 3 and Appendix B of the draft Issue 21



### Paper from EPA. So at this time we're looking for 22



### feedback on our evaluation of the individual stud ies, our 23



### synthesis across the epidemiology database, as well as 24



### the integration with the experimental toxicology 25



### database. As was mentioned yesterday, we're sort of 26



### stopping short from making a request as to what the 27



### cancer classification should be, per s e, but more looking 28



### for feedback on the process at which we came to our 29



### preliminary conclusions and the extent to what the data 30



### support those conclusions at this time. 31

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### So having said that, Question 10, Part A reads: "Please 1



### comment on the sufficiency of t he Agency's cancer 2



### epidemiology reviews with respect to identifying the 3



### major strengths and limitations of each study in the 4



### overall synthesis of results by cancer type." 5

6



### DR. DANIEL SCHLENK : Thank. And our lead discussion on that 7



### is Dr. Bove. 8

9



### DR. FRANK BOVE : Good morning, everyone. Having sat on the 10



### 2000 and 2003 science advisory panel meetings for 11



### atrazine and registered my frustration in each of these 12



### meetings that the EPA had not done a systematic and 13



### comprehensive evaluation of all the cancer at t he work 14



### that had been done up to those times, I'm pleased that 15



### EPA has finally done so. And I think that they've done a 16



### pretty good job. Although we have some differences with 17



### EPA on some of the evaluations, for the most cancer sites 18



### we're in agreement w ith EPA's assessment. We think it‟s 19



### pretty comprehensive. 20

21



### Focusing first on the methodology of EPA's literature 22



### search, we find that the methods were sufficient, 23



### thorough and transparent. EPA's method of evaluating 24



### studies was, in general, sufficient and, as I said, 25



### comprehensive. Important aspects of the studies were 26



### considering, including accurately measuring the cancers 27



### and exposures, issues of bias, sample size and 28



### statistical power. 29

30



### Major strengths and weaknesses were identified, and in 31



### partic ular, whether exposures were assessed 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### quantitatively; the ranges of exposure, whether critical 1



### windows, time windows of exposure were evaluated. And 2



### they used the usual etiological criteria, such as 3



### temporality, magnitude of the measure of association, 4



### wh ich would be the relative risk or the odds ratio, for 5



### example, exposure

- response trends, consistency of 6



### findings across studies and biological plausibility. 7



### However, there are some issues with EPA's methods of 8



### assessment, at least I have. 9

10



### First, the f ocus of the assessment should be on the 11



### individual level studies. Ecological studies should be 12



### evaluated only if there are compelling reasons to do so. 13



### For example, if there is no other individual level 14



### studies to evaluate. 15

16



### Secondly, the focus should not be on whether a finding is 17



### statistically significant, especially given the low 18



### statistical power of most of these studies. Emphasizing 19



### statistical significance when power is low will likely 20



### result in Type II errors. I did notice a couple of times 21



### in the text the notion of borderline significance was 22



### mentioned. There really is no such thing; a finding is 23



### either statistically significant or it isn't. And there 24



### was also a statement in the text that the findings that 25



### are borderline are more likely to be chance findings and 26



### that's not accurate either. We can get into that if we 27



### want, but that's

-- 28

29



### A third issue is concerning biases. It's important to 30



### provide some evidence, not just charge that the bias 31



### might be there, but actually provide some evidence as to 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### why a particular bias is likely to be present in this 1



### study; the likely magnitude of the bias and the likely 2



### direction of the bias. In particular, the likely impacts 3



### of non

- differential exposure misclassification be taken 4



### seriously. That is, bias towards the null for 5



### dichotomous exposure variables and distortion of 6



### exposure

- response relationships, in particular, 7



### attenuation at the high end so that monotonic trends are 8



### not observed. 9

10



### This is also the case with the healthy worker survivor 11



### affect bi ases and since we're studying occupational 12



### cohorts most of the time here, that's also an issue. 13



### Again, these kinds of biases tend to distort exposure

14



### response relationship so they're not monotonic. 15

16



### Also, the issue of confounding: It‟s important to kee p 17



### in mind it's not just that a factor is correlated with, 18



### for example, pesticides correlated with another 19



### pesticide. There really needs to be a strong risk factor 20



### involved. An example, with asbestos and lung cancer and 21



### smoking as a possible confounder; e ven though the work 22



### forces that are studied have a high prevalence of 23



### smoking, the confounding effects of smoking in these 24



### studies are usually no more than 20 to 30 percent. And 25



### smoking is an extremely strong risk factor for lung 26



### cancer and is also very h ighly correlated with asbestos 27



### exposure and yet that's about as much as the confounding 28



### that exists. So when we're talking about confounding by 29



### other risk factors that are weak risk factors

-- even 30



### though they may be correlated with pesticide exposure

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### you do not see much confounding. I'll talk about that a 1



### little bit later and I'll give you an example. 2

3



### Fourth, it's problematic to make a general statement 4



### about all cancers. That's true whether you've studied 5



### all cancers combined, as sometimes the Agri culture Health 6



### Study does, or whether you make a blanket statement

-- as 7



### in page 71 of the text

-- that atrazine is not likely to 8



### be carcinogenic in humans. 9

10



### The evidence across cancer sites is considerably mixed, 11



### with some sites having evidence of no as sociation and 12



### other sites having at least suggestive evidence. So 13



### lumping, making these kind of blanket statements

-- and 14



### also lumping all cancers together to analyze them

-- is 15



### not very helpful. 16

17



### Fifth, the appendix: The text, actually, was very good 18



### in describing each cancer site and the evidence for that 19



### in the epi literature. The appendix, on the other hand, 20



### had studies of different sites all mixed in together. It 21



### would be helpful if the appendix was better organized, 22



### like the text was. And that al so includes the tables 23



### that are in the text. And actually, Dr. Gold has put 24



### together a table that we'll put in our report that is an 25



### example of what might be done. 26

27



### Okay. The EPA discussed the strengths and weaknesses of 28



### the Agricultural Health Study and we thought it was 29



### comprehensive. One strength that the Agricultural Health 30



### Study has is that it is a longitudinal follow

- up and 31



### exposures and risk factor are updated every five years. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Information is updated every five years; however, this 1



### information ha s not been used

-- at least analyzed yet

-- 2



### in these studies we evaluated. The information is still 3



### from Phase I. 4

5



### Another issue with the Agricultural Health Study cohort 6



### is that it is predominately white and may therefore not 7



### include more susceptible pop ulations; for example, 8



### prostate cancer if more prevalent among African

9



### Americans. And another limitation is there is a small 10



### number of female applicators making it difficult to study 11



### cancers in females occupationally exposed. 12

13



### One other point that EPA mak es in the text is they state 14



### that most of the agricultural health studies were 15



### hypothesis generating. And actually, all of them were 16



### hypothesis generating and that's true of most scientific 17



### research, but they were also all hypothesis

- testing 18



### studies. The y all had an interest in particular cancers 19



### as well as other cancers, but there were particular 20



### cancers of interest and hypotheses were tested. 21

22



### Okay. Now let‟s get to the particular cancer sites. EPA 23



### pointed out correctly that most of the studies focu sed on 24



### cancers of the lympohematopoetic system, the reproductive 25



### and the endocrine system, and that's what we‟ll be 26



### focusing on. First, prostate cancer ; i t was evaluated by 27



### the 2003 Science Advisory Panel. Back then, the Science 28



### Advisory Panel's position was that the database was 29



### insufficient to support a conclusion regarding the 30



### potential of atrazine to cause prostate cancer. 31

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### This conclusion remains valid today even though the 1



### agricultural health study cohort provides evidence 2



### against an association. And the reason it‟s still valid 3



### is that there are still lingering questions about the 4



### Saint Gabriel triazine manufacturing studies. These 5



### studies were initiated because of an excess of prostate 6



### cancer

-- five observed and two expected

-- that occurred 7



### pri or to the start of the prostate screening program at 8



### the plant. Now, the screening program can explain most 9



### of the excess cases at the plant and we said that back in 10



### 2003

-- but not the excess represented by these five 11



### cases. The exposure experience of t hese five cases has 12



### never been presented. The follow

- up case control study 13



### could've compared the exposure experience of these five 14



### cases with controls that were employed prior to the 15



### screening program, but that wasn't done. 16

17



### At the previous 2003 SAP panel , it was concluded that 18



### "Lack of association among farmers does not preclude the 19



### existence of a positive association with triazine 20



### manufacturing plant workers," and this is because the 21



### exposure experience is different. Farmers had more 22



### intermittent exposu res; workers would have more chronic 23



### exposures. 24

25



### Moving onto breast cancer, a study of the agricultural 26



### health cohort observed relative risk hovering around 1.0. 27



### So this is negative evidence. On the other hand, there 28



### is a drinking water study in Wiscon sin where the mean 29



### atrazine level in the high use area, high pesticide use 30



### area, was very low: less than .5 parts per billion. And 31



### only a handful of cases were exposed to well water with 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### equal to or greater than three parts per billion 1



### atrazine. But the odds ratios range from 1.2 to 1.4, 2



### again, based on small numbers of cases. 3

4



### The evidence for association is extremely weak in this 5



### study, it shouldn't be dismissed. EPA correctly 6



### identified the limitations in these studies, including 7



### the agricultural he alth survey and that was small 8



### numbers, low power exposure, misclassification, inability 9



### to evaluate critical time windows of exposure and 10



### inability to evaluate exposure

- response relationships; 11



### however, EPA states in the text that there is a lack of 12



### eviden ce, and that's not correct either. There is some 13



### evidence. It‟s very weak. So it may be better to 14



### characterize breast cancer as having inadequate 15



### information to assess whether atrazine can cause breast 16



### cancer. 17

18



### Ovarian cancer: EPA focused on four stu dies, three of 19



### which were individual level studies; a study in Italy, a 20



### study in Central Valley, California, and the Agricultural 21



### Health cohort studies. Both the Italian case control 22



### Study and the Agricultural Health study observed positive 23



### associations a nd the Italian study observed higher odds 24



### ratios with longer duration of exposure to triazines. It 25



### did not look at atrazines specifically. And when they 26



### more precisely defined the exposed group, they also found 27



### higher odds ratios. Although it didn‟t eva luate atrazine 28



### specifically, the Italian study reported that the sales 29



### of atrazine in the area where these pesticides were used, 30



### the sales of atrazine were 10 times higher than the sales 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### of other triazines. So it looks like atrazine was 1



### predominately used in that area. 2

3



### The Central Valley, California case control study used 4



### pesticide usage reporting data and questionnaire 5



### information to construct the job exposure matrix to 6



### assess occupational exposure to atrazine. They also 7



### evaluated residential proximity to areas where the 8



### pesticide was applied. Based on two exposed cases, the 9



### odds ratio forever occupationally exposed to atrazine was 10



### .76, and for residential proximity it was .88, based on 11



### eight exposed cases. However, the study excluded cases 12



### that died, they were too ill to participate, which EPA 13



### pointed out may have introduced a selection bias. Given 14



### the positive findings in two relatively well

- conducted 15



### studies, EPA should consider the evidence as suggestive 16



### for an association between atrazine and ova rian cancer. 17

18



### Moving on to lympohematopoetic cancers, the evidence is 19



### negative for leukemias, except for hairy cell leukemia

-- 20



### I'll talk about that in a second

-- and multiple myeloma. 21



### There are two studies, both of which are hospital

- based 22



### case control studies

-- I think both are French studies

- 23



### - that evaluate hairy cell leukemia. Both were positive 24



### for triazines. Atrazine wasn‟t looked at separately. 25



### Both of the Italian studies used similar methods for 26



### control selection. EPA had some problems with their 27



### control selection, but in reviewing these studies, I 28



### don‟t find any problem whatsoever. They also had similar 29



### exposure assessment methods. 30

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### In the earlier Italian study, an odds ratio of 2.4 was 1



### observed for definitely exposed to triazines, based on 20 2



### cases. The analysis was restricted to cases and controls 3



### unexposed to organophosphates, the odds ratios were 4



### reduced to between 1.5 and 2, depending on what variables 5



### were included in the models. No exposure

- response 6



### relationship was reported, but they did not present any 7



### data in this study. 8

9



### A more recent Italian study observed an odds ratio of 5.1 10



### for hairy cell leukemia, based on four triazine

- exposed 11



### cases. This study evaluated several exposure lag periods 12



### and didn‟t find any differences when they did that, but 13



### they did not report any of their exposure

- response 14



### analysis. However, given that there are two positive 15



### studies here, there is, I would think, suggestive 16



### evidence for an association between triazines and hairy 17



### cell leukemia that should be followed up. 18

19



### As for non

- Hodgkin's lymphoma

-- and this was discussed 20



### briefly in the 2000 Science Advisory Panel, but again, 21



### not in a comprehensive fashion

-- there were several 22



### positive individual level studies of atrazine and non

23



### Hodgkin's lymphoma, including a pooled analysis of 24



### Midwestern studies that used hierarchical methods to take 25



### into account a large number of pesticides simultaneously. 26



### I think it was greater than 40 pesticides. 27

28



### Interestingly, the study concluded: "Adjustment for 29



### multiple pesticides suggested that there were few 30



### instances of substantial confounding of pesticide effects 31



### by other pesticides. Again, confounding, it's very 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### important to remember, it has to be strong risk factor as 1



### well as being associated with the other exposur e of 2



### interest. This study of hierarchical pooled analysis 3



### observed an odds ratio of 1.5 for atrazine and non

4



### Hodgkin's lymphoma. 5

6



### Another study found an association between atrazine and a 7



### specific sub

- type of non

- Hodgkin's lymphoma, the 8



### chromosomal tran slocation T

- 1418, and the odds ratio was 9



### 1.7, based on 15 exposed cases. On the other hand, for 10



### the negative T

- 1418, the odds ratio was 1. There were 11



### some issues here; they could not get tissue samples for 12



### most of the cases. They had to do a missing val ue 13



### algorithm to impute values. So there are some issues 14



### there. But in any case, they did see a positive 15



### association for that specific sub

- type. 16

17



### A French study that examined hairy cell leukemia also 18



### observed associations between triazine and the non

19



### Ho dgkin's lymphoma subgroups diffuse large cell, odds 20



### ratio 2.1 based on eight cases and follicular lymphoma 21



### odds ratio 2.3, based on four cases. On the other hand, 22



### the Agricultural Health Study recent update was negative 23



### for atrazine and non

- Hodgkin's lymp homa, including the 24



### subgroups. But given the positive studies, there is 25



### suggestive evidence of an association between atrazine 26



### and non

- Hodgkin's lymphoma and I think that should 27



### continue to be evaluated. 28

29



### Thyroid cancer: Here we have just the recent up date of 30



### the Agricultural Health Study which observed elevated 31



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### lifetime days. But the trend was not monotonic, again, 1



### probably due to exposure misclassification bias. The 2



### categorization was, as I think it was pointed out a day 3



### or two ago, was kind of funny. The categorization used 4



### in the analysis was based on all cancer cases and was not 5



### really appropriate for this cancer. Unfortunately, 6



### researchers could've used some smoothing methods to 7



### evaluate how the curve looked and maybe done the 8



### categorization based on that but they did not. In any 9



### case, this study provides suggestive evidence and should 10



### be followed up. 11

12



### A number of other cancers that have been studies, usually 13



### there's only one study for them , except for gliomas, and 14



### they've been negative. And those include lung, pancreas, 15



### melanoma, colorectal, and as I said, gliomas. In the 16



### recent Agricultural Health Study update, non

- monotonic 17



### exposure

- response trends were found for liver and 18



### esophageal ca ncers. So you may want to say the evidence 19



### is inadequate and requires follow

- up for those two. 20

21



### Finally, two studies evaluate childhood cancers. The 22



### Agricultural Health Study evaluated paternal use of 23



### atrazine in all childhood cancers combined and obse rved 24



### 1.27. They only had small numbers of particular cancers, 25



### so they had to lump them all together. I think that is 26



### problematic. The second study in California evaluated 27



### residential proximity to areas where triazines were 28



### applied and acute lymphocytic leukemia and observed a 29



### non

- monotonic exposure

- response trend. When lifetime 30



### exposure

-- lifetime of a child

-- was evaluated, but 31



### didn‟t observe any elevations whatsoever. They just 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### looked at the first year of life proximity. They 1



### reported limitations in both, which EPA pointed out in 2



### its evaluation. So this again, inadequate evidence of an 3



### association here as well and requires follow

- up. 4

5



### So in summary, the cancers for which one can consider the 6



### suggestive evidence of carcinogenic potential

-- I'm 7



### usi ng these categories that EPA uses

-- would include 8



### ovarian cancer, non

- Hodgkin's lymphoma, hairy cell 9



### leukemia and thyroid cancer. Cancers for which there is 10



### inadequate evidence would include prostate, breast, 11



### childhood cancers, liver cancer and esophagea l cancer. 12



### Both categories I would say the cancer sites require 13



### follow

- up studies. And then cancers not likely to be 14



### caused by atrazine include oral, lung, colorectal, 15



### pancreas, bladder; leukemia, except for hairy cell, 16



### multiple myeloma, melanoma, kidney, larynx, brain, 17



### gliomas. That's it. 18

19



### DR. DANIEL SCHLENK : Thank you, Dr. Bove. Dr. Gold? 20

21



### DR. ELLEN GOLD : Thank you. Good morning. I also want to 22



### commend the staff on a really much more thorough review 23



### and a very thoughtful one. We thought it was very good. 24



### We've consulted with each other, so I don't have a whole 25



### lot to add, but I did want to underscore just a couple of 26



### things. So the point about adjusting for the multiple 27



### other pesticides, I think is really important because the 28



### statement is mad e in multiple places that adjustment was 29



### made if these pesticides were used together a lot, if 30



### they were highly correlated. But if they're not related 31



### to the outcome, then I think what you're seeing, 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### potentially, you're over

- adjusting and potentially seei ng 1



### an attenuation, an adjustment toward the null in general. 2



### So I think that needs to be considered when interpreting 3



### the results. 4

5



### Also, this is a relatively minor point, but I also saw in 6



### several places that the comment was made that the 7



### agricultural health study had minimal selection bias 8



### because they had only two percent lost to follow up. 9



### Well, that's not the only source of selection bias. So 10



### they enrolled 82 percent, which is a really good 11



### enrollment, but the other 18 percent could be completely 12



### different and so could introduce selection bias that way. 13



### So the lost of follow

- up is not the only source of bias. 14

15



### The third point, which Dr. Bove touched on and I just 16



### want to highlight a little bit more, is this is a pretty 17



### typical occupational prospec tive study in that exposure 18



### assessment was made at the beginning and then long 19



### intervals passed before it was ever assessed again, and 20



### then people were followed up for outcomes. The reason I 21



### asked the question when I did the first day about the 22



### data colle ction is because while that's typical of some 23



### occupational studies, it's not typical of well

- done 24



### cohort studies that at regular intervals reassess the 25



### exposure and the covariates. So this could potentially 26



### relate in either under

- ascertainment or over

- ass essment 27



### of exposure, number one, and inadequate assessment of 28



### covariates. So that's why I think that‟s a limitation 29



### that could be added to the design features. 30

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### And then finally, the issue of the non

- representativeness 1



### of the AHS cohort and the small nu mbers of women. So 2



### it's impossible to know if the most highly susceptible 3



### group, namely black males, have a different

-- if there's 4



### an effect modification by race in terms of the effect, 5



### say, on prostate because they have a much higher risk of 6



### prostate ca ncer. 7

8



### And in terms of women, we know, as it was said about 9



### prostate cancer yesterday that there are probably 10 10



### different types, the same is true with breast cancer. So 11



### it was not possible to look at whether there were 12



### particular subtypes that

-- in ot her words, whether the 13



### exposure might predispose to certain subtypes; you simply 14



### couldn‟t do that. So that's a limitation as well. 15



### That's all I have. 16

17



### DR. DANIEL SCHLENK : Thank you. Dr. Young. 18

19



### DR. HEATHER YOUNG : I mostly concur with what's already b een 20



### said because we've consulted on the answer. I just want 21



### to make one other point, is that when you're doing a 22



### literature review, I also think it‟s important to note 23



### the gaps in the literature. And for the most part all of 24



### these studies are looking at occupationally exposed 25



### populations and there's a real dearth in the literature 26



### of drinking water exposure and residential exposures. 27



### And that is what the primary concern is when we're 28



### thinking about the population as a whole. So I think 29



### it's worth noting and acknowledging in the literature 30



### review that there's a real gap in the literature, looking 31



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### DR. DANIEL SCHLENK : Thank you. Yes, Dr. Gold? 2

3



### DR. ELLEN GOLD : Because Dr. Bove mentioned this table that I 4



### d rafted yesterday, I'm going to as my colleagues to 5



### double

- check it because it was done kind of quickly. But 6



### also, all I did was take the papers since 2003, and that 7



### were individually based. So we excluded the ecologic 8



### analysis because we felt they should be down weighted. 9



### If

-- and we would kind of encourage EPA to consider this 10



### if they use such a table

-- the idea is to use the weight 11



### of the evidence, then the papers that came before 2003 12



### that are individually based, case control or cohort, 13



### should be in cluded and I have not done that. 14

15



### DR. DANIEL SCHLENK : Any other panel comments? Dr. Portier. 16

17



### DR. KENNETH PORTIER : One of the reasons I kind of asked about 18



### thyroid cancer the other day was of all the cancers they 19



### looked at, that's the one that seems to be not going down 20



### and possibly going up. So, you know, a lot of the other 21



### cancers, it's kind of hard to get excited because they're 22



### all kind of declining and you would expect it would at 23



### least be staying level if atrazine and the long duration 24



### of cancer w as occurring. But with thyroid cancer, we 25



### really do suspect something is going on. And with the 26



### odds ratio of 4 in two of those four categories, our 27



### flags went up and said this is one we should be looking 28



### at. 29

30



### DR. ELLEN GOLD : Can I just point out that thyroid cancer is 31



### another good example of where the high

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### really not looked at and yet you still see an elevation; 1



### it's much more frequent in women, and they are under

2



### represented here. 3

4



### DR. DANIEL SCHLENK : Any other comments from the panel? 5



### Question 10? Okay. Let me go to the EPA. Do you have 6



### any questions or clarification at all? 7

8



### DR. CAROL CHRISTENSEN : No, not at this time. Thank you very 9



### much for the time and effort you put into that question. 10

11



### DR. DANIEL SCHLENK : Okay. Would you want to read in Question 12



### 11 into the record? 13

14



### DR. CAROL CHRISTENSEN : Yes. Question 11, subparts A and B: 15



### "Please comment on the extent to which the scientific 16



### information supports the integrative analysis contained 17



### in Section 3.3 of EPA's draft Issue Pap er with respect to 18



### the similarities, differences of the experimental 19



### toxicology and epidemiology findings. Please comment on 20



### any significant uncertainties in the epidemiologic 21



### findings." 22

23



### And Part B: "Please comment on whether the epidemiology 24



### literature published since the last SAP review, including 25



### the findings from the Agricultural Health Study is 26



### sufficient to justify changing the Agency's conclusion 27



### that atrazine is not likely to be carcinogenic to 28



### humans." 29

30



### DR. DANIEL SCHLENK : Thank you. Our lead d iscussion on that 31



### is Dr. Gold. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. ELLEN GOLD : Thank you. So we've consulted on this as 2



### well and we felt that there was a lot of overlap between 3



### this question and the prior one, especially Part A of 4



### this one. So if it‟s okay, I mean, we do go cancer

- by

5



### cancer, but Dr. Bove did a really good job of that so I'm 6



### not going to repeat that for Part A if that's okay with 7



### you, unless you want something specific. 8

9



### DR. CAROL CHRISTENSEN : Yeah. Certainly no need to repeat 10



### concerning the epidemiology finding. On Part A we were 11



### looking for sort of cancer

- by

- cancer, considering both 12



### the epi and the experimental database; is that correct? 13

14



### DR. ELLEN GOLD : I don‟t have anything to add to what Dr. Bove 15



### said. I can ask my colleagues if they do. 16

17



### DR. DANIEL SCHLENK : Well, is that consistent with Dr. Bove 18



### and Dr. Young? You have no further comments on A? 19

20



### DR. HEATHER YOUNG : No. No further comments on A. 21

22



### DR. DANIEL SCHLENK : Okay. Let me go back to the EPA just to 23



### make sure. Do you have some questions, clarificati on 24



### you‟d like to ask about A? 25

26



### DR. CAROL CHRISTENSEN : Right. Yeah. So in Part A, we're 27



### specifically thinking about that Section 3.3 again of the 28



### draft Issue Paper, pulling together what's known from the 29



### experimental toxicology, the animal bioassays, the in 30



### vitro studies for each specific cancer site. You know, 31



### for example, thyroid cancer that was just mentioned, you 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### know, the animal model is particularly sensitive to 1



### thyroid tumors, kind weighing that, providing some 2



### feedback and opinion, kind of weighi ng the fact that we 3



### have a very sensitive animal species in which we're not 4



### seeing. 5

6



### In fact, we have a high quality epi study in which we are 7



### seeing something, but only one, you know, that kind of 8



### thing

- pulling that kind of thing together. So any 9



### fee dback that any member has on that kind of thing by 10



### anatomical cancer site, that was ideally what we were 11



### getting at, and if we were not clear, hopefully that 12



### clarifies a little bit. 13

14



### DR. DANIEL SCHLENK : Yes, Dr. Young? 15

16



### DR. HEATHER YOUNG : I think I'm cor rect in stating for all of 17



### us that the recommendations that Dr. Bove went through 18



### for each of those cancers individually, we really did it 19



### considering both pieces of the evidence. For Question 20



### 10, we weren't really just looking at the epi studies in 21



### a vac uum, but we looked at them looking at also, what 22



### were the experimental toxicology findings, mode of 23



### action, those types of things. And so the 24



### recommendations we made in Question 10 would really be 25



### consistent with what we would we say for Part 11(a). We 26



### d idn‟t look at the epi studies in a vacuum when we were 27



### doing that. Am I speaking for everyone correctly? 28

29



### DR. ELLEN GOLD : And also I will say that some of this will 30



### come up in response to Part B. 31

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### DR. DANIEL SCHLENK : Let‟s go ahead with B. Yes, Dr. F owle. 1

2



### DR. JACK FOWLE : I don't know. Perhaps not sufficient amount 3



### is known, but I was just wondering is enough known about 4



### the cancer of mechanisms leading to thyroid cancer in 5



### experimental animals versus humans to say that they're 6



### some different mechan isms that would make the humans more 7



### sensitive? Any information that could shed light on 8



### possibly evaluating that because rats tend to be 9



### exquisitely sensitive to thyroid cancer and we didn't see 10



### it at all. So we were really contemplating that fairly 11



### dee ply. 12

13



### DR. DANIEL SCHLENK : Yes, Dr. Mendez. 14

15



### DR. ELIZABETH MENDEZ : Also, another little bit of information 16



### that I got this morning from our colleagues in ORD is 17



### that there are some data in frogs who are also very 18



### sensitive to thyroid hormone perturbation and that does 19



### not seem to be affected either. So we're struggling as 20



### to what appears to be a little bit of a disconnect there. 21

22



### DR. DANIEL SCHLENK : So if I understand you correctly, you're 23



### asking the panel to comment on other modes of action 24



### related to thyroid hormone impacts? Is that kind of the 25



### question? 26

27



### DR. ELIZABETH MENDEZ : I guess we're trying to understand what 28



### the etiology might be that would lead us to a different 29



### path in a human. 30

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### DR. DANIEL SCHLENK : Okay. Understand the susceptibility 1



### iss ues between species then for those particular effects. 2



### Does anyone have any input with regard to that? Yes, Dr. 3



### Meek? 4

5



### DR. BETTE MEEK : I just wanted to make the point that when we 6



### first discussed the framework for integration of 7



### epidemiological and toxi cology data at one of the earlier 8



### meeting that in fact it seemed relevant to walk through 9



### the weight of evidence for causality for the 10



### epidemiological data, initially, and then to integrate 11



### with the toxicological data, including weight of evidence 12



### for mode of action. So I think this would explicitly 13



### call out, addressing for each of those cancers, 14



### biological plausibility. So again, I'm not sure the 15



### extent that you did that, and certainly from the thyroid 16



### cancer perspective, it‟s a bit difficult to understa nd 17



### the human findings based on what we know about modes of 18



### induction of thyroid cancer in animals. 19

20



### DR. FRANK BOVE : I think what we're saying is this, that first 21



### of all, let‟s evaluate the epi evidence separately. And 22



### when we do that, we see that for mos t of the sites 23



### there's no evidence. For some of the sites, there's some 24



### suggestive evidence in the epi literature, which need to 25



### be followed up. I don‟t think we're ready to talk about 26



### mechanism at all. When we say suggestive evidence, we 27



### mean that yeah , there are a few studies out there that 28



### seem to be positive, but, you know, we're not ready yet 29



### to merge the tox with the epi. If you do that, what you 30



### end up doing most of the time is ignoring the epi 31



### findings and letting the tox findings trump it. So what 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### I would prefer we do is to take the epi evidence 1



### seriously, for a change, and see where the gaps are, 2



### where the research needs to be done and do it. And then 3



### when we get to a point where we feel that the epi 4



### evidence is pretty good, then start mergin g it with the 5



### tox; otherwise, you'll ignore the epi evidence. 6

7



### DR. ELLEN GOLD : I think also we have to be a little bit 8



### careful. I mean, I understand, looking at the weight of 9



### the evidence and looking at mechanisms and so forth, but 10



### in the early days of c ancer epidemiology, we didn‟t know 11



### mechanisms. We still don‟t. For many, I would contend, 12



### maybe for thyroid cancer we don't. We know relatively 13



### few risk factors, probably three that I can think of. 14



### And so sometimes the epidemiology will spur people on to 15



### do the mechanistic studies. And so I think in the case 16



### of

-- well, let me back up. 17

18



### For many of the cancers, the approach was well there are 19



### some neuroendocrine mechanism and that justified looking 20



### a prostate over and breast, for example, maybe thyro id, I 21



### don‟t know. You know, if it's having an effect on 22



### pituitary, maybe. But I think for some of these others

- 23



### - and I think we do have it in our comments

-- that we 24



### perhaps, don‟t know enough or the animal literature might 25



### inconsistent, but I think as epidemiologists, we worry 26



### about extrapolating farm animals in the fact that the 27



### mechanisms may not be the same. So I would put some 28



### cautionary notes like that. And I think we did try and 29



### integrate in what we wrote, sort of consideration of 30



### that. 31

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### DR. KAT HERINE ROBY : I just want to comment with respect

-- 1



### I'm not an expert on thyroid cancer, but I know ovarian 2



### cancer and I think it was well added into the position 3



### paper that actually, there's a real dichotomy there 4



### because what we do know about ovarian ca ncer is that an 5



### inhibition of LH should actually be protective. So there 6



### is really a separation between what I think, based on the 7



### epidemiology you say is suggestive, but the evidence that 8



### we know, mechanistically, would indicate really the 9



### opposite shoul d be the case, which may point to some 10



### other mechanism if the suggested comes to be correct. So 11



### it could be pointing to some different mechanism. 12

13



### The other point that I wanted to make is that, again, 14



### just specifically with regard to ovarian cancer, the re 15



### really are no animal model systems for the initiation or 16



### causal factors of ovarian cancer. So whatever is in the 17



### literature that might indicate there's a model looking at 18



### this compound or this toxicant causes ovarian cancer, 19



### there are no model systems to address that issue. 20

21



### DR. ELLEN GOLD : I would just point out that it was also 22



### mentioned in the issue paper that that mechanism that was 23



### originally based on the animal studies for breast cancer 24



### doesn‟t apply in humans. And so I think we have to be 25



### reall y careful on two scores; one is can you extrapolate 26



### from one species to the other in terms of mechanisms? 27



### And secondly, the fact that you don‟t have an animal 28



### model doesn‟t mean that you shouldn't pay attention to 29



### the epidemiology. 30

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### DR. DANIEL SCHLENK : Any other comments? So back to Dr. 1



### Christensen and Dr. Mendez, is this something you find 2



### useful, I guess, that you need? 3

4



### DR. CAROL CHRISTENSEN : Yeah. Maybe we can hear the responses 5



### to B and we'll kind of try to sum up what we‟ve heard at 6



### the end. 7

8



### D R. DANIEL SCHLENK : Yeah. I think that'll probably be a good 9



### strategy. So let‟s go ahead and move onto B. Dr. Gold? 10

11



### DR. ELLEN GOLD : Okay. By the way, in the introduction to 12



### Question 11, it seemed like you were asking whether there 13



### was a basis, sort o f cancer

- by

- cancer, to change your 14



### opinion from the 2003 SAP decision. So that's sort of 15



### the orientation of the comments for B. And I have sort a 16



### bullet point for each sort of category, if you will, and 17



### mostly grouped by cancers. 18

19



### So the epidemiologic evidence compiled since the last SAP 20



### review in 2003 regarding the carcinogenicity of atrazine 21



### does not justify changing the Agency‟s conclusions 22



### regarding prostate cancer, breast cancer, adult gliomas, 23



### oral, esophageal, pancreatic, melanoma, renal, laryng eal, 24



### lung, bladder, colorectal and liver cancer, or leukemia

- 25



### - with the exception of the hairy cell leukemia perhaps

- 26



### - chronic lymphocytic leukemia or multiple myeloma. 27

28



### The epidemiologic evidence regarding a potential 29



### association of atrazine exposure with ovarian cancer is 30



### suggestive of an association, but still inconclusive and 31



### requires more rigorous investigation with larger sample 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### sizes, which is difficult for this rare cancer that is 1



### likely to have a long latent period, and which also 2



### greatly compl icates the exposure assessment. 3

4



### For thyroid cancer we only have one study, the recent AHS 5



### cohort analysis, but it suggests a strong relationship

-- 6



### fourfold increased odds ratio

-- that is unlikely to be 7



### due to residual confounding. We've already ment ioned 8



### some of the concerns about how the cut

- offs were made for 9



### exposure. So those might be reconsidered, but that might 10



### explain why there's a non

- significant exposure

- response 11



### relationship, you know, like cutting it off at the median 12



### might have worked be tter. 13

14



### So this is very suggestive finding from a single study 15



### and is not sufficient to be certain of a causal relation 16



### between atrazine and thyroid cancer and thus requires 17



### replication in a larger study and more experimental 18



### investigation with regard to potential biologic 19



### mechanisms. 20

21



### The epidemiologic findings regarding an association of 22



### NHL and hairy cell leukemia with triazine use after 23



### adjusting for other pesticide exposures, although having 24



### small numbers of exposed cases in most of these studies, 25



### s uggest about a one and a half to two

- fold increase. 26



### Some of these estimates were statistically significant, 27



### and some findings had non

- significant exposure

- to

28



### response relationships, although the numbers of cases for 29



### each of these malignancies were fairly small. 30

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### However, these findings were not duplicated in the most 1



### recent cohort analyses from the AHS, which had twice as 2



### many cancer cases. Thus, while early studies suggested 3



### possible relationships of atrazine use with NHL and HCL, 4



### the more recent bette r designed and controlled studies 5



### with larger sample sizes did not replicate these 6



### findings, indicating, as mentioned in the Issue Paper, 7



### that sufficient evidence for associations of atrazine 8



### with NHL and HCL is lacking in humans or animal 9



### experimental stu dies. Although, the limitations of the 10



### AHS that we noted in response to Question 10 should not 11



### be ignored in considering these results. 12

13



### And then studies of pediatric cancers

-- by the way, I 14



### would just agree with the comment about not lumping all 15



### cancers together, and so with the pediatric ones, this is 16



### a little bit problematic in some that have teased out 17



### acute lymphocytic leukemia and found an increased risk, 18



### although a monotonic exposure

- response relationship was 19



### not observed. This is also an extremel y rare cancer, but 20



### the most frequent one in children. 21

22



### So the Issue Paper correctly concludes that the evidence 23



### is currently insufficient to determine if atrazine 24



### exposure increases the risk of pediatric cancers, 25



### particularly leukemia. That is all I hav e. 26

27



### DR. DANIEL SCHLENK : Dr. Bove, anything to add? 28

29



### DR. FRANK BOVE : No. I have nothing to add. 30

31



### DR. DANIEL SCHLENK : Dr. Young, anything to add? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. HEATHER YOUNG : No. Nothing to add. 2

3



### DR. DANIEL SCHLENK : Okay. So we'll go back to the

-- oh, let 4



### me open it up. Any other comments from further panel 5



### members? Yes, Dr. Akana? 6

7



### DR. SUSAN AKANA : Just a mild observation. I might've missed 8



### it, but we know in the rodent data that the atrazines can 9



### activate the adrenal's downstream in certain situations

. 10



### So notice here that adrenal cancers are not on the list. 11

12



### DR. DANIEL SCHLENK : Okay. Any other comments from the panel? 13



### Okay. Dr. Christensen, any questions or clarification 14



### for you? 15

16



### DR. CAROL CHRISTENSEN : Not specifically. Again, thank you 17



### very much for the time and attention to addressing this 18



### part of the question. In an attempt to sort of recap, 19



### maybe let me do so

-- and you can correct me if I'm in 20



### error

-- but what I heard you say, you know, in your 21



### evaluation of the cancer of the epidemiolo gical evidence 22



### and the cancer

- specific sites, you sort of automatically 23



### and inherently considered both the observational and 24



### experimental data within those evaluations and your 25



### comments regarding insufficient evidence or suggestive 26



### evidence or considering that information implicitly. I 27



### also heard a caution concerning moving, perhaps, too 28



### quickly to integrate the tox and the epi when there are 29



### some suggestive findings out there with some limitations 30



### and uncertainties as to how to interpret how far you can 31



### t ake that inference within the observational data at this 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### time. But still, your conclusions regarding specific 1



### cancer sites, again, inadequate or sufficient, in your 2



### opinion is informed by both toxicology and epidemiology. 3

4



### DR. DANIEL SCHLENK : Anyone want to take that one on? Dr. 5



### Gold? 6

7



### DR. ELLEN GOLD : I think that's a fair statement because we 8



### were also impressed by the fact that the Bradford Hill 9



### criteria were used, and one of those is biologic 10



### plausibility. And that sort of implies that you 11



### consider information about mechanism or evidence from 12



### toxicologic experiments to see if it‟s consistent. 13

14



### So I think that it's fair to say that the emphasis of our 15



### comments was on the epidemiologic studies, but I think it 16



### was also in consideration of the animal e xperiments and 17



### toxicologic data as well, when it existed. You know, I 18



### think it's really important to remember that a lot of 19



### public health policy is based on sort of imperfect 20



### science and sometimes you don‟t have the animal 21



### experiments, but you still can t ake preventive action and 22



### influence the incidence of disease. I think smoking and 23



### lung cancer is a great example. We didn‟t understand the 24



### path of physiology, but it didn‟t prevent public health 25



### from acting. 26

27



### DR. HEATHER YOUNG : I just want to emphasize again that just 28



### because we aren‟t sure about the biological plausibility, 29



### doesn‟t mean that it's implausible. And so because you 30



### don't know about the mode of action, it doesn‟t mean that 31



### there is no mode of action. So I think that‟s what we're 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### trying to say is that although it may not be known what 1



### the mode of action for some of these effects that we're 2



### seeing in humans, it doesn‟t mean that one doesn‟t exist 3



### or that may not appear in experimental evidence with 4



### animals at some point, or maybe it's not go ing to show up 5



### in experimental animals because we're not using the right 6



### models. And so I think you need to not throw away 7



### epidemiologic evidence that has really strong risks 8



### appearing just because we're unsure about mode of action. 9

10



### DR. DANIEL SCHLENK : Okay. So do you guys have any other 11



### further questions? Oh, Dr. Bradbury, do you want to make 12



### a statement? 13

14



### DR. STEPHEN BRADBURY : Question 10 and 11 really get to the 15



### crux of our February 2010 SAP where we're trying to bring 16



### together this framework conc ept of how to integrate 17



### experimental toxicology information with epidemiology 18



### information. And our goal is to more fully and 19



### completely and hopefully adequately bring epidemiological 20



### information into our risk assessment and evaluations. So 21



### to the extent you were thinking or the panel's thinking 22



### were not wanting to use epidemiology data on it, I want 23



### to make sure that's very clear, quite the opposite. 24

25



### What we're trying to work through is when you get to a 26



### very specific case, like let‟s say the thyroid 27



### i nformation, getting back to what Bette Meek was saying 28



### is with a very specific set of information before us and 29



### trying to exercise that framework is thinking through. 30



### So how do we try to reconcile and understand the 31



### uncertainties and try to articulate eve n qualitatively? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Here's what we know about these experimental models. How 1



### they react to what we do know in say, the rat or the 2



### mouse in terms of how cancers of the thyroid play out

-- 3



### blah, blah, blah

-- and here's this epidemiology 4



### information which is suggestive. 5

6



### And given that at a certain point in time you have to 7



### make a decision about what's the likelihood of risk 8



### associated with exposures to different amounts of 9



### atrazine. How do you try to pull this together, 10



### qualitatively, you know in many case s? And so that's 11



### where you are hearing some of us trying to probe a little 12



### bit, not so much in the generic, but when you have a very 13



### specific example before us. For example, the thyroid 14



### cancer, any advice you have on sort of how to integrate 15



### the informat ion. It's advice, you know, how do you pull 16



### this information together and try to reconcile some 17



### things. 18

19



### DR. HEATHER YOUNG : So as a public health professional, I 20



### would say you proceed with caution because you don‟t 21



### have a lot of evidence, until you do h ave more evidence, 22



### to make a decision either way. I think that's why we are 23



### sort of in the suggestive camps. We‟re not saying that 24



### there really is an association. We have a population

25



### based study that's highly suggestive. We're not sure 26



### about mode of a ction. So we're not saying there's a 27



### causal association, but we're also not prepared to say 28



### that it‟s unlikely. And so I think what we're saying is 29



### proceed with caution until we have more evidence. 30

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### DR. ELLEN GOLD : I would just reiterate once again that 1



### biologic plausibility is only one component of the 2



### Bradford Hill. And so I would agree with what Dr. Young 3



### said, but I think, you know, what you're doing is 4



### building a case and all the pieces may not fit perfectly, 5



### but if the case is strong for the other components, the 6



### fact that you don‟t know the mechanism, or that the 7



### mechanism appears to be different in a different species, 8



### would add a note of caution, but it doesn‟t down weight 9



### the rest of the strength of the evidence. 10

11



### DR. STEPHEN BRADBURY : The wor d "caution" is an interesting 12



### word. In different context it means different things. 13



### So could I ask if you could discuss how to articulate 14



### this kind of information in the context of uncertainty, 15



### as opposed to caution? If I can indulge the panel to 16



### think about ways to talk about uncertainties as you try 17



### to bring different information together. 18

19



### DR. DANIEL SCHLENK : Anybody want to take that on? Bette? 20

21



### DR. BETTE MEEK : I'm going to push the agenda a bit more on 22



### this to pose the question, given the uncer tainty that we 23



### have about the observed association, is there any way 24



### that we can use the information, quantitatively, in any 25



### context, to give us a comfort level, perhaps, or not, 26



### about the focus of any kind of dose response relationship 27



### modeling that we do ? Because that would at least enable 28



### us to take the information into account. This really 29



### goes back to an issue that came up, I think, early on 30



### when we were talking about a framework to integrate, and 31



### in terms of the epidemiological data, was really to d o a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### problem formulation to consider where will the epi data 1



### play out in this risk assessment and how can we most 2



### meaningfully us it. Because I'm sensitive to the issue 3



### faced by the Agency to say well, we should follow this 4



### up, but on the other hand, they have to make decisions 5



### now. So how could we use that information, even in some 6



### kind of semi

- quantitative sense to give us at least a 7



### comfort level or not? I think that's kind of the issue 8



### that I see. 9

10



### DR. ELLEN GOLD : I think it‟s hard to do this gene rically. 11



### You kind of need to do it cancer

- by

- cancer as we tried to 12



### do it. So let's take the example of thyroid cancer. 13



### They had four categories of exposure, and in a couple of 14



### them the risk ratio is four

- fold or more. But when I 15



### looked at the numbers, they had, I think in the four 16



### categories, 3, 12, 3, and 11. Something like that. I 17



### think we would agree that there's such variability around 18



### those estimates in the categories where you only have 19



### three people that trying to figure out

-- you could have 20



### a lot of misclassification, a lot of variability. And 21



### the fact that you don‟t have a monotonic dose trend 22



### doesn‟t really say much. So I made the comment if it 23



### were my data, I think I would've looked at the 24



### distribution and maybe tried to make sure that I have 25



### enough numbers in maybe two categories, like above and 26



### below the median, for example, which is not as satisfying 27



### as having four categories, but if reflects the reality of 28



### the situation. 29



### So that said, I mean, as the Agency has pointed out, you 30



### have t he temporality of the association. You have a 31



### four

- fold association

-- even if you divided it on a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### median, my guess is that would go down a little bit in 1



### each category, but let's say it's three

- fold, which I 2



### think it would be because the two larger catego ries were 3



### the ones where it was more closer to four so that's going 4



### to heavily weight your estimate. So it might come out 3, 5



### 3.5. That's a risk estimate that's unlikely to go away 6



### with adequate control for confounding and stuff like 7



### that. 8

9



### So my point be ing, temporality, strength of the 10



### association

- if you looked at it like that, you might 11



### actually have a dose response. We know very little about 12



### the etiology of thyroid cancer. And we're sort of 13



### missing, maybe biologic plausibility. We also don‟t have 14



### other studies, so we don‟t have consistency. T hat's why 15



### we use language like suggestive, as opposed to unlikely. 16



### So when talk about caution, I think it's reflecting those 17



### kinds of words, "suggestive" rather than "unlikely." 18

19



### DR. FRANK BOVE : Yes. And also "inadequate" as opposed to 20



### "not likely." Not likely is a very statement. 21



### Basically, you would have to ignore the epi evidence for 22



### many of these cancers to say not likely. So that's one 23



### of the things we're trying to caution you against doing. 24

25



### As for risk assessment, it would be nice if there was 26



### animal data and human data. For example, for 27



### tricoethylene, there is some animal data for kidney 28



### cancer and there is some human data. You can check and 29



### see if you extrapolate from epi studies and animal 30



### studies, you can get some kind of bounding that is great. 31



### That's not what we have here. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### On the other hand, suppose we have a situation where 2



### there's a birth defect cluster that's happening in a 3



### skyrocketing number of cases and there's no animal model, 4



### o r the animal model is negative like flutamide for 5



### example, what do you do then? You obviously work on the 6



### epi data. So I'm just saying, you know, for risk 7



### assessment purposes, you have information in front of 8



### you. You have some evidence from tox; you ha ve some 9



### evidence from epi. You may have less evidence in one or 10



### the other. You're just going to have to make some 11



### judgments. Okay. If there is evidence in both, that's 12



### makes it easy, but in most of these cases, that's not 13



### going to happen, especially in this case I don‟t see it 14



### happening. 15

16



### So what do you do? The tendency has been

-- and as I 17



### said, I've been on these panels since 2000

-- the 18



### tendency has been to really give sure shift to the 19



### epidemiological evidence. And this is a plea to not do 20



### that, even if it doesn‟t jive with the tox information 21



### because the tox information may be wrong. The animal 22



### models may be wrong. We may learn something down the 23



### pike. The epi information could also be wrong that's why 24



### we're asking for follow

- up work, especial ly on thyroid 25



### because there's only one study. But even on non

26



### Hodgkin's lymphoma where there are several studies and 27



### you can pool those studies, and that's been done, and get 28



### some kind of overall odds ratio somewhere in the range of 29



### 1.5 and 2 and you can use that if you want, but there's 30



### no animal information to bound that with. So what do you 31



### do then? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Any comments that we have? Yeah, Dr. 2



### Meek? 3

4



### DR. BETTE MEEK : Just a point of clarification, I wasn't think 5



### that we necessarily have to have the animal evidence to 6



### bound, but rather whatever approach is taken in the 7



### ultimate dose response characterization that we could say 8



### something, semi

- quantitatively, at least, about the risk 9



### that we've seen or we suspect in the epi studies. So it 10



### w ould be bounding it for another end point. 11

12



### DR. DANIEL GRIFFITH : You might think of it in terms of given 13



### the small numbers, your probability is somewhere between 14



### zero and one, and it might've only shrunk to somewhere 15



### between .1 and .9 because the numbers are just so small. 16

17



### DR. DANIEL SCHLENK : Any other comments. Again, let me remind 18



### the panel, please send your comments to Dr. Gold as she 19



### has to basically put this together in a manner that 20



### reflects the panel's input there. So just be sure to 21



### send your c omments there. 22



### Okay. Are we ready to move on? All right. Question 12. 23



### I think you're going to switch out to readers here; is 24



### that right? 25

26



### DR. ELIZABETH MENDEZ : I'm actually going to be reading. 27



### Dr. Rodriguez is going to come up to address any 28



### quest ions the panel may have. So good morning; Elizabeth 29



### Mendez, EPA. So we're shifting again and now we're going 30



### from epidemiology data to the pharmacokinetic information 31



### that we've been evaluating and considering in this 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### process. And I want to preface this by saying that one 1



### of the questions that you will see within Question 12 is 2



### about the PBPK model that we have no fully reviewed at 3



### this time. We felt that since we had you all in the 4



### room, it would be wise of us to avail ourselves of your 5



### expertise as we move forward towards the reg review 6



### process in 2013. So with that in mind, I'm just going to 7



### go forward and read the questions. Do you want me to 8



### read all four parts or

-- 9

10



### DR. DANIEL SCHLENK : I think just A through D would probably be 11



### appropriate, yeah

. 12

13



### DR. ELIZABETH MENDEZ : Question 12, subpart A: "Please 14



### comment on the strengths and limitations associated with 15



### a simplified pharmacokinetic modeling approach for human 16



### extrapolation." And that is in regard to the one we've 17



### been proposing. 18

19



### Subpart B: "Compare and contrast the strengths and 20



### weaknesses of using total radioactivity for 21



### pharmacokinetic analyses, as presented in Agency's Issue 22



### Paper, as opposed to using available pharmacokinetic data 23



### for the parent and the chloro

- s

- triazine metabolites that 24



### have similar toxicological properties to the parent." 25

26



### Subsection C: "As pointed out in the Agency Issue Paper, 27



### we are still reviewing a PBPK model submitted by 28



### Syngenta. As we complete our review of the Syngenta 29



### model, please comment on key aspects that EPA should be 30



### considering, concerning a PBPK model, including model 31



### credibility and a structure parameter values and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### documentation, model reliability. How well does the 1



### model simulate the dose metric relevant to the mode of 2



### action, and model applica bility? Does the model have 3



### essential features for intended application?" 4

5



### Finally, Subpart D: "Please comment on the extent to 6



### which the one

- compartment linear model of total plasma 7



### radioactivity derived from 14 

### C labeled atrazine, may 8



### account for inters pecies differences in 9



### pharmacokinetics." 10

11



### DR. DANIEL SCHLENK : Okay. Our lead discussion on that is 12



### Dr. Greenwood. Let's go through them, A, and then break 13



### and then B and then break. 14

15



### DR. RICHARD GREENWOOD : Okay. There is some overlap in some 16



### of these , but we'll be able to refer back to where we've 17



### covered it in earlier sections. We spent a little time 18



### discussing between ourselves and the people who were in 19



### discussions on this, some of the data and approach. What 20



### I'm going to say is sort of a compila tion of inputs from 21



### other people, but then will also have some other comments 22



### to make. So I'll make a start with an overview. 23

24



### I think the approach taken by the Agency assumes the area 25



### under the plasma concentration curve reflects the 26



### opportunity for exposure of the site of action to 27



### atrazine. That‟s one of the assumptions. And it also 28



### assumes that the toxicities of the metabolites are very 29



### similar. And on the evidence presented by the Agency, 30



### it's a reasonable assumption, particularly when you 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### cons ider that one metabolite, the deoxycholated atrazine 1



### dominates the profile. 2

3



### However, when we look at some of the data presented by 4



### Syngenta, which compare dosing by oral gavage and the 5



### dietary route, this suggests that actually, it might be 6



### worth revisiti ng some of the assumptions that underlie 7



### the approach using total radiolabel, and I'll explain 8



### why. If you're wanting to use area under the curve as an 9



### appropriate measure of exposure of whatever the site of 10



### action or sites of actions are involved in the 11



### suppression of the LH surge. 12

13



### Now, the Syngenta data show that when atrazine was 14



### administered by oral gavage, the area under the curve is 15



### larger than that found by dietary dosing, particularly 16



### for the parent compound and the mono

- deoxycholated 17



### metabolite. But the major difference is, really, were a 18



### much smoother plasma concentration curve found with only 19



### a few fluctuations when it's given with the feed. When 20



### you look at what happens with gavage, you get these huge 21



### transient peaks. And this is something t o bear in mind 22



### when you go back to looking at the radiolabel data. 23

24



### Now, if we look at the relatively modest differences in 25



### the overall area under the curve for DACT, then it's 26



### surprising that the suppression of the LH surge was 27



### produced by gavage admini stration, but not by dietary 28



### administration. So there's still a reasonable area under 29



### the concentration curve when it‟s dietary. 30

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### Now, several explanations offer themselves

-- I've put a 1



### little thought into this with colleagues that might 2



### explain this

-- it could be that for atrazine, total area 3



### under the curve might not be the appropriate measure for 4



### exposure. It could be

-- there's only one explanation, 5



### there's no evidence

-- it may be the area under the curve 6



### above a critical threshold concentration. So this is 7



### just a hypothesis. 8

9



### Another hypothesis that might explain this is that a 10



### sustained constant low concentration may not be 11



### sufficient to cause the effect. So the gentle pressure, 12



### it may require pulses, intermittent pulses of high 13



### concentrations that you get with oral gavage. Again, no 14



### evidence at the moment, it is just potential 15



### correlations. 16

17



### The other difference between dietary and gavage is that 18



### the dietary route takes about 24 hours to reach the high 19



### plateau of concentration but then is m aintained. And 20



### because feeding goes on longer

-- after the oral gavage 21



### finishes the last dose, they're still feeding

-- then, of 22



### course, the peak is maintained for longer in dietary. So 23



### a lot depends, I think, on where that might fall within 24



### that critica l four

- day period because the effect on the 25



### LH surge. 26

27



### It does open up some questions, and I think because of 28



### the approach taken by the Agency sort of depends on these 29



### assumptions being made, these really need to be checked 30



### out and looked at very careful . Given the importance of 31



### identifying an appropriate dose metric, I think it's 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### important that some effort is put in to just looking at 1



### that. I think a few suggestions for the Agency of how 2



### this might be tackled

- you don‟t have to be hung up on 3



### giving th is stuff by gavage or in the diet, there are 4



### lots of methods available now for giving, achieving 5



### constant plasma levels by subdermal implantation of slow

6



### release formulations. And you can get very high pulses 7



### in a very short time just by intravenous injec tion. It's 8



### an old trick, but it's been used lots of times. 9

10



### So some of these things could be tested with those sorts 11



### of experiments. But in the absence of information to 12



### where the interpretation of the Syngenta data of this 13



### link between pharmacokinetic behavior and pharmacodynamic 14



### activity

-- this is for the LH surge suppression

-- which 15



### is just one of the secondary lesions, resulting from some 16



### unidentified primary lesions. This is where we're stuck 17



### all the time. We don‟t know what the primary lesion is. 18



### But it's reasonable to examine all the available 19



### pharmacokinetic data in the way that the Agency has 20



### proposed. You've proposed to look at all the 21



### pharmacokinetic data, and that's the only way you can go 22



### forward. It's sensible. 23

24



### The area under the cu rve is the dose metric that 25



### represents the exposure of all tissue, target and non

26



### target, to the toxicant. You can‟t get away from that, 27



### so that area under the curve approach does give you a 28



### measure of the potential exposure of all tissues, not 29



### just targe t tissues, non

- target tissues. Everything that 30



### gets a blood supply gets exposed. So it really is a 31



### sensible way forward, from the pharmacokinetic point of 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### view, to consider area under the curve as a reasonable 1



### dose metric. The problems come when you the n try to 2



### relate to the pharmacodynamic activity. But I think the 3



### advantage of the use of the total radiolabel is that you 4



### can get quite a lot of reassurance from a mass balance 5



### check. It gives you some confidence that all the 6



### administered dose is account ed for. And I'll refer back 7



### to this when we look later at the physiologically based 8



### pharmacokinetic data because that is something that the 9



### registrant is going to look at, I think in trying to get 10



### a mass balance. It needs to be done. It's easy with 11



### radi olabel. 12

13



### It‟s still unique to apply some caution when you're using 14



### the old 14 

### C label atrazine studies because I've now got 15



### access to these and I've looked at them. It‟s quite 16



### reasonable because it‟s the usual thing to assume first 17



### order kinetics, which is what you've done for the overall 18



### elimination process. But there's good evidence when you 19



### look at the data you've presented, the Agency presented 20



### and Syngenta presented, that that's what it is. 21

22



### But the other thing that seems to hit me when I look at 23



### al l of this is that there's evidence that there are two 24



### first order elimination processes going on 25



### simultaneously. And that in fact, if you had enough 26



### data, you'd get a pretty good fit to a double exponential 27



### model. I'm pretty certain if you fitted a doubl e 28



### exponential model you'd get it because there seem to be 29



### two fractions of material in the plasma that have been 30



### operated on by a fast

- rate constant, one by a slow

- rate 31



### constant. The first one we will probably be 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### representing, elimination of that, in fact , the free 1



### material. And the slow elimination compartment, it would 2



### be probably that bound to proteins where the turnover is 3



### very much

-- the proteins are slower. 4

5



### So there is some evidence that that's from the non

- human 6



### primate data for double exponent ial nature of the 7



### elimination process, but there's also evidence in the 8



### rodent radiolabel data which you use to estimate the 9



### fraction elimination rate constant. Because if you look 10



### at those lower concentrations linear time plots and you 11



### look at the patter n of residuals from the fitted straight 12



### lines, given that you've only got four points for these 13



### things, it's always difficult. You've got three degrees 14



### of freedom, so it's tough to try and get anything, but if 15



### you look at the pattern of residuals, it's ac tually 16



### consistent: high, low

- low, high. And it's consistent 17



### across the different doses, across the different studies. 18



### And in fact, I've looked at the mouse study of Ross and 19



### co

- workers, 2009, and you get a similar picture there. 20



### So there is quite a lo t of evidence that there are two 21



### compartments. 22

23



### Well, fortunately, I think the fraction which is operated 24



### on by the slow process is probably very small, 25



### negligible, compared with the fast process, the free 26



### process. So although there is some bias introduce d into 27



### the estimates for the first order rate constant, it's not 28



### going to be

-- when you look at the variability in the 29



### whole system, it's not going to be really too important, 30



### I don't think. Though you went on to look at quite a few 31



### studies and you get v ery similar values for the first 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### order elimination rate constant across the study, which 1



### is, again, given the small number of points in each, it's 2



### heartening. I always get a bit more confident when I see 3



### it's repeatable rather than just statistically 4



### sign ificant. 5

6



### So I think the approach is sound. And the only 7



### deviations that I find from this consistency, which you 8



### pointed out, are the high elimination constants observed 9



### for the 50 and 100 milligrams per kilogram doses in the 10



### feed data. If you remember, there were factor of three 11



### probably out

-- well, in the grand scheme of things, 12



### that's again, not exactly a problem. But you do need to 13



### be careful about the interpretation of the radiolabel 14



### studies because all of them use a similar experimental 15



### design. T hat is, they use either single

- dose or equally 16



### spaced constant doses. And they take samples 17



### infrequently, usually every 24 hours. 18

19



### So this gives a really lousy definition of the 20



### pharmacokinetic profile. And you can't get anything else 21



### but a smooth plat eau out of it because when you join two 22



### lines together it‟s a straight line. And if they're 23



### taken at the same point each day, they're going to be 24



### roughly the same height. So you end up with what appears 25



### to be an nice plateau, but actually, if you look at the 26



### Syngenta data or where some of the others were, they've 27



### got a better definition, you see these huge spike 28



### superimposed on the top of it. If it‟s by gavage and you 29



### still see wobble about it in the dietary dosing. 30



### So again, that needs to be bore in m ind in an 31



### interpretation. But despite all of this, the studies can 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### still be useful because the area under this apparent 1



### plateau is still consistent proportion of the total area 2



### under the curve. So if you're trying to use that and 3



### correlate it with pharma codynamic activity, you're still 4



### in with a fighting chance. But the other thing that you 5



### need to be very careful about is this concept of the 6



### pseudo steady state being achieved after four days 7



### dosing. And there's no evidence of this in the Syngenta 8



### data or any of the others where they look at the 9



### individual components rather than the total radiolabel. 10

11



### In fact, if you look those, you get a pretty steady state 12



### in DACT, even with gavage, after Day 1. So after 24 13



### hours, it's up there and it's pretty well maintained. So 14



### there is very limited evidence for this. And the feed 15



### study is very difficult to explain. Now, there's one 16



### possible explanation

-- well, there are several 17



### explanations, again, and I give them for what their 18



### worth. It's possible that some bindings occur in over 19



### four days and once that's all saturated, then you do get 20



### this pseudo steady state. I don't see what some of those 21



### binding sites would be, but you may have other ideas. 22



### But if the pseudo steady state did involve binding, then 23



### the a rea under the curve would not be the freely 24



### available, and that is the pharmacodynamically relevant 25



### fraction, but it would be material which is bound, which 26



### is not available for interaction with the site of action, 27



### wherever it is. So again, you've got to be careful about 28



### how you interpret it. 29

30



### But if the rise in plasma concentration is

-- if we say 31



### that the plasma is in equilibrium with the tissues, then 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the implication is that there is a compartment within one 1



### or more tissues which needs to be saturated before you 2



### can get the final rising plasma concentration. And in 3



### that tissue or tissues

-- it could be any tissue

-- it 4



### could be that there is a slower distribution process 5



### taking place over four days so that you get this rise 6



### that feed observed in the t otal radiolabel in the plasma. 7



### And it would be interesting to see whether there was also 8



### a slow elimination process from this compartment. 9

10



### Well, if you look at some of the various studies, if you 11



### look at the poll dataset, there is some indication that 12



### fo llowing the single

- dose by oral gavage, there is a very 13



### slow elimination for liver and kidney, but an even slower 14



### elimination from red blood cells, and we know that that's 15



### due to binding, covalent binding, to the red blood cells, 16



### but also in muscle. The r ate of elimination from muscle, 17



### if you look at the poll data, is very similar to that 18



### from the erythrocytes. That's following the cessation of 19



### dosing and they did seven

- day daily dosing in that study. 20

21



### So I think that the whole topic has become rather 22



### confused in people's mind because the time to the pseudo 23



### steady state happens to be four days, which just by 24



### coincidence happens to be the critical exposure of which 25



### you got to hit in the rat estrous cycle. But the two are 26



### independent of each other; one i s pharmacokinetic and the 27



### other is pharmacodynamic. So it wouldn‟t matter if you 28



### had a study state when it is not at the critical period, 29



### it has no effect whatsoever. 30

31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Actually, if you say that you need a steady state in 1



### order to suppress the LH surge, then logically, that 2



### isn't achieved until after four days dosing. So you 3



### would never suppress the LH surge if you started dosing 4



### on the first day because it takes four days to achieve 5



### steady state. You'd always have to start dosing, if you 6



### apply that log ic, four days before the start of the 7



### critical period in the estrous cycle. Because it's only 8



### then that you'd get this pseudo steady state. So I think 9



### it's actually been a bit of a red herring, this idea that 10



### you need a pseudo steady state and it's come out of the 11



### fact that there are limitations in some of the 12



### radiolabeled studies. I'm afraid I've spilled over into 13



### some of the others, but I think this is probably the 14



### place where I felt my comments would best fit. 15

16



### So really, as far as I can see, there really aren't any 17



### grounds

-- or there are grounds, certainly, for 18



### examining, reexamining this idea of what‟s required, in 19



### term of the nature of the exposure and the level of 20



### exposure to suppress the LH surge over that critical 21



### period. Whether you need spi kes, whether a constant 22



### pressure ain't going to do, or whether you just need to 23



### get the concentration high enough that some critical 24



### period over those four days. I'll leave it there and 25



### hand over to colleagues. 26

27



### DR. DANIEL SCHLENK : Okay. Just so I'm cle ar, Dr. Greenwood, 28



### it sounds like you kind of hit all A through D in some of 29



### your comments. 30

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### DR. RICHARD GREENWOOD : I've got some other comments which 1



### are specific to the others, but I will relay it back to 2



### this. It has been sort of a long explanation, but I 3



### thought it was the easiest way of doing it. 4

5



### DR. DANIEL SCHLENK : Sure. No worries. I was just wondering 6



### how it was going to split up with everybody else. Okay. 7



### Thank you. Dr. Hayton? 8

9



### DR. WILLIAM HAYTON : Well, I agree with my colleague's 10



### comme nts and I would add a few thoughts, in terms of Part 11



### A question to comment on strengths and limitations of the 12



### simplified pharmacokinetic modeling, using the one 13



### compartment model. I think one strength we could mention 14



### is that it is simple, in the sense t hat it has a minimal 15



### numbers of parameters to estimate. And because of that 16



### you need a fairly limited number of data points. So a 17



### lot of the radioactivity concentration time profiles 18



### really wouldn't support more complicated modeling. So I 19



### found that a s trength that could be mentioned. 20

21



### I also found another strength is that the one compartment 22



### approach does have utility in that the basic idea here is 23



### to estimate exposure to total triazines and because the 24



### data seemed to conform to the model that the pur pose for 25



### which we want to use the model is satisfied. And then 26



### finally, we have data available from three species: from 27



### rat, monkey and human. I thought that was a strength. 28

29



### In terms of limitations, you know, I think the point that 30



### Dr. Greenwood broug ht up that total radioactivity seems 31



### to include some fraction that is albumin adduct or plasma 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### protein adduct, which doesn‟t have toxicologic activity. 1



### So it would be nice to be able to get rid of that. From 2



### the data that I saw, particularly the CODAR 20 11, study. 3



### It seemed that if you look at atrazine and its three 4



### chloro

- s

- triazine metabolites, the DEA, DIA, and DACT, 5



### the total radioactivity, if we could rid of the bound 6



### radioactivity, covalently bound, that that would track 7



### the sum of those four metab olites fairly closely. I 8



### think that's one weakness or limitation of using just 9



### total radioactivity and because it's data from the 10



### literature

-- old data

-- there's probably no way to 11



### subtract that out. 12

13



### Another limitation, I thought of the one compartme nt 14



### system, its simplicity is a virtue, but also, some of the 15



### finer points of the pharmacokinetics tend to be obscured. 16



### So we don‟t know much, using that model, about saturable 17



### binding, transport of metabolism that could give some 18



### kind of a non

- linear rela tionship between the 19



### administered dose and the exposure of the site of action. 20

21



### I found some comfort from the fact the half

- life of total 22



### radioactivity is dose independent over a broad range of 23



### doses. I thought that give some comfort that there are 24



### non

- linearities that could confound the analysis. 25



### Thanks. 26

27



### DR. DANIEL SCHLENK : Okay. Dr. Meek? 28

29



### DR. BETTE MEEK : Yeah. I have very little of substance to 30



### add. I'm really encouraged that the Agency is moving 31



### along to estimate the internal dose metric. An d I think 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### this is as step along the way. I think that you've also 1



### indicated that the ideal approach would be a 2



### physiologically based pharmacokinetic model for all of 3



### the reasons kind of mentioned by previous commenters, in 4



### terms on the limitations of the approach. 5

6



### DR. DANIEL SCHLENK : Okay. Any other panel member input on 7



### the PK stuff here? Okay. Are you guys going to address 8



### B separately then? Okay. We have a question from Dr. 9



### Rodriguez

- question/clarification. 10

11



### DR. CHESTER RODRIGUEZ : Just a com ment, actually. One of the 12



### issues that we found, especially with the human study 13



### that were presented is that it was a significant mass 14



### balance issue. When atrazine DEA, DIA, and DACT were 15



### monitored, those four species only accounted for 14.5 16



### percent of th e dose. So 85 percent of the dose, they 17



### don‟t know where it went. So in terms of us using 18



### caution, we feel at this point that radiolabel studies 19



### may actually safeguard against that. But until we have a 20



### better understanding of mass balance, I think this 21



### represents a reasonable approach at this time. 22

23



### DR. DANIEL SCHLENK : So I'm assuming that‟s a question that 24



### you're asking. Is that what you're asking the panel to 25



### correspond on that? 26

27



### DR. CHESTER RODRIGUEZ: No. It‟s just a comment. 28

29



### DR. DANIEL SCHLENK : Oh, okay. I think we got that. Do you 30



### guys have anything to say about that? 31

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### DR. RICHARD GREENWOOD : I agree that you need to have mass 1



### balance, and it's one of the things I think that is going 2



### to be addressed if we look at the contribution by 3



### Syngent a in their paper they presented. It's one of the 4



### things they need to look at. It‟s true, it does need 5



### looking at, but the problem is it's not just mass balance 6



### with the total radiolabel. You know where it is, but you 7



### don't know how it's divided within c ompartments within a 8



### tissue. You just combust it and you get the total. 9

10



### You often need to go on for a long time, the study, to 11



### make sure you can see what the real turnover rate of it 12



### is

- get enough points to be able to do the proper 13



### analysis of the el imination to see whether it's single, 14



### double, or triple exponential, for instance, whether it's 15



### saturable and so on. 16

17



### DR. DANIEL SCHLENK : Sure. The comment

-- it‟s just my own 18



### personal comment; it seems you would also need to know 19



### what those glutathione adducts are as well because it 20



### seems that a fairly large chunk of the metabolism seems 21



### to be glutathione conjugated. So consequently, maybe 22



### that 76 percent that‟s there, a large amount of that 23



### could be some of these unknown conjugates that are 24



### present. S o that needs to be characterized as well 25



### because that would not necessarily be toxic, per se, it 26



### would be a nontoxic metabolite at that point. 27

28



### Any other comments on A? Okay. Let's go ahead and go 29



### through B and then we'll take a break after B. Dr. 30



### Gre enwood, again, do you want to lead off? 31

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### DR. RICHARD GREENWOOD : Yeah. Thank you. Well, I think the 1



### question, it's the sort of thing that you might set for 2



### the undergraduates actually, compare and contrast is the 3



### wording. But it's a problem. This is no t the 4



### straightforward business, choosing what sort of model to 5



### use because all of these methods have their own strengths 6



### and weaknesses, and I'll try to look at some of these in 7



### light of what we've seen with atrazine. 8

9



### I think all people doing studies in pharmacokinetics have 10



### to ask themselves to start with, what do I want to use 11



### the data for because there are two extreme approaches; 12



### one you use a single compartment model, use total 13



### radiolabel, and it's got advantages, it's very simple to 14



### carry out. You' ve got a very, very good sensitivity and 15



### the modeling is easy. On the other extreme, you've got a 16



### big physiologically

- based pharmacokinetic study, where 17



### you have lots of compartments, and when you do the 18



### modeling, lots of boxes connected by differential 19



### e quations and you've got to parameterize all of those, 20



### you can end up with more than 40 parameters. 21

22



### If you look at the Syngenta model, I think there are 40

- 23



### odd parameters that I looked at. And it‟s a lot of hard 24



### work to get sufficient data to estimate a ll of those, 25



### some available in the literature. So often people opt 26



### for a sort of middle path, which is a compromise between 27



### the two, in terms of the amount of work and what you get 28



### out of it. Because what you get out of a radiolabeled 29



### study is difficult to interpret. And the big advantage 30



### of the physiologically based pharmacokinetic models is 31



### that they are very easy to interpret, in terms of the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### physiology and the lesions that happen, a disruption of 1



### physiology when you put in toxicant. And you can 2



### actu ally look to see whether the toxicant is affecting 3



### the pharmacokinetics, which can happen. In some of the 4



### studies I've done, it certainly does happen. So you can 5



### either go for the complex and the arguably more realistic 6



### physiologically based model, but y ou need to get the 7



### information to parameterize them. 8

9



### These days, life has been made a little bit easier 10



### because you can use mass spec, and so the limits of 11



### quantification really have gone down. The problem is, in 12



### order to get it to the mass spec, the L C mass spec, 13



### you've actually got to do sample preparation, which all 14



### needs validation, involves dissection of individual body 15



### component, quantitative extraction, preliminary clean up, 16



### and often

-- well, usually you have to, in order to get 17



### reliable results , you need labeled unalikes to correct 18



### for matrix effects in the mass spec analysis. And it is 19



### very difficult, as been pointed out, to achieve a mass 20



### balance. Even though mass spectrometry detectors can get 21



### down to lower levels of quantification, they st ill cannot 22



### achieve the lower levels of quantification that you can 23



### get with radiolabeled compounds with combustion and 24



### scintillation counting. 25

26



### I guess the important thing is, though, that what the 27



### methods used for extraction of tissues do is make sure 28



### t hat you are actually extracting the free. Normally you 29



### do not extract if it's bound

-- if it's covalently bound, 30



### you don't extract it

-- but you extract the free 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### material, which is the material that's physiologically, 1



### toxicologically relevant. 2

3



### Assuming a sort of mammillary model with the circularly 4



### system providing rapid mass transport around to every 5



### tissue. Then when steady state is achieved the levels in 6



### all the tissue will change at matching

-- not necessarily 7



### at the same rate

-- but matching rates and you get a sort 8



### of steady state achieved. That's with one dose and then 9



### elimination. The area under the curve does represent the 10



### overall opportunity for exposure of the site of action 11



### and it doesn‟t matter whether it's one or more tissues. 12



### It does n ot matter where it is located. 13

14



### So these physiologically based pharmacokinetic models do 15



### provide information which is readily interpretable and it 16



### supports interpretation of modes of action. It doesn‟t 17



### assume that the parent compound and metabolites are equi

18



### toxent, you don't have to make that decision. 19

20



### But it also can help to identify where you get deviations 21



### from the expected behavior

-- which do happen

-- where 22



### you change the physiology by the poison in the animal. 23



### For instance, if you modify card iac output or you modify 24



### hepatic function. Then you are going to change 25



### distribution and you are going to change elimination 26



### rates. That will happen in time, you get time

- dependent 27



### parameters. I'm sure it makes life very interesting for 28



### the modelers. 29

30



### N ow, simple models which are based on far fewer samples 31



### to be analyzed, a lot less preparation required and 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### total radiolabel, it's easy to measure and it‟s sensitive 1



### and it could be automated so you can get through a lot of 2



### samples. As I said before, the mass balance is readily 3



### checked and that is important. However, I think as Dr. 4



### Hayton said, the problem is if you've got bound material 5



### mixed in that total fraction, then that's not available 6



### for distribution to the site of action. 7

8



### So the modeling is si mpler, but the interpretation, in 9



### terms of toxicology and mode of action is far more 10



### difficult and it could be misleading, particularly if 11



### there were big differences between the toxicities of 12



### parent compound and metabolites. If there is significant 13



### bindin g, then depending on the method of preparation, of 14



### course, the area under the curve might not provide a good 15



### measure of exposure of the site of action. 16

17



### I mean, one way of getting around this is if you think 18



### that there is significant binding, you could a lways do a 19



### radiolabel study, ultra filtrate the plasma, count the 20



### filter and count the filtrate and you'll then see what 21



### proportion of it is actually bound and you can get a 22



### handle on it, but it is one more step. So without doing 23



### that, you can actually ov erestimate, if you like, the 24



### exposure of the site of action. So I'll leave it there. 25

26



### DR. DANIEL SCHLENK : Dr. Hayton? 27

28



### DR. WILLIAM HAYTON : Yeah. Let me just quickly summarize what 29



### I thought strengths of using radioactivity were, compared 30



### with specifi c assays for the chloro

- s

- triazines. I think 31



### with total radioactivity, you get some comfort that you 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### haven't missed any toxicologically active metabolites and 1



### you get good sensitivity. Of course that depends on 2



### specific activity, but that can usually be made very 3



### high. I thought that's the strength of the total 4



### radioactivity approach. 5

6



### A weakness is that the label is distributed among 7



### multiple chemical species and each one of those species 8



### has its own pharmacokinetic behavior, so total 9



### radioactivity ten ds to hide much of the underlying 10



### kinetic behaviors. From what we know of the chloro

- s

11



### triazines, they seem to be equally equipotent, 12



### toxicologically. So to the extent that they represent 13



### total radioactivity, you know, that's going to work out 14



### okay. I g uess the uncertainty that's already been 15



### mentioned several times is that there seems to be quite a 16



### bit of radioactivity in plasma that may not be the 17



### chloro

- s

- triazines and some of it has quite a bit longer 18



### half

- life. So what‟s going on there introduces s ome 19



### uncertainly into the overall consideration? 20

21



### DR. DANIEL SCHLENK : Okay. Dr. Meek? 22

23



### DR. BETTE MEEK : Yeah. I have nothing much to add. 24

25



### DR. DANIEL SCHLENK : Any other panel comments for that? Dr. 26



### McManaman? 27

28



### DR. JAMES MCMANAMAN : You know, I think these were good 29



### comments from the group that explored this issue, but I 30



### want to add a couple of cautionary notes. If you look at 31



### your Slide 22 from the Agency, there is a difference in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the elimination rates for the various compounds of DIA, 1



### it is much fa ster than the DACT. If you look at the data 2



### presented by Syngenta, they have DACT as being the 3



### primary compound under which protein adducts can occur or 4



### glutathionylation. 5

6



### So depending on differences

-- and there be may be 7



### differences between species and the rates of these 8



### adduction processes or the elimination processes, so by 9



### using the radioactivity, I think you don‟t get at that. 10



### And using the single compartment model, I don‟t think you 11



### get at that. So I would be a little careful since we 12



### really don‟ t know what‟s going on with the human as much 13



### as we do with the rat, I don‟t think you can extrapolate 14



### because the rates, you know, if the rate of adduction is 15



### different from humans to rats, then you may have a 16



### different toxicity and that has to be conside red. So 17



### that's just a cautionary note. 18

19



### DR. DANIEL SCHLENK : Thank you. Any other comments before we 20



### break? We'll just wait until we finish the complete 21



### question before we come back to you guys to finish up, if 22



### that‟s okay. Let's go ahead and move on t o Question 23



### 12(c). Dr. Greenwood? 24

25



### DR. RICHARD GREENWOOD : I'm not going to say a great deal on 26



### this, but one of my colleagues will, I think. I think 27



### we've already gone over a lot of this, but one of the big 28



### advantages, I think, of this model of mice wort h pursuing 29



### and validating and so on is it does hold out the prospect 30



### of really reliable, scientifically based extrapolation 31



### between species. It's one of the advantages, I think. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So I think it is worth pursuing this because 1



### physiological models for humans there have been because 2



### of the pharmaceutical industry. 3

4



### There are some problems with this model, as submitted by 5



### Syngenta, and one of the weaknesses is that there was 6



### some in vivo parameterization from in vitro metabolic 7



### studies. So that's always a prob lem. But the curves are 8



### well defined by frequent measurements in time. The 9



### predictions, though, if the tissue concentration depend 10



### heavily or will depend heavily on selected tissue plasma 11



### partition coefficient. These are really critical and you 12



### get this with lots of methods, both in environmental 13



### analysis and in pharmacokinetic analysis. Those values 14



### are critical and can introduce real bias. And I'm really 15



### glad to see that Syngenta intend to verify these in vivo. 16



### I think that‟s essential and it's one of the things that 17



### they said they would intend doing. 18

19



### Amongst other things, it may actually help to identify 20



### binding within tissues in multiple compartments within 21



### tissues and might provide a check on what appears to be a 22



### slow distribution compartment as we mentioned earlier. I 23



### think the limitation of this, and again the Agency needs 24



### to think about this, is that because of the limits of 25



### quantification, it‟s going to be very difficult to use 26



### this to validate for low, probably human

- relevant doses. 27



### I see t hat as something that needs looking at carefully 28



### by the Agency

-- well, would need to be looked at before 29



### they can go ahead and adopt it. Thank you. 30

31



### DR. DANIEL SCHLENK : Dr. Hayton? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. WILLIAM HAYTON : I'd like to pass to Dr. Meek because I 2



### think she i s going to enumerate all of the information 3



### requested in the question. And if she doesn't I do have 4



### a laundry list, but I think she's got the better one. 5

6



### DR. DANIEL SCHLENK : Okay. Dr. Meek, you've been tapped. 7

8



### DR. BETTE MEEK : Well, the question is fa irly broad, as you'll 9



### note. So we're trying to determine how best to divide 10



### this up. I wanted to say that I I'm suitably impressed 11



### with, first of all, the considerable progress on the 12



### development of the PBPK model and its review for all the 13



### reasons and t he value of the model for all the reasons 14



### that we've heard here. It avoids a number of 15



### generalizations and the value of the sensitivity analysis 16



### associated with the model for testing hypothesis is 17



### considerable as well. So I would strongly encourage the 18



### A gency to work with the proponent to ensure that the 19



### model is sufficiently robust to meet their needs. I 20



### mean, given its considerable potential to more accurately 21



### predict interspecies and intraspecies differences in 22



### kinetics and to test a wide range of hyp othesis regarding 23



### critical determinates. 24

25



### So in relation to key aspects that should be considered 26



### in review of the PBPK model submitted by Syngenta by the 27



### Agency, I reference d the recently released WHO guidance 28



### on the C haracterization and A pplication of 29



### P h ysiologically B ased P harmacokinetic M odels and R isk 30



### A ssessment. It was referenced by one of folks presenting 31



### to the meeting of the other day. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Development of the guidance drew broadly on expertise 2



### internationally in both PBPK modeling and risk assessmen t 3



### and involved protracted input from a drafting group in a 4



### series of related workshops. This group developed a 5



### comprehensive list of questions for consideration 6



### relevant to evaluation of the biological bases, model 7



### simulations, reliability and applicabili ty of specific 8



### PBPK models for application in risk assessment. 9

10



### I‟d note also that a subset of these questions is equally 11



### applicable to other types of pharmacokinetic models and 12



### it would be helpful to step through them, then, in 13



### relation to the modeling a pproach currently proposed by 14



### the Agency. 15

16



### I‟m always concerned when we hold, often, more data 17



### informed approaches such as PBPK modeling to higher 18



### standards of verification than approaches which are based 19



### on less inference. So it's important to consider 20



### stepping through these questions for all modeling based 21



### approaches. 22

23



### The document also makes recommendations concerning 24



### process for consideration of PBPK models in regulatory 25



### risk assessment. This includes early and iterative 26



### involvement of regulatory ris k assessors in model 27



### development, access to both internal and independent 28



### expertise, documentation by model developers in standard 29



### format risk assessment applications and independent 30



### review. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So I'm not sure whether I want to go through the list of 1



### conside rations for considering PBPK models in risk 2



### assessment. I'll briefly try to summarize what‟s here 3



### and submit, for the record, the more detailed listing. 4



### But for the biological basis: 5



### Are the major sites and processes of absorption, 6



### storage, transformati on and clearance included in 7



### the model? 8



### Are the mathematical equations of ADME based on a 9



### sound theoretical biological basis? 10



### Are the input parameters related to the 11



### characteristics of the host, chemical or 12



### environment? 13



### Is the sum total of the tissue blood flow rates 14



### equal to the cardiac output? 15



### Is the ventilation perfusion ratio specified in the 16



### model within physiological limits? 17



### Are the volumes of compartments within known 18



### physiological limits? 19



### Is the approach used to establish partition 20



### coefficients with in the domain of valid application? 21



### Is the method used for estimating biochemical 22



### parameters adequate? 23



### Is the allometric scaling of parameters, if 24



### applicable, done appropriately? 25



### Is the integration algorithm proven for solving 26



### differential equations in sim ilar models? 27



### And has the computer model code been verified for 28



### syntax errors and the accuracy of units? 29



### And then the model simulation of data: 30FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Has the model been evaluated for its ability to 1



### predict kinetics under various conditions, 2



### consistent with its in tended application? 3



### Does the model consistently reproduce the general 4



### trend of the data, the peaks, bumps and valleys, 5



### saturation of metabolism, or only portions of one or 6



### more data sets? 7



### Are the model predictions within an acceptable level 8



### of corresponden ce with the experimental data that 9



### was considered to be within a factor of 2? 10



### And the reliability for model testing, uncertainty and 11



### sensitivity. 12



### Is the model capable of providing predictions of the 13



### concentration time course of the candidate dose 14



### metrics in the target organ or a suitable surrogate 15



### compartment? 16



### Has the uncertainty in model predictions of dose 17



### metric been assessed for the relevant exposure 18



### conditions? 19



### What is the reliability of the data used for 20



### calibrating and/or evaluating the PBPK model? 21



### And is the sensitivity of the dose metric to change 22



### in numerical values of input parameters 23



### characterized for relevant exposures? 24



### And then, of course, Applicability: 25



### Has the model been developed and evaluated in the 26



### species and life stage of relevance to the risk 27



### assessment? 28



### Do the exposure routes in the model correspond to 29



### those of anticipated human exposures, as well as 30FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### those of the critical studies chosen for the 1



### assessment? 2



### Has the model been tested for the exposure doses and 3



### durations of relevance to the intended 4



### extrapolations? 5



### And does the model contain point estimates of 6



### parameters, consistent with the purpose of 7



### application? 8

9



### So one of the difficulties that we came up against is 10



### really this kind of transparent presentation of the model 11



### content for risk assessment and I was encourage to hear 12



### that, certainly, Syngenta was aware of the requirements 13



### for documentation and are presenting it in that context. 14



### I was also pleased to hear that they had the model 15



### evaluated by external reviewers as well. And I 'll leave 16



### it at that. 17

18



### DR. DANIEL SCHLENK : Anything to add, Dr. Hayton? 19

20



### DR. WILLIAM HAYTON : No. 21

22



### DR. DANIEL SCHLENK : Okay. All right. Open for any other 23



### panel members. Comments? Yes, Dr. Horseman? 24

25



### DR. NELSON HORSEMAN : This is almost certainly a completely 26



### naïve question, but this last point here, model 27



### applicability, I wonder if I might hear some comments on 28



### how these models might be applicable, depending upon 29



### whether one is concerned about LH surge suppression 30



### versus thyroid tumorigenesis. It seems to me that model 31



### applicability implies a relationship to the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### toxicological, physiological endpoint s

. T hat would be 1



### interesting for me to hear. 2

3



### DR. DANIEL SCHLENK : Who wants to take that one? Dr. 4



### Greenwood? 5

6



### DR. RICHARD GREENWOOD : I think that i t‟s difficult. All the 7



### pharmacokinetic data will tell you is

, what is the likely 8



### exposure of all tissues. And this is one of the problems 9



### we face here with atrazine. We don‟t know for sure whe re 10



### the site of people has suspicions. We don't know where 11



### th e primary lesion occurs and we don‟t know how much 12



### actual exposure, if you like, of the primary site of 13



### action or sites of action to produce a sufficient lesion 14



### to cause the secondary lesions that we observed as the 15



### symptoms, including LH suppression and s o on

. 16

17



### So at the moment, we're really in the dark. And what 18



### we're trying to do with all of this sort of approach, 19



### what people try to do
, is to just get a measure of the 20



### opportunity for a particular compound or a group of 21



### compounds to interact with a sit e of action. If you know 22



### what that is, and with the pyrethroids, with OP's, then 23



### it's really easy, relatively. But when you don‟t know 24



### where it is and what it is, this is the best that you can 25



### do in order to try and decess overall exposure of the 26



### site of action because the area under curve, the other 27



### plasma, really, because all tissues get exposed to that. 28



### It really is the best measure of overall opportunity for 29



### a compound to interact with any particular site of 30



### action. 31

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### One of the problems is that you don‟t know that when 1



### you're looking at individual tissue distributions, for 2



### instance. You don‟t know whether that‟s just a sync 3



### which keeps it away from the site of action or whether 4



### it's a good thing, if you like, from the atrazine, if 5



### it's getting ther e to the site of action. So it is 6



### difficult, but I think at the moment, this is probably 7



### the best that we can do and you can use these such 8



### models, even the simple models to try and get an estimate 9



### of exposure over various time scales. And, of course, 10



### so me things can sometimes take longer exposure, maybe, 11



### than for some of these things like interaction of an OP 12



### with an enzyme, where you get an instant effect. 13

14



### DR. BETTE MEEK : Really, we're trying to get a little closer 15



### to the internal does even though we don't necessarily 16



### know what the target is to consider much more accurately, 17



### interspecies differences and human variability. So 18



### ultimately, you're trying to move from the external dose 19



### to at least a closer surrogate for the internal dose to 20



### be able to repl ace the kind of default uncertainty 21



### factors that we use for that purpose, but it relates 22



### solely to exposure when you don‟t necessarily understand 23



### the adverse outcome pathway. 24

25



### DR. PENELOPE FENNER

- CRISP : One of the areas that iterated in 26



### the WHO guid ance , with respect to applicability, had to 27



### do with developing models appropriate to the 28



### subpopulation of interest that you were focusing on. And 29



### of course, with respect to atrazine, there's a whole lot 30



### of data and interest in defining the toxicological 31



### consequ ences of exposures at various life stages. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### There's a lot data generated on that point, but as far as 1



### I can tell, from this point in time, the simple PK model 2



### only models for an adult; an adult which isn‟t even an 3



### average adult. 4

5



### And to this point in tim e, seems not to be modeling for 6



### any of the younger life stages of concern that's really 7



### the focus of this risk assessment. So it's just a point 8



### to reemphasize in conducting and developing these models, 9



### whether it continues to be the simple one or the most 10



### sophisticated PBPK model, one has to consider having 11



### variations in the application of the model that are 12



### consistent with the life stages of concern. 13

14



### DR. DANIEL SCHLENK : Any other comments on Letter C? Yes, Dr. 15



### Portier? 16

17



### DR. KENNETH PORTIER : You know, in that long laundry list that 18



### you did, is there something in there that says 19



### implementing this on a platform that's transparent for 20



### others to look at? 21

22



### You know, I was sitting there thinking okay, five years 23



### from now we'll be sitting and you will have imp lemented 24



### it in something that we can‟t run on our computers. So 25



### I'd like add that, way at the bottom of the list, that I 26



### think it‟s consistent with other things we've heard like 27



### with the dietary programs, you implemented in SAS

, I 28



### don‟t have SAS , so why d idn't you implement it in 29



### something I can run it in. 30

31



### DR. DANIEL SCHLENK : Dr. Meek? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. BETTE MEEK : Just to underscore the point, there was a lot 2



### of discussion in this project on exactly that issue and 3



### the need for transparent modeling platforms that ar e 4



### available to all. And some of that is evolving. First 5



### of all, for the purposes of increasing understanding and 6



### uptake. 7

8



### DR. DANIEL SCHLENK : Okay. Any other comments on Letter C? 9



### Okay. Let‟s go on to D. Dr. Greenwood, do you want to 10



### start off on t hat? 11

12



### DR. RICHARD GREENWOOD : Yeah. It‟s asking us to comment on 13



### the extent to which this one compartment model can 14



### account for intraspecies differences. You can do it, but 15



### there's a lot of uncertainty associated with it because 16



### it‟s difficult to introdu ce into one compartment model 17



### differences in metabolic capabilities, for instance, 18



### binding properties of various tissues. But you can 19



### extrapolate using empirical allometric factors. You can 20



### do that, empirically. But what you can‟t do is carry out 21



### the e xtrapolation on the basis of any sort of good 22



### scientific physiological and metabolic information. So 23



### again, they'll be a large uncertainty associated with any 24



### extrapolation between species, using the single 25



### compartment model. 26

27



### Another problem with it, rea lly, it's difficult to 28



### compare the exposure time needed for infecting rats with 29



### that in humans . B ut a lot of the reason is the 30



### information we've got in rats is based on the same dose 31



### being given on each day. It‟s simply because people are 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### looking at the suppression of the LH surge. So all of 1



### the experiments are being carried out in the same way 2



### because that's what they're interested in. So it may be 3



### more difficult to try and extrapolate this sort of 4



### information across to human exposure because that‟s no t 5



### the usual mode of exposure. 6

7



### One worry for me is that the rat did not scale to monkey 8



### when they used the standard allometric scaling factors. 9



### In fact, he went the wrong way. Part of the problem, I 10



### think, is in different species, you need to consider 11



### binding sites as well as metabolism because,

-- as I've 12



### said earlier, without going on about it any longer

-- 13



### it‟s actually the concentration of free material that 14



### counts. And one area where I think these physiologically 15



### based pharmacokinetic models are g oing to have the 16



### advantage in terms of extrapolation over these simple 17



### models is because you can get the physiological 18



### parameters. You can actually parameterize a lot of these 19



### from the literature. 20

21



### Well, it's got that advantage. It‟s based on something 22



### you can measure as well as cardiac output and so on, 23



### blood flow to various organs, organ weights. And there 24



### have been a couple of studies lately, one by Boudoir (ph) 25



### and one by Buoy last year, where they've actually taken 26



### human physiologically based phar macokinetic models and 27



### then played games. They've used stochastic modeling. 28



### And what they've done is to say

, okay , i f you look at 29



### young children

, you look at old people, then things like 30



### cardiac output , renal function, hepatic function all 31



### change, and we 've got measures of how they change. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So you can also say, okay, what happens if you get 2



### somebody who weighs 120 kilograms instead of 60 3



### kilograms? And you can play the games by altering the 4



### parameters of the model and then doing a stochastic 5



### approach a nd trying to generate a population based on the 6



### sort of population variability that you've got. Okay, 7



### it‟s in early stages, but what it's trying to do is to 8



### try to l ook at individual variability using the model. 9



### You can‟t use those sorts of games. You c an‟t play those 10



### sorts of games with a single compartment model. 11

12



### So again, going back to what Dr. Meek said, actually, 13



### you've got to decide what do you want to use this model 14



### for and if you want to extrapolate between life stages 15



### and if you want to extra polate between species, probably 16



### it‟s not the best way of doing it. You may get more joy 17



### out of the more complex model, given all the drawback s to 18



### those that we've already outlined. 19

20



### DR. DANIEL SCHLENK : Dr. Hayton? 21

22



### DR. WILLIAM HAYTON : I agree with my c olleague and I guess 23



### I'll just emphasize, based on total radioactivity

-- I 24



### don't know what to make of it, but I don‟t know whether 25



### it rises to the level of being disconcerting, but why the 26



### half

- life in monkey actually came out to be shorter than 27



### rat when you'd expect it to go the other way. We have 28



### only have three species here. I mean, you know, rat, 29



### monkey, and a very limited amount of data in human for 30



### the scaling part. But other than that anomaly, it seemed 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### like the volume of distribution for total r adioactivity 1



### is relatively constant across the species. 2

3



### Certainly, the rat elimination rate constant seemed to 4



### scale to the human value, even though that's based on 5



### limited observation, it seemed to scale according to 6



### expected allometric scaling relatio nships, you know, 7



### three

- quarter our body weight relationship. I'd say 8



### overall, from what we have now, it‟s seems to work 9



### satisfactorily. Well, let me hasten that it will be 10



### interesting to see what's going on with the monkey and it 11



### seems like those studie s are in the works , r ight , that 12



### Syngenta is doing that? 13

14



### DR. DANIEL SCHLENK : Dr. Meek? 15

16



### DR. BETTE MEEK : Yeah. I have nothing to add. Thanks. 17

18



### DR. DANIEL SCHLENK : Any other panel input on Letter D, 19



### Question 12? Okay. Go back to the Agency and deter mine 20



### whether or not you guys have what you need. Any 21



### questions or clarification? Okay. Let‟s go ahead and 22



### move onto 13. And before we do, I think Agency has some 23



### further questions or clarification for some of the 24



### previous questions we were given. 25

26



### DR. ELIZABETH MENDEZ : Yeah. Before we proceed to Question 27



### 13, Dr. Dellarco would like to ask a question for 28



### clarification. 29

30



### DR. VICKI DELLARCO: I'm Dr. Vicki Dellarco. I'm in the 31



### Office of Pesticide Programs. I'm the science advisor in 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### the Office of the Director. I want to come back to the 1



### question of how we integrate different lines of evidence 2



### that we're seeking your advice on. There's been logic in 3



### how we've proceeded with all these SAP reviews. 4

5



### In the first review that we had in February, introd uced a 6



### framework that we would use to pull together information 7



### to inform an opinion about what the compound might do in 8



### humans. And so, really this question that we're asking 9



### you about how to integrate the experimental, both 10



### mechanistic, empirical, and t he epidemiology comes back 11



### to that framework. 12

13



### What we're seeking advice from you on is this: if you 14



### remember that framework, there were certain attributes of 15



### it. It was a hypothesis

- based framework, taking all the 16



### evidence and trying to understand what the compound does, 17



### kinetically, dynamically along a pathway. It was an 18



### evidence

- based framework. And it was a framework that 19



### integrates different data streams and being able to 20



### characterize a conclusion and the confidence in that 21



### conclusion and the unce rtainty around that conclusion. 22

23



### So if we go back to the thyroid example

-- because it was 24



### discussed a lot

-- to kind of use it as an example of the 25



### guidance that we're seeking on. As we look at the 26



### different tumor sites that are suggested in the 27



### epidemio logy and how we bring all information to bear on 28



### interpreting that is

-- it's hypothesis

- based, so you 29



### would ask, okay, what do we understand about thyroid 30



### cancer in humans because we're interested in humans? 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Rather than saying we don‟t know. There coul d be any 1



### mechanism to try to lay down some reasonable hypothesis, 2



### based on the experimental, medical, epidemiologic 3



### literature about what could be some key events involved 4



### in that. So as an example, we know radiation is a 5



### factor, so one would want to look at urogenesys. One 6



### would want to go to thyroid human disease models and see 7



### what the association is in those models with thyroid 8



### cancer, and perhaps, perturbation of that thyroid axis 9



### and elevation of THS could be a factor. 10

11



### But again, laying down that hypothesis, drawing on all 12



### knowledge . A nd then to start looking at the experimental 13



### evidence to see what it tells us about how it may evoke 14



### those key events. You know, i s the compound a mutagen? 15



### Do you have a sufficient basis to draw that conclusion? 16



### Do we have studies that have looked at perturbation of 17



### the hypokalemic pituitary thyroid axis? What do we 18



### understand about that? What is the epidemiology telling 19



### us? 20

21



### So where we could use your help is how can we structure 22



### that analysis in a scientific ally rigorous way? How can 23



### we structure it in a way that is transparent in how we 24



### reach conclusions so that it's understood how we're 25



### weighing different line of evidence? In some cases, the 26



### epidemiology may be given weight. In other cases, 27



### experimental and epidemiology may be given equal weight. 28



### It depends on the tumor site that we're looking at and 29



### the information that we have. So this is basically what 30



### we're asking you to do so that when we go into the 31



### experiment, what are the things that we should t hink 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### about in characterizing the strength of that evidence and 1



### the limitations in that evidence. 2

3



### When we look at the epidemiology, you've given us some 4



### very good advice there on how we should look at the 5



### epidemiology. Now we need your advice in how we bring 6



### this all together, again, in a structured, rigorous, 7



### transparent way so that in the end, when we reach 8



### conclusions, it‟s very transparent to everybody what the 9



### uncertainties were; how much weight you put on those 10



### uncertainties or how much confidence in the conclusion. 11



### And so it's a multi

- discipline process. So this is 12



### probably a question that requires a multi

- disciplined 13



### input. It would really be helpful if the panel could 14



### come together; the epidemiologist, the biologist, and the 15



### risk assessor to g ive us guidance on this. 16

17



### DR. DANIEL SCHLENK : Does anybody want to sort of tackle 18



### that? We have Dr. Portier. 19

20



### DR. KENNETH PORTIER : It's really good. I know what you're 21



### trying to get at. And I was sitting here looking back at 22



### the notes from the Febr uary meeting. You broke it out 23



### into the exposure modeling, the PBPK modeling, the PD 24



### modeling, and then you 're trying to bring it all 25



### together. And nowhere in there did we really link the 26



### epidemiology quantitatively. It's kind of qualitatively. 27



### And tha t the framework starts with the exposure modeling. 28



### So we've been doing a lot of discussion about exposure 29



### modeling. And I think in this case, we have that 30



### compartment pretty well discussed. I see that going on. 31

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### The issue I was going to bring with the PK modeling is 1



### that in your framework, you kind of start with the 2



### typical adult, but I didn‟t see that PK model here. What 3



### I saw was an atrazine

- specific model that's much simpler 4



### than your typical adult model that you kind of started 5



### with in your framew ork. And I felt like, in this case, 6



### you kind of did what I 'd call "top down" modeling rather 7



### than a "conceptual up" modeling, which I thought what the 8



### framework was all about. Dealing with here's a typical 9



### adult , here's some typical processes; atrazine i s going 10



### to impact these processes, these pathways and produce 11



### this kind of signal in the body that's going to result in 12



### this kind of

-- and I'm not sure the PK model we're 13



### looking at here is quite

-- and I'm looking at Dr. 14



### Greenwood because he was sitting there as well. I hope 15



### he knows what I'm talking about. I don't think the PK 16



### modeling in the atrazine cases is as good as what you 17



### would conceptually add in the framework. I have nothing 18



### to say on the PD modeling. 19

20



### I' ve been sitting here thinking, thou gh, about how we get 21



### the epidemiology end , and I understand their point. W hen 22



### we start looking at the PK and the PD modeling and 23



### there's no information to inform the typical adult model, 24



### then we have to fall back on the epidemiology and say, 25



### w hat are the associations? What's the strength of the 26



### association? Are these associations helping me to better 27



### understand whether something is really happening in the 28



### body that I should look at? 29

30



### I don't think we really discussed that very well, even in 31



### the last meet ing. We make the qualitative link, but then 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### we go looking

-- and I think that's the epidemiologist 1



### point

-- we go looking for excuses to throw the 2



### epidemiology out rather than think of excuses for why the 3



### epidemiology should force us back into the lab to look 4



### more carefully at mechanisms. I don‟t know how

-- you're 5



### asking how we put those together. And I think I'll throw 6



### that back to the panel and say do we have any paradigms, 7



### any structures to help us think that way? And I haven‟t 8



### seen any. 9

10



### I know w hat you‟re asking for, but I don‟t know how to 11



### take that loose epidemiology information and kind of link 12



### it in a qualitative way or as a driver for mechanism 13



### research, even if it's to push the mechanism research 14



### out, or push more epidemiology out. 15

16



### Unfor tunately, pushing the epidemiology out is typically 17



### too expensive, in terms of time and effort and timeframe 18



### - for EPA's timeframe. You know, they have to make a 19



### decision in a year and a half; they're not going to do a 20



### full

- blown repeat epidemiology study in a year and a 21



### half. So I'll turn it over to Dr. Bove. Maybe that's 22



### kind of got them thinking, trying to translate some of 23



### this

. 24

25



### DR. FRANK BOVE : I don‟t know if this is going to help at all, 26



### but in the February meeting and in this meeting, again, 27



### it' s important, first of all, to get the evaluation of 28



### the epi evidence right. There were problems with the 29



### 2010 Issue Paper. There are problems with this one. We 30



### see an advance, but we still see weaknesses in just 31



### evaluating the epi data. So that's the f irst thing. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Before we talk about integration, let's actually evaluate 1



### the epi data in the best way we can and maybe

-- I mean, 2



### sure, you can‟t do an epi study right off the bat, but 3



### you can pool data. For example, for the prostate cancer 4



### situation with t he Saint Gabriel plant, a simple thing 5



### could be done/should've been done to answer that 6



### question. What about these five cases? What were their 7



### exposure experiences? What happens when you compare 8



### those five cases with the controls that also were there 9



### be fore the plant started the screening program? 10

11



### This is nothing to do. And you can actually then answer 12



### the question: Is there something there a t that plant or 13



### not? If there isn‟t, then the case is closed on prostate 14



### cancer, for example. 15

16



### So these are th ings that can be done if you evaluate the 17



### epi evidence properly and appropriately. Again, go over 18



### the years, there's a history to this, in 2000, there was 19



### hardly any. We called it a brevity and superficial 20



### evaluation of the epi evidence. In 2003, it was a little 21



### bit better, but there was a lot of evidence that wasn't 22



### discussed and it was focused on prostate cancer and there 23



### were problems with that. 24

25



### In 2010, we had ecologic studies, mostly to evaluate, and 26



### the evaluations were problematic. That's the best I can 27



### say. This is better, but you still have a ways to go. 28



### So my feeling is let's get the evaluation of the epi data 29



### right. There are things that could answer some of these 30



### questions. Thyroid cancer

- there's no way to answer 31



### that question withou t further study. Most of the cancers 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### where we talked about suggestive evidence or inadequate 1



### evidence, they require further study. There's no way 2



### around it. You could do some pooled analysis, though, in 3



### the meantime, but you have an ongoing agricultural health 4



### study. You could encourage states

-- we were just 5



### talking about this

-- you can encourage states to use 6



### their municipal drinking water data and their cancer and 7



### birth defect registry to start answering some of these 8



### questions too. 9

10



### So that's on th e epi side. First things first; before 11



### you talk about integration, let's see what evidence we 12



### have, evaluate it appropriately, and see what things we 13



### can do in the short term to enhance that information. 14



### Then when we‟ve got that together, then we can sta rt 15



### integrating. It‟s done all the time. If you look at the 16



### risk assessments for trichloroethylene PCE, so on, that 17



### are just recently being done , t hey're integrating to tox 18



### and epi information. In the case of trichloroethylene, 19



### it's the human data that's taking precedence. In PCE, 20



### it‟s not. And they're categorizing it for carcinogenicity 21



### based differently because of that. I think that those 22



### are examples that EPA can look at its own risk assessment 23



### process to see how these things are getting integrated. 24

25



### DR. DANIEL SCHLENK: Dr. Meek? 26

27



### DR. BETTE MEEK : Thanks. I think sometimes what complicates 28



### true integration of available data is that we really are 29



### reacting to chemical

- specific data. So we're not drawing 30



### more broadly on, for example, what we know abou t human 31



### disease. And I also think that the way the questions are 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### posed here, looking at pieces of the

-- we haven't been 1



### asked to look at the totality of the data. We've been 2



### asked to look at the epidemiological data or what's the 3



### critical effect. That kind of thing. 4

5



### I think that there needs to be some broader thought about 6



### how we bring what we know about diseases models into 7



### account in interpreting both the epidemiological and 8



### toxicological data. When I read through the section 9



### here
, which related t o integration, I kind of walked away 10



### saying I don‟t feel there's been an integration yet. 11



### Again, I don't think we're drawing broadly enough on the 12



### available information. 13

14



### I think the other issue that complicates this is we don‟t 15



### really have a hypothesiz ed adverse outcome pathway yet. 16



### So it's as a basis for trying to integrate available 17



### information t hat's complicating the issue as well. 18

19



### DR. DANIEL SCHLENK : Dr. Chambers and then Dr. Horseman. 20

21



### DR. JANICE CHAMBERS : Well, I appreciate that you're going to 22



### have to deal with atrazine in 2013, and so it's on the 23



### table right now. It seems like for answering this broad 24



### question, which is a very good question, you need a case 25



### that has a little bit more solid information here and 26



### there. The epidemiology evid ence seems to be suggestive, 27



### at best, at this point. The mechanisms we're looking at 28



### for the point of departure and everything is an entirely 29



### different type of thing. The mechanism isn‟t known 30



### there. The exposure data from environmental and to a 31



### certain extent, from the occupational are pretty fuzzy. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### So you really don‟t have good solid information and 1



### enough mechanistic information and enough pharmacokinetic 2



### information right now to do that. 3

4



### If you're going to look at integration, I think you need 5



### a mo re solid case where you have a mechanism solid 6



### epidemiology data and more information that all can be 7



### integrated as the first case to try to do that, and 8



### probably atrazine doesn‟t have all of those elements. I 9



### know it's on the table and all, but I don‟t t hink that's 10



### really feasible right now. 11

12



### DR. DANIEL SCHLENK : Dr. Horseman? 13

14



### DR. NELSON HORSEMAN : My point is very similar to Dr. 15



### Chambers' but maybe worded in a different way. I don‟t 16



### know whether you can call it pharmacodynamic, 17



### toxicologic, physiologic

- the fact that we've been asked 18



### to consider as a point of departure, which is the LH 19



### surge suppression, I had a sense that that was related to 20



### epidemiological findings, if you will, related to 21



### menstrual cycle irregularities and reproductive 22



### senescence, a nd some other animal things

-- so on and so 23



### forth

-- which we heard nothing about in this meeting. 24

25



### The epidemiology that we heard about is cancer 26



### epidemiology. We haven‟t heard anything about cancer 27



### pharmacodynamics or toxicology or anything else in th is 28



### meeting or in the white paper. I get the sense that 29



### we're being asked to integrate t wo things that have 30



### nothing to do with one another, except atrazine

- to go 31



### back to Dr. Chambers' point. Maybe that's a wrong 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### interpretation. If it is, I'd like to he ar somebody 1



### correct me. 2

3



### DR. DANIEL SCHLENK : Dr. Greenwood? 4

5



### DR. RICHARD GREENWOOD : Again, I was at the earlier meeting 6



### where we started to look at epidemiology, and I think 7



### there, the message that came across to me was that one of 8



### the main weaknesses in many of the studies was poor 9



### exposure data. I think the Agency is trying to pool 10



### together the exposure data, but they‟re not there yet, 11



### but they're getting close now. I think once that's 12



### together, then it may be possible to do some stronger 13



### studies. 14

15



### DR. KENNETH PORTIER : I wanted to follow

- up on something Dr. 16



### Greenwood was talking about at the end of his discussion 17



### on Part D , which was that they're starting to use these 18



### PKPD models in a play mode, right, a "what if" mode, a 19



### hypothesis generation mode. So again, when I thought 20



### about the framework, I was thinking, oh, great, they'll 21



### have kind of a generic model and then they can look at 22



### the epi and say well, thyroid. What would have to be 23



### happening in this mode for us to see something happening 24



### with th yroid? 25

26



### So in a sense, you're generating that hypothesis. You're 27



### looking at the epi and saying okay, the epi people are 28



### saying it‟s kind of possible. Can we do something in our 29



### generic model to produce

-- you know, we know this is an 30



### endocrine disrupter. We know from the ecotox that it has 31



### affects on certain animals. Amphibian effects maybe are 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### not directly translatable to humans, but we know 1



### something about what's going on. 2

3



### Can we just play with this model and see if something 4



### happens? That was, to me, one way of generating a 5



### hypothesis . I t‟s not testing it, but it kind of 6



### feasibility. Does the model say it's feasible? If y ou 7



### can‟t tweak the model enough to get that effect, then 8



### you're at least in a position where you're saying, well, 9



### you know, w e've looked at our current big knowledge, our 10



### current understanding of PKPD processes

, and we can‟t 11



### make it happen . T hen you can turn back to the community 12



### and say if you still think there's really something 13



### happening here, propose something different, bu t we've 14



### kind of exhausted the obvious avenues. To me, I thought 15



### that was part of the framework. What I'm calling "that" 16



### is kind bottom up from basic concepts and trying to make 17



### something happen in this conceptual model. 18

19



### DR. DANIEL SCHLENK : Dr. Meek? 20

21



### D R. BETTE MEEK : Just a brief response to that, Ken. I think 22



### what the modeling is telling us currently is that we 23



### handle the chemical very similarly to rats. In fact, 24



### that the chemical is rather evenly distributed. So it 25



### doesn't address the PD component because we don‟t have a 26



### hypothesized AOP here. So the PBPK model doesn‟t really 27



### help us in that context. 28

29



### DR. DANIEL SCHLENK : Dr. O'Byrne and then Dr. Jerde. 30

31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. KEVIN O'BYRNE : I share Nelson's concerns about the 1



### fragmentation. One of the things that frustrates me is 2



### the lack of epi data on those reproductive impact of 3



### atrazine. Apparently in the September meeting there were 4



### two papers brought forward. I mean I looked at those. 5



### One wasn't worth looking at and the other one was just so 6



### weak. And I just wonder, why has that been neglected, in 7



### terms of

-- I don‟t mean neglected from your perspective, 8



### but in terms of the epidemiologists tackling this issue. 9



### Is there a reason why it's being left, given that the 10



### gonadatropines seem to be so central to t he mode of 11



### action, et cetera, with atrazine? 12

13



### So that's one point that I'd like to make. The other is 14



### -- I think Richard Greenwood made some very good comments 15



### earlier on about the diet versus the gavage dynamics of 16



### atrazine and its metabolites in the pla sma. And he's 17



### absolutely right. Those sorts of peaks following gavage 18



### versus their absence in diet could have major affects on 19



### how the brain is per ceiving and processing those signals. 20

21



### I think very recently, Stavert Lightman, in Bristol in 22



### the UK, has been looking at the brain's response to 23



### pulsatile release of corticotropins, up to the 24



### gluco corticoids. And it's astonishing, the sensitivity 25



### of the brain to the pulsatile reception of these hormones 26



### and how you get translocation and pulsatile 27



### transcript ion. It's absolutely fantastic what he's 28



### demonstrated the sensitivity of the brain to pulse modes. 29

30



### W hen they gavage these animals and you get these huge 31



### peaks, goodness knows what's going on inside the brain. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### I think the move towards the

-- in my poin t of view

-- as 1



### a sort of simple physiologist, moving towards feeding 2



### animals, if you can't get it into the water, is much more 3



### relevant to looking at the mechanism s of action of 4



### atrazine on the reproductive system, and I suspect other 5



### systems as well. I don't know if that‟s helpful at all. 6

7



### DR. DANIEL SCHLENK : Dr. Jerde? 8

9



### DR. TRAVIS JERDE : I wanted to second what Dr. Horseman said 10



### and offer this: so you read through a lot of this and 11



### what's available to the public and what‟s available to 12



### the scientific community we‟ve heard from industry 13



### representatives, something along the lines of there's no 14



### compelling evidence available that atrazine may be 15



### carcinogenic to humans. And that sounds an awful lot 16



### like atrazine is not carcinogenic to humans, to a lot of 17



### people. 18

19



### I guess I'd like to support the epidemiologic side of 20



### this because it seems like the conclusions that they're 21



### making, based on a very limited literature in most cases 22



### -- separate types of cancers, separate diseases, likely 23



### separate mechanisms of a ctions

-- t he conclusions they're 24



### drawing are, wait a minute , s tep on the brakes . W e can't 25



### really say something so definitive that sounds an awful 26



### lot like this isn‟t carcinogenic. 27

28



### Furthermore, a lot of these studies are on high exposures 29



### in the plant. As a public health issue, we could even 30



### deal with that personal protective equipment, help the 31



### workers and that sort of thing. And yet the water, to a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### larger prospective, the exposure in water might be the 1



### bigger problem. From what I understand, from w hat you 2



### guys have been saying, there's almost nothing on it. And 3



### so this gets back to Dr. Horseman's point, integrating a 4



### model

- we're losing what I think is a fairly strong 5



### statement from them, which is we need to understand this 6



### a lot more than what we currently do. That's becoming 7



### obscured in trying to get the right model and we really 8



### don‟t know what the right model is because we don‟t have 9



### any clue, from limited epidemiologic studies what that 10



### might be. 11

12



### And once we have better data from say, the thyroid, and 13



### now we may look at the thyroid and say okay, in these 14



### patients that are exposed, if there is an increase in 15



### thyroid, we looked at the thyroids , t his changes. Now we 16



### can go back to the model system and say
, okay, we're 17



### going to change this and see what happens and now we've 18



### got our model. 19

20



### So I'm just concerned as a scientist who looks somewhat 21



### translational, but I do consider myself a molecular 22



### biologist who uses models. I'm just concerned that some 23



### of those epidemiologic findings might be ge tting obscured 24



### by so much talk about modeling and integration. 25

26



### DR. DANIEL SCHLENK : Okay. Dr. Young? 27

28



### DR. HEATHER YOUNG : I think I want to come back to the point 29



### that I made earlier, too, is the huge gap in the 30



### literature is that it's looking almost exclusively at 31



### occupational exposures, which is why we have very few 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### studies looking at reproductive outcomes because the 1



### occupation that we're looking at is predominately male

2



### dominated. And there are a few studies looking at female 3



### gynecologic cancers

, b ut for the most part, again, we're 4



### focusing on occupational exposures, not on community 5



### exposures where you would expect to see, if there are 6



### any, the reproductive effects . B ecause then we would 7



### have a much broader population that we're looking at, a 8



### muc h better representation of female. So again, I think 9



### it's hard to ask us to integrate when we don't have all 10



### the pieces of the information. 11

12



### DR. DANIEL SCHLENK : Dr. Roby? 13

14



### DR. KATHERINE ROBY : And to take that to the next step, also, 15



### we need to continue to explore the mechanism of action. 16



### A s we learn more about the mechanisms of cancer, and we 17



### learn about the mechanism of atrazine action, along with 18



### epidemiology, we can begin to make the ties, but there's 19



### not only gap in the epi data, but there's gap in 20



### understanding mechanism of action of atrazine and 21



### mechanism of cancer development. So all of these data 22



### need to grow together, but there needs to be continued 23



### exploration of atrazine's mechanism of action. 24

25



### DR. DANIEL SCHLENK : Dr. Gold? 26

27



### DR. ELLEN GOL D : I wanted to make a couple of points. First, 28



### I want to agree

-- I think Mr. Horseman made the point

-- 29



### in the Issue Paper, the mode of action that's emphasized 30



### is largely the neuroendocrine LH surge one. And it is 31



### true that that was discussed pretty t horoughly in the 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### September meeting to look at reproductive effects, but 1



### I'm not sure that it applies, necessarily. It applies, 2



### perhaps, to some of the cancers we're looking at, but not 3



### all of them. So point Number one is there was a little 4



### bit of a disco nnect there
, but it probably reflects what 5



### we know at the moment. 6

7



### Secondly, the question was raised why we're not doing a 8



### better job of looking at reproductive, and part of it is 9



### because we're not looking at the community . B ut part of 10



### it is because the e pidemiologic study that we're 11



### depending on the most was a cancer institute study that 12



### was focused on cancer outcomes. So when they made an 13



### attempt to look at reproductive outcomes, I think it was 14



### done in a less than optimal way, even in that cohort. 15

16



### The other point I want to make is it's occurred to me, 17



### sitting and listening to this and being part of the SAP 18



### that talked about the framework for using epidemiologic 19



### evidence that I think the Agency is undergoing a little 20



### bit of a culture change in trying to figure out how to 21



### incorporate epidemiologic data ; t hat it comes from a 22



### place of using mostly toxicologic data. And this is 23



### like, you know, a new piece. How do we deal with this? 24



### And culture change takes time. 25

26



### So I think we've been trying to inform yo u about our 27



### feelings about if you have epidemiologic data but you're 28



### lacking toxicologic or mechanistic data, you shouldn't 29



### ignore the epidemiologic data. And finally, that leads 30



### to having the epidemiologic data drive

-- or provide the 31



### impetus for doing f uture mechanistic

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### -- just because you don‟t know, it doesn‟t mean you 1



### should ignore it and say there's unlikely cancer risk. 2

3



### DR. DANIEL SCHLENK : Okay. Nice discussion. I'm not sure 4



### where it's going to go in the report. Perhaps, yea h. 5



### All right. Yes, Vicki? 6

7



### DR. VICKI DELLARCO: So I think we've gotten some nuggets of 8



### advice . I f it could be pulled together in a logical way, 9



### it would be very helpful. And if I can summarize what 10



### I've heard, you guys don‟t have to integrate, we have to 11



### integrate. So we want your advice in things that we 12



### should be thinking about. And what I've heard is some 13



### advice. 14



### 1) Before you can integrate, you have to ensure that 15



### you've done a thorough analysis of the individual lines 16



### of evidence. We've been given some advice on the 17



### epidemiology and things that we should go back and look 18



### at more closely, in terms the analysis. And that 19



### includes the experimental data too. 20



### 2) Secondly, I heard that if there is an empirical 21



### finding, whether it comes from an animal stu dy or it 22



### comes from epidemiology, you start to look to see do you 23



### have an understanding around that. So simply, you don't 24



### have the mode of action and the animal model, as Dr. Meek 25



### pointed out, start to look in the middle literature to 26



### see if you can begin to look at plausibility and lay some 27



### testable hypothesis down. 28



### 3) I also heard that we do have an understanding of 29



### some perturbations occurring that could lead to some 30



### outcomes. And as you look at that understanding, you 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### should look in the epidemiology to see how well the 1



### population of interest has been characterized. 2



### So again, that helps you as you integrate, be able to 3



### begin characterizing strength, limitations and 4



### uncertainties. 5

6



### I don't know if I've pulled together everything that 7



### you've said, but what's useful is the things that we 8



### should be thinking of, where we should be focusing as we 9



### bring these different lines of evidence together

. 10



### B ecause we are going to have to do that at some point 11



### before more research or more epidemiology is done. With 12



### a ny pesticide, we continue to look at it because we have 13



### reevaluation schedules. Thank you. 14

15



### DR. DANIEL SCHLENK : Thanks. I think what we're going to do 16



### -- Dr. Portier is taking furious notes here

-- I think 17



### what we'll do is maybe put this on the end of Question 18



### 11. If you can do that, Dr. Gold, that would be great. 19



### So we'll tack it on to Question 11. 20

21



### We have some travel issues that the panel needs to deal 22



### with, so think what we're going to do is take an early 23



### lunch and if the panel would meet in the c offee room, we 24



### need to very rapidly decide a few things because 12:00 is 25



### check out time. So we need to make a decision very 26



### quickly. So we're going to take an hour and a half 27



### lunch. We'll be back at 1:00 and finish the last two 28



### questions. 29

30

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### DR. DANIEL S CHLENK : Good afternoon, everyone. Let's go ahead 1



### and get started on Question 13. Dr. Mendez, are you 2



### going to read that? 3

4



### DR. ELIZABETH MENDEZ : Good afternoon. Charge Question Number 5



### 13 has to do with the temporal relationships between 6



### exposure and to x endpoint. 7

8



### Question A: "Please comment on the rationale used by the 9



### Agency for selecting these exposure duration options" 10



### that I mentioned in the preamble of the question. 11



### "Please discuss the rationale for other alternative 12



### durations of concern, if an y." 13

14



### Question B: "Please comment on which exposure duration 15



### in humans most closely corresponds to the exposure 16



### duration found to cause adverse effects in rats." 17

18



### Question C: "Please comment on the approach used by the 19



### Agency, i.e. the one compartment line ar model to relate 20



### atrazine levels from the water chemographs to predict 21



### corresponding human plasma triazine levels for the 22



### proposed durations of concern. In particular, please 23



### comment on the Agency's propose d approach to use water 24



### AUC estimates to calcul ate a time

- weighted daily average 25



### of atrazine exposure for a given duration of concern. 26



### Please suggest alternative approaches as appropriate." 27

28



### DR. DANIEL SCHLENK : Our lead discussant on this question is 29



### Dr. Bill Hayton. 30

31

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### DR. WILLIAM HAYTON : Our group did meet to discuss this and 1



### tried to come to some meeting of our minds on the 2



### response. So I'll read my response, and if the other 3



### members want to add to that, that is what we'll do. 4

5



### So my response to Part A is a time to reach steady state 6



### and time t o effect are not necessarily closely related. 7



### It could simply be a coincidence that they both take 8



### about the same amount of time . The time to accumulate 9



### radioactivity to steady state and the route with the oral 10



### gavage dosing takes about four days, and it also takes 11



### four days of exposure before you start to see LH surge 12



### suppression. 13

14



### So we didn‟t really see any evidence for a cause

- effect 15



### relationship there at all. It seemed like if one looked 16



### at the CODAR , 2011 study

-- I better get back to my text 17



### or I'm going to get all balled up here . W here he 18



### measured atrazine and then the three DEA, DIA, and DACT 19



### metabolites , t he exposure produced by the pseudo steady 20



### state level for those for compounds, in four days
, was 21



### about the same as produced during the firs t day. In 22



### other words, the accumulation in the steady state for 23



### those substances seem to happen fairly quickly. 24

25



### The CODAR study of four daily doses of atrazine by oral 26



### gavage, followed by a four

- day washout period with plasma 27



### concentrations measured in tensively during both the 28



### treatment and washout perio ds, showed very similar Cmax, 29



### Cmin and AUC for treatment days two through four
, for 30



### atrazine and the toxicologically active metabolic. 31



### Again, DEA, DIA, and DACT. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### Treatment Day 1 exposures were only sli ghtly smaller than 2



### those observed for Days 2

- 4. So in other words, there 3



### was little accumulation of the chloro

- s

- triazines with 4



### daily multiple dosing regimen, which is very consistent 5



### with the relatively short half

- lives of the triazines, 6



### compared with th e 24

- hour dosing interval. 7

8



### The one dose I looked at fairly intensively was the 50 9



### milligram per kilogram per day oral gavage treatment. 10



### The longest half

- life of the four triazines was that for 11



### DACT, which was about seven hours. It should be noted it 12



### w as a much longer half

- life, starting around 36 hours 13



### after the fourth dose, and that half

- life was about 17 14



### hours. But that half

- life controls just an insignificant 15



### fraction of the overall accumulation of the systemic 16



### exposure to DACT. 17

18



### So the seven

- hou r half

- life and 24

- hour dosing interval 19



### indicate that accumulation would be negligible, and 20



### therefore, that exposure after the first dose is pretty 21



### much the same as you would see at steady state on Day 4. 22

23



### So since the accumulation of nacreous triazines is 24



### negligible when atrazine is dosed daily by oral gavage, 25



### the time to e ffect is apparently not controlled by the 26



### time required for the systemic concentrations to reach a 27



### minimum critical level associated with the onset of 28



### effect, as the triazine exposure, after the first daily 29



### dose, is similar to that after the fourth dose. 30

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### So the logic here is we're not looking at a 1



### pharmacokinetically

- controlled accumulation to some 2



### threshold level because you must hit that threshold level 3



### right after the first dose, so it doesn't take four days 4



### of dosing to get there. 5

6



### So we concluded that it is therefore more probable that 7



### the time to onset of effect is controlled by the 8



### pharmacodynamics; in other words, the kinetics of events 9



### downstream from the chemical initiati ng event are in 10



### control of the onset of effect. And the kinetics of 11



### downstream adverse outcome pathway events for LH 12



### attenuation in human versus rat are not well 13



### characterized and it is therefore, not apparent w hat the 14



### appropriate duration of human exposu re is to use in 15



### conjunction with setting maximum level of exposure to 16



### prevent LH attenuation in humans . W ithout the relative 17



### rat versus human effect kinetics, the conservative 18



### approach would appear to be to use the four

- day duration 19



### identified in the stud ies with rats. 20

21



### And so that's based on the individual chloro

- s

- triazines. 22



### For total radioactivity, plasma concentration, the 23



### elimination half

- life is longer and the expected 24



### accumulation profile has a considerably longer time to 25



### steady state. In this cas e, the daily exposure would 26



### increase day

- by

- day, with three to four days of exposure, 27



### required to achieve 90 percent of the steady state plasma 28



### concentration. 29

30



### An accumulation to a threshold concentration could define 31



### the time to onset of the LH surge su ppression. As long 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### as the long half

- life of total radioactivity lik ely 1



### reflects the half

- life of albumin adducts, which are not 2



### active in LH surge suppression , t his explanation of the 3



### four

- day exposure being defined by the time to reach 4



### steady state is un likely. 5

6



### DR. DANIEL SCHLENK : Thank you. Dr. Chambers? 7

8



### DR. JANICE CHAMBERS : I was actually not part of that earlier 9



### discussion group. I don‟t know what that means, but the 10



### only thought that I had that I think is worth reiterating 11



### is something you men tioned also, that it‟s probably just 12



### a coincidence that the four

- day and the 28

- day 13



### extrapolation are just a coincidence, nothing to do with 14



### a common mechanism and an amount leading to an effect. 15

16



### DR. DANIEL SCHLENK : Okay. Dr. Greenwood? 17

18



### DR. RICHARD GR EENWOOD : I think I've already said pretty much 19



### what I needed to say earlier. I think I just, again, I 20



### support what Dr. Chambers' said . I t's just really very 21



### difficult in the absence of any scientific knowledge to 22



### be able to extrapolate to human exposure that's 23



### equivalent to this exposure that's necessary to suppress 24



### the LH surge in rats. 25

26



### DR. DANIEL SCHLENK : Okay. Dr. Fenner

- Crisp? 27

28



### DR. PENELOPE FENNER

- CRISP : I don‟t have anything to add. I 29



### had my input yesterday. 30

31



### DR. DANIEL SCHLENK : Okay. Dr. Me ek? 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. BETTE MEEK : I don‟t have very much to add. I think it's 2



### important to recognize that if you use the four

- day kind 3



### of period, that‟s really a science policy choice to be 4



### conservative because essentially what we were saying is 5



### that there's this rea lly limited information on which to 6



### base that period. 7

8



### Just one other point I'd like to make is the allometric 9



### scaling that was done for the 21 to 3 0 days in humans, 10



### you normally wouldn't use allometric scaling where you're 11



### expecting the effect to be med iated by metabolites. So 12



### it's probably something to think about. 13

14



### DR. DANIEL SCHLENK : Other panel members? No? Okay. Let‟s 15



### move onto B. Dr. Hayton? 16

17



### DR. WILLIAM HAYTON : For this question we did consult, Dr. 18



### Greenwood and I, briefly with Dr. Rodrigu ez about what 19



### they were really looking for there . We had difficulty 20



### really responding to their question because the molecular 21



### initiating event and the adverse outcome pathway are not 22



### well enough understood at this point, we felt, to fully 23



### address this que stion. It seems possible that the 24



### kinetics of events downstream from the chemical 25



### initiating event control the time to onset of LH 26



### attenuation. 27

28



### Another factor to consider is the minimum duration of LH 29



### attenuation that must occur before adverse toxicolo gical 30



### effects ensue. Is a brief transient suppression for LH 31



### to be avoided or suppression of longer duration ? H ow 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### large a suppression of the LH surge must be avoided ? And 1



### we felt there just isn‟t the quantitative information 2



### available to answer those qu estions. So without answers, 3



### you know, I guess this would be science policy kind of 4



### consideration, but a conservative approach would be to 5



### avoid even a brief transient suppression of LH, but 6



### really no evidence to conclude that. 7

8



### DR. DANIEL SCHLENK : Dr. C hambers? 9

10



### DR. JANICE CHAMBERS : The only thing I wanted to add here is a 11



### couple of things that have already been said; 1) is I 12



### don't think that it is really understood whether a steady 13



### state concentration is what's causing the effect or 14



### whether it's a high

- dose pulse. S o it's hard to 15



### interpret this question in not knowing that. 16

17



### And the other thing that I think that is worth 18



### reiterating is that it's been mentioned several times 19



### that the suppression in the LH surge may not really be a 20



### truly adverse effect a t this point. So we don‟t know. 21

22



### DR. DANIEL SCHLENK : Dr. Greenwood. 23

24



### DR. RICHARD GREENWOOD : I don‟t think I have anything to add. 25

26



### DR. DANIEL SCHLENK : Dr. Fenner

- Crisp? 27

28



### DR. PENELOPE FENNER

- CRISP : I'd probably ask a different 29



### question here. I'd prob ably ask a question about what 30



### exposure duration in humans not most clearly corresponds 31



### to the exposure duration found to cause adverse effects 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### in rats, but rather, what exposure duration in humans 1



### would be needed to induce

, in effect, representative or a 2



### correlate to those observed in the rat studies. 3

4



### We've talked about the menstrual cycle correlations in 5



### terms of time. We haven‟t talked about expected 6



### durations of exposure for any of the plethora of other 7



### adverse effects seen in the animal studies th at may well 8



### have human correlates like the delaying in puberty and 9



### all those kinds of things. I think that would be the 10



### appropriate question to ask. I t may well be something 11



### other than either the 4 or the 14 of the 28, depending 12



### upon which adverse correl ate you're talking about. 13

14



### DR. DANIEL SCHLENK : Okay. Dr. Meek? 15

16



### DR. BETTE MEEK : I think I would echo . I would certainly 17



### like to see the discussion broaden to consider other than 18



### simply the effect on LH attenuation. So again, it would 19



### be drawing on m ore of the data to consider what the 20



### appropriate kind of timeframe might be. 21

22



### DR. DANIEL SCHLENK : Other panel members? Dr. O'Byrne? 23

24



### DR. KEVIN O'BYRNE : I suppose the frustration here is the 25



### huge difference between primates, whether it's r hesus 26



### monkeys or humans and the rat model. The whole panel is 27



### mindful of this because it was discussed apparently in 28



### September when Tony Plant was here and gave a lengthy 29



### presentation. He touched on this just the other day on 30



### certain salient aspects of the difference . And that's 31



### just the surge generating mechanism. The different time 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### scale, you know, days rather than hours of the surge

- 1



### the estrogen dependence. 2

3



### I mean, you got to have 30, 36 hours of continuous 4



### estrogen stimulation to get a surge in a monkey or a 5



### woman, or a man if you remove his testicles. But in 6



### terms of moving to puberty, I mean, the time scales are 7



### even greater between primates and rats. So that‟s an 8



### even greater mind field, as far as I can see. 9

10



### DR. DANIEL SCHLENK : Dr. Roby? 11

12



### DR. KATHERI NE ROBY : I think the other complicating factor is 13



### if you're talking about a one

- time event where you were 14



### causing a one

- time transient inhibition of LH, and if 15



### we're talking about onset of puberty . A one

- time event 16



### really is not going to have a significa nt effect on the 17



### onset of puberty. If you're talking about eliminating LH 18



### for an extended amount of time, then you'll have a 19



### negative effect downstream. But again, the one

- time very 20



### transient inhibition in itself is going to have minimal 21



### effect, even on something like the onset of puberty. 22

23



### DR. PENELOPE FENNER

- CRISP : My comment is, in the four

- day 24



### window of exposure would be of no use in answering that 25



### question. 26

27



### DR. KATHERINE ROBY : Correct. 28

29



### DR. DANIEL SCHLENK : Any other comments from the panel on B? 30



### Okay. Let's move on to Letter C. Dr. Hayton? 31

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### DR. WILLIAM HAYTON : Yeah. Just to briefly review, I guess 1



### it‟s on the screen, isn't it? That they're asking for 2



### comment

-- the Agency is asking for comment on using 3



### water ; t he area under the curve estimat es that calculate d 4



### time

- weighted daily average of atrazine exposure for a 5



### given duration of concern. 6

7



### And the response is that the approach is theoretically 8



### sound. The integral of the water chemograph, divided by 9



### the time span of the chemograph provide s an estimate of 10



### the time

- weighted average concentration of triazines in 11



### the water during the time span . A nd multiplication of 12



### the average concentration by the daily water ingestion 13



### rate quantifies the daily triazines dose. And the daily 14



### dose divided by the human triazine clearance, which is 15



### estimated allometrically, provides an estimate of the 16



### steady state average plasma concentration of 17



### radioactivity. And when that is multiplied by 24 hours, 18



### then the AUC for the human over a 24

- hour period is 19



### obtained

. I think we all agreed that if you make the 20



### assumption that it's behaving as a one compartment system 21



### that will work. 22

23



### And then I had one little additional piece he re . The use 24



### of water AUC to calculate a time

- weighted daily average 25



### is theoretically sou nd. An alternative to the water AUC 26



### is simply to average the measured water concentrations, 27



### but this would be inferior. You wouldn't get a time

28



### weighted average; it would just give you a simple 29



### arithmetic average. So we didn‟t see a better way 30



### forward t here. 31

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### DR. DANIEL SCHLENK : Okay. Dr. Chambers? 1

2



### DR. JANICE CHAMBERS : Nothing to add. 3

4



### DR. DANIEL SCHLENK : Dr. Greenwood? 5

6



### DR. RICHARD GREENWOOD : I think that the approach is sound. I 7



### agree with that, in terms of theoretically sound. I 8



### think it just is neces sary to check some of the 9



### underlying assumptions about that pharmacokinetic curve. 10

11



### DR. DANIEL SCHLENK : Dr. Fenner

- Crisp? 12

13



### DR. PENELOPE FENNER

- CRISP : I don‟t have anything to add. 14

15



### DR. DANIEL SCHLENK : And Dr. Meek? 16

17



### DR. BETTE MEEK : Nothing to add. 18

19



### DR. DANIEL SCHLENK : Other panel members? Okay. That 20



### completes 13. Let me go back to the EPA and ask if they 21



### have any questions or clarification. 22

23



### DR. ELIZABETH MENDEZ: I'm just looking at the team, and I 24



### don‟t see anybody that is jumping out wit h a question. 25



### So I guess we could move onto Question 14. 26

27



### DR. DANIEL SCHLENK : Okay. Sounds good. Hold on. Dr. 28



### Portier has a question. 29

30



### DR. KENNETH PORTIER : And it‟s to Dr. Roby. You know, I was 31



### listening to what you were saying and I thought to mys elf 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### well, under a scenario, suppose that just slightly above 1



### background atrazine were enough to completely suppress LH 2



### in the human female . I n a typical year it would be maybe 3



### three months , right? So what do you think the impact 4



### would be if three months out of every year you had that 5



### suppressed? And I was sitting there thinking, I don‟t 6



### know if we know the answer to that, although women take 7



### birth control pills. I guess if you're really forgetful, 8



### you could be doing it three times out of a year, but do 9



### you have any

-- I'm think ing worst

- case scenario here. 10



### I'm just trying to think

-- 11

12



### DR. KATHERINE ROBY : Let's put that scenario in a mature 13



### reproductive woman . I n that case, probably little 14



### because we have the example of oral contraceptives that 15



### are doi ng the same thing. And now there are oral 16



### contraceptives that basically inhibit the cycle for 17



### months at a time, in a row. So the effect, again, 18



### probably very little because we know that those oral 19



### contraceptives are safe, and when you stop using them, 20



### yo u reinitiate your cyclicity, which is the important 21



### endpoint. 22

23



### Now, if that were to happen at maybe a different life 24



### stage, maybe the impact could be a little bit more, but 25



### if we take the mature situation where we assume the 26



### cyclicity in the brain, it‟s reinitiated when you stop 27



### the inhibitory effect. It would, again, just push 28



### puberty a little bit further and it might hasten 29



### senescence or menopause, or the transition through 30



### menopause. So whether those are significant adverse 31



### events, I guess remains to be decided. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. KENNETH PORTIER : This is Dr. Portier. I think that 2



### thinking would be good for Section B if you kind of added 3



### that in because you guys were focusing on the very short

4



### term exposure and I was sitting there saying well, but 5



### the worst

- case scenario is we use it during the season 6



### and it really impacts the woman. And what I'm hearing 7



### you say is well, even if it did that, you know, our 8



### current knowledge might seem to indicate, at least in a 9



### normal adult woman, if it were operating like an ora l 10



### contraceptive, the long

- term impacts could be mild. 11

12



### Now, what we don‟t know is whether atrazine maybe is 13



### different than direct estrogen and progesterone in the 14



### sense of what it does to the brain and whether it short

15



### circuit something else , a nd I think I got that 16



### implication. 17

18



### DR. DANIEL SCHLENK : Just to clarify, what question do you 19



### think that should be added to? 20

21



### DR. DANIEL SCHLENK : Oh, B

-- on 13(b) 22

23



### DR. KENNETH PORTIER : B, t alking about exposure duration in 24



### humans. 25

26



### DR. DANIEL SCHLENK : Oh, o kay. Dr. O'Byrne? 27

28



### DR. KEVIN O'BYRNE : I think there's a slight difference 29



### because when you're on oral contraceptive pill, then 30



### you're not hypoestrogenic. It's quite possible that if 31



### atrazine is switching off your pulse generator and that 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### may be common, maybe similar to functional hypothalamic 1



### amenorrhea, where you would be hypoestrogenic. So there 2



### you c ould end up with potential for osteoporosis, et 3



### cetera, et cetera. 4

5



### But I'm just mindful of all the seasonal animals that 6



### switch off for weeks or mont hs or even half

- a

- year, and 7



### there's no adverse effect there. I mean, they just come 8



### back and breed and switch off again, year in/year out. I 9



### still feel that even a brief loss of reproductive 10



### function would not have any great impact. 11

12



### DR. DANIEL SCHLENK : Okay. Any other comment? Dr. Horseman? 13

14



### DR. NELSON HORSEMAN : I think I'd like to speak for the males 15



### in the Midwest. Well, th is discussion about integrating 16



### this into the female reproductive cycle and we haven‟t 17



### talked at all about suppressing LH puls e generation in 18



### males, which I don‟t mind too much seasonal suppression 19



### of reproductive function in ground squirrels. I don't 20



### think in men that would be such a great thing. There has 21



### been no consideration of how you might view this LH surge 22



### suppression i n males. 23

24



### DR. DANIEL SCHLENK : Okay. Dr. Roby first. 25

26



### DR. KATHERINE ROBY : So I guess my comments are assuming that 27



### the only effect is at the level of the ovulatory surge, I 28



### think that if there's a level of effect at the pulse 29



### throughout the rest of the c ycle, then it's a different 30



### story. Absolutely. 31

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### DR. DANIEL SCHLENK : And Dr. O'Byrne? 1

2



### DR. KEVIN O'BYRNE : I can see a male contraceptive coming on 3



### line here, but I think the thing to appreciate here is 4



### that a reduction of post generator frequency in the 5



### female is serious business because the whole menstrual 6



### cycle is exquisitely sensitive to changes in post 7



### generator frequency. Us men, our pulse generator can be 8



### knocked down quite considerably, and we still produce 9



### testosterone to pro tect our bones and m aintain our 10



### libido, et cetera, et cetera, and our spermatogenesis. 11



### So we're much more robust than women, in that respect. 12

13



### DR. DANIEL SCHLENK : Nice addition there. Way to pull the 14



### foot out of the mouth on that one. Very good. Very, 15



### very diplomatic the re. Any other comments, with that? 16



### Okay. Let's go ahead then and read in Question 14. 17

18



### DR. ELIZABETH MENDEZ : Question 14 relates to the case study 19



### that was at the end of the Issue Paper and the Agency's 20



### use of the 95th and 5th percentile of conditional 21



### simulations of daily concentration. "Please comment on 22



### the use of a 95th percentile of the conditional 23



### simulations for providing an upper bound on rolling 24



### average concentrations in the case study." 25

26



### DR. DANIEL SCHLENK : Our lead discussion for that is Dr

. 27



### Portier. 28

29



### DR. KENNETH PORTIER : Thank you. This is Ken Portier. While 30



### they're bringing up my slides, I just have some slides 31



### for illustration. I want to read this into the record. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### EPA asked this panel to discuss its epidemiology and PK 2



### findings in l ight of the framework discussed before the 3



### SAP in February 2010, the consultation with the panel. I 4



### want to say for the record that as I write up this 5



### discussion that we had right before lunch, I'll be 6



### including in this report a copy of Figure 1 from the 7



### February 2010 SAP report, and that Figure 1 is of the 8



### framework diagram. So I can refer back to it and kind of 9



### put the discussion in context. 10

11



### In addition, it's very likely that a second figure may be 12



### included in the report to allow better illustration of 13



### the issues and discussion on this topic. And the second 14



### figure is likely to be a slight enhancement or 15



### modification to the framework diagram. Of course, I 16



### don't have it at this point. So I can‟t show it to you, 17



### for the record. So just watch my hands , and we're going 18



### to do this. But I just wanted it for the record. 19

20



### T he panel likes to make sure that nothing shows up in our 21



### report that we haven't talked about in the room. And so 22



### I wanted to make sure that you were warned that when you 23



### see these dia grams, you're not surprised because I was 24



### trying to figure out how to write up the discussion 25



### without the diagram. I don‟t think that I could do it. 26

27



### A lot of what we're going to be talking about here really 28



### follows on Questions 1 through 4. If we don‟ t get what 29



### we talked about in one to four correct, we're not going 30



### to be able to do this correctly as well. 31

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### So the AUC water value is a time series that's computed 1



### from an input water concentration time series by 2



### successfully integrating, numerically, u sing this 3



### trapezoi n method, over the period of concern, say four 4



### days, and then it uses this as input into computing the 5



### AUC plasma value. 6

7



### The time step for the underl ying concentration time 8



### series is daily, and the resulting time step for the AUC 9



### time series is also daily. The goal is the estimation of 10



### human average daily concentration of atrazine over the 11



### period of concern. For the four

- day duration of concern, 12



### concentrations from four sequential days

-- in this case , 13



### using five actual time points

-- are input into the 14



### trapezoid method to produce an average AUC value. 15

16



### For the 14

- day duration concern, we used 15 data points. 17



### And for the 28, we're going to use 29 data points. An 18



### example of this, you can see Figure 21 in the white 19



### p aper. Again, thi s is just trying to make sure everybody 20



### understands what's going on here because the write

- up in 21



### the white paper was pretty tight. It wasn't a lot of 22



### illustration there. 23

24



### The first period of concern, for example, uses 25



### concentrations from Days 1 to 5, an d the second period 26



### using Days 2 to 6. So it's really a rolling average kind 27



### of thing that's going on. So we have a total of T days 28



### of data. We're going to have T

- minus four data point s in 29



### the subsequent AUC time series. 30

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### So consider first the daily sampling concentration time 1



### series. In Figure 29(a), it shows the actual daily time 2



### series curve in a simulated 95th percentile curve and a 3



### simulated 5

- percentile curve . P assing the actual daily 4



### sampling time series through the numerical integration 5



### func tion produces the actual AUC water ti mes

. 6

7



### So what I've done here is I tried to recreate what EPA 8



### did in that Figure 29(a), but I don‟t have all the 9



### kriging tools and everything else. So what I did is I 10



### took the data from the 1995 Maui River data and I kind of 11



### smoothed it out to produce a daily time series. I 12



### apologize for those of you way in the back, but right in 13



### the middle of all that green is a solid black line and 14



### that represents the actual smoothed time series for a 15



### concentration. And the green a round that is the 1,000 16



### simulated time series with uncertainty or noise. 17

18



### J ust as we did with the g eospatial model where you added 19



### some variability for those points between the sample 20



### points, you get kind of noise. You get 1,000 21



### realizations of what thi s time series might have really 22



### been. And the black line becomes the average. And what 23



### EPA did

-- and again, I apologize for those of you in the 24



### back

-- I've just drawn a dotted line across the top of 25



### all those greens and a dotted line along the bottom o f 26



### the greens that represents the 95th

-- or the maximum, if 27



### you like

-- upper bound and the minimum lower bound. I 28



### could've done it on the 95th percentile. I just wasn't 29



### thinking at 11:30 last night as I was doing it. But that 30



### top curve represents

-- yo u can think of the top curve as 31FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### representing the 95th percentile of all those simulations 1



### and the bottom one representing the bottom percentile. 2

3



### So you have these kind of three curves. You have the top 4



### curve, the 95 max, and the bottom curve, the 95 min in 5



### the black line, and then this is past

-- so here are 6



### these curves and we pass the concentration curve through 7



### this trapezoidal integrator, which computes and average, 8



### and you end up with these three time series. Kind of one 9



### in the middle which represe nts the mean or the median; a 10



### 95th percentile upper and a 95th percentile lower. So 11



### all I did was take that dotted line from the previous 12



### graph, pass it though the AUC formula and here's what I 13



### get back again. This is actually AUC times 24 hours. I 14



### didn ‟t divide it by 24; it just would change the scale. 15

16



### If I did that same AUC process and did it for every one 17



### of the thousand simulations, I get something that looks 18



### like this. And the point I was trying to make is that 19



### you can't take the percentile functi on from the 20



### concentration and just kind of directly pass it through 21



### the integrator. You have to integrate every one of the 22



### realizations and then compute the upper 95th percentile 23



### and the lower 95th percentile because that would be the 24



### top of the green lin e. The top of the green area is a 25



### better estimate of that. 26

27



### S o you can see what EPA did. My understanding from 28



### reading the document and then talking personally with 29



### Nelson, what they did was take the formula and pass it 30



### through and I think that produce s a very conservative 31



### upper concentration AUC estimate. And a better way to do 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### it would be to pass your simulations through and then 1



### compute your statistics on the simulated numbers. I 2



### think that's the whole point of what I wanted to make in 3



### my comments, and these graphs will all be in the 4



### document. 5

6



### So what I was saying is that the way EPA did it is not 7



### the way a statistician would have done it. We would have 8



### gone back to the original, individual simulations, run 9



### those through the AUC average and then c ompute the 10



### percentiles and use those as our estimates of upper and 11



### lower bounds. And I think they'd be more realistic, 12



### assuming everything that we discussed in Questions 1 13



### through 4, we get the model fitting right. We get the 14



### infill correct and all this other stuff. 15

16



### I want to make two other points that kind of came to me 17



### last night. So part of the discussion we have is where 18



### we're doing just averaging. You're saying well, what if 19



### I have the daily time series? What if I average and look 20



### at four

- day a verages or seven

- day averages or 14

- day 21



### averages or 28

- day averages? Again, these don't show up 22



### really well in the back, but the point we were trying to 23



### make the other day is that as you average the variability 24



### and the process gets decreased , and that as you actually 25



### expand the average amount, you could lose some of the 26



### patterning . T he point I was making, you lose some of the 27



### duration of exposure information, so that you can see for 28



### four and seven

- day averaging it's not bad, but once you 29



### get to say, 28

- da y averaging, you've lost two of the 30



### major peaks. They've been averaged into one peak. And 31



### that one peak is much broader than the individual two 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### peaks that we average then. And so you get the wrong 1



### picture. So you don‟t see a lot of interest on our part 2



### when you're dealing with kind of an average time series. 3



### We'd rather you deal with the daily time series and 4



### infill. 5

6



### And then the second point is that when simple averaging

- 7



### - all I did here was take four days and averaged. You 8



### know, make a window of four days, and get an average. 9



### Move it one, get another average. That‟s what that red 10



### graph is. But for the AUC, when we use that trapezoid 11



### function, we're doing exactly the same thing, it‟s just a 12



### slightly different averaging. So on the previous slid e I 13



### took four points and averaged it. On this slide you're 14



### really taking five points and you're giving half the 15



### weight to the first point and the fifth point, and full 16



### weight to the middle three. It‟s a slightly different 17



### average. It's going to be sligh tly smoother, but I think 18



### if I had taken the red line here and the red line on the 19



### previous graph, they would've been almost identical. 20

21



### So what you're really doing when you're computing the AUC 22



### is very similar to what you're doing when you're 23



### averaging th ese series. I mean, they're the same thing, 24



### except that the AUC is scaled to an hourly value, at 25



### least using your equation. So to me, the bottom line 26



### here is I wouldn't want to be computing AUCs on five or 27



### four

- day averages because I basically would be a veraging 28



### averages. And you‟re going to end up with the equivalent 29



### of a 16

- day average instead of what you think you're 30



### doing is four

- day averaging. It's kind of hard to see 31



### that. I think that was the statistical way of looking at 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### this issue of the 95th percentile and providing an upper 1



### bound on rolling average concentration. So with that, 2



### I'll rest to the panel. 3

4



### DR. DANIEL SCHLENK : Thanks, Dr. Portier. Dr. Fenner

- Crisp is 5



### our first associate on that. 6

7



### DR. PENELOPE FENNER

- CRISP : I couldn't possibly a dd anything 8



### to that. 9

10



### DR. DANIEL SCHLENK : Dr. Greenwood. 11

12



### DR. RICHARD GREENWOOD : Me too. 13

14



### DR. DANIEL SCHLENK : Ditto, I guess, huh? Dr. Griffith. 15

16



### DR. DANIEL GRIFFITH : Sorry. I have something to add. 17

18



### DR. DANIEL SCHLENK : I know. Fabulous. 19

20



### DR. DAN IEL GRIFFITH : I agree. It reflects back on some of 21



### the discussion from Questions 1 through 4. And again, 22



### I'll read this. I made a comment yesterday, which I 23



### think links to Questions 1 through 4 as well about 24



### sources of error and some of that will come out in here. 25



### I do have one table which I will describe. 26

27



### Identified sources of error noted in the reports include 28



### sample size, to which sampling error links, spatial and 29



### temporal proximity of samples which alludes to coverage 30



### and hence, quality of sampl es . B ut I note that spatial 31



### proximity does not appear to be used

, and the nature of a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### given phenomenon

, in other words, its inherent 1



### variability. Model misspecification should be added to 2



### this list, as should measurement error. This latter 3



### source of err or could be linked to the substitution of 4



### kriged or deterministic model

- generated imputations into 5



### a daily time series, as well as the handling of below 6



### detection limit values. 7

8



### Although it furnishes a tool to ascertain uncertainty and 9



### risk, conditional simulation, which utilizes Monte Carlo 10



### techniques, does not embrace all of these sources of 11



### error. One weakness is that conditional simulation is 12



### sensitive to the data upon which conditioning is made. A 13



### simulation replicates its conditioning values on av erage. 14



### Frequently, the normal or log

- normal distribution is the 15



### probability model of choice that is attached to the 16



### conditioning values. In other words, the conditioning 17



### values may be t he means of a collection of normal 18



### distributions, one for each day in a time series. 19

20



### For the specimen atrazine data, a log

- normal distribution 21



### assumption fails to adequately track the serial 22



### correlation in the data and furnish es a poorer 23



### statistical description from the monitoring data than 24



### selected alternatives statisti cal distributions. 25

26



### When considering a 90 percent confidence interval, which 27



### is what the 5th to 95th percentiles are referring to, a 28



### balance should be maintained between claiming an 29



### excessive atrazine concentration when one does not exist, 30



### and failing to detect an excessive atrazine concentration 31



### when one does exist. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### The latter is the riskier of these two situations. For 2



### the purpose of atrazine impact analysis, this confidence 3



### interval focuses attention on the 95th percentile for 4



### conditional simulation. Because rolling average 5



### concentration are means, by definition they result from 6



### smoothing data so that peaks disappear. Consequently, 7



### actual peak concentrations are underestimated. These 8



### averages are easier to predict, specifically because they 9



### are mea ns. 10

11



### Figures 27 and 29 illustrate that 14 and 28

- day rolling 12



### averages may be of little value for decision

- making and 13



### monitoring purposes, even though they have relatively 14



### tight confidence intervals. Although four

- day rolling 15



### averages are better, the cru cial peak missed by them is a 16



### substantial peak. This point may be of less importance 17



### if the rolling averages represent duration of exposure. 18

19



### The situation may well improve what the change in the 20



### variogram model as well as the change in the probability 21



### m odel employed for the stochastic simulation. A 22



### variogram model that better captures autocorrelation 23



### effects will better differentiate between the conditional 24



### and stochastic components. A probability model that 25



### allows more variability has potential to bet ter capture 26



### the peaks. And those go back to some of the comments I 27



### made earlier. 28

29



### A standard conditional simulation fails to capture all 30



### sources of variation. It assumes that the conditioning, 31



### the kriged values, are fixed and true. We saw a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### reference to this before. What happens then is that the 1



### confidence band shrink to

-- and in the classical case

-- 2



### they shrink to zero at the observe data as though those 3



### data values are true values. And then simulate sampling 4



### error about these values. It fails to i ncorporate 5



### parameter estimation error. The log

- transformed atrazine 6



### example time series data reveals the following additional 7



### sources of error, a nd this is the table. 8

9



### So we see the spherical models being used quite 10



### extensively in the paper, and the sph erical model has a 11



### relatively poor fit compared to other models. It's 12



### weighted some of the squared error, is 28, whereas, for 13



### the Gaussian, it's 13 and the Bessel function is 12.9. 14



### It gives a good nugget estimate because it can't estimate 15



### the nugget effe ct, s o it defaults to zero. The Gaussian 16



### gives a slightly higher nugget effect . The Bessel 17



### function gives something very close to zero, but it's not 18



### statistically significant from zero. And the advantage 19



### of those two

-- which is why they probably captur e the 20



### pattern better

-- is that the Gaussian and the Bessel 21



### have a cusp near the origin, and that cusp means that 22



### your autocorrelations structure actually goes out a bit 23



### stronger than what the spherical is capturing. 24

25



### The scale parameters between the sphe rical and the Bessel 26



### are about identical. The Gaussian is slightly lower. 27



### And then when you look at range, well the spherical has a 28



### rang, by construction, the Gaussian and Bessel are 29



### asymptotic functions, so you can only get an effective 30



### range. The sphe rical suggests that there is a range of 31



### about 22 days. The Gaussian about 14 days, which is a 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### substantial difference, and then the Bessel actually 1



### suggests something more like 37 days. And if you look at 2



### the time series, just like the ones we saw, 37 act ually 3



### seems more reasonable. 4

5



### The conditional simulation fails to incorporate 6



### measurement error. The substitution of selected 7



### quantifies for below detection limit values, should have 8



### minimal impact upon these results. I saw in the reports 9



### where .05 were used in some cases, in the Synge n ta six 10



### supplemental water system monitoring data, it looked to 11



### me like they used .03. I don‟t think that that's going 12



### to make much difference. 13

14



### The variability in an assay to detect and quantify 15



### atrazine in water sample s

-- and my understanding from 16



### what I've reads on EPA websites is that the RaPID Assay 17



### Kit, analytical precision standards

, apply and they're 18



### plus or minus 30 percent. So all of these measures can 19



### be off by as much as 30 percent above or below the 20



### reporte d values, which is substantial. And none of that 21



### measur ement error is actually being captured in what has 22



### been done. 23

24



### The cumulative effect of these errors, at least some of 25



### them may compound, which propagate through an analysis, 26



### may well invalidate the c laim of a 95th percentile. 27



### Without tracing the cumulative effects of these different 28



### sources of error , perhaps a more representative approach 29



### would be to use a 97.5 percentile; in other words, switch 30



### to a 95 percent confidence interval to try and adjust f or 31



### these , but as I said before, I think it would be much 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### better to see what is compounding, in terms of the error 1



### and how it's propagating through the system. 2

3



### DR. DANIEL SCHLENK : Thank you, Dr. Griffith. Dr. Hayton? 4

5



### DR. WILLIAM HAYTON : I can‟t add to that. 6

7



### DR. DANIEL SCHLENK : Dr. Meek? 8

9



### DR. BETTE MEEK : I have nothing to add. 10

11



### DR. DANIEL SCHLENK : Okay. General panel comments? Yes, Dr. 12



### Gilliom? 13

14



### DR. ROBERT GILLIOM : I guess I just want to add the 15



### perspective that I think all the statistical issues with 16



### the exposure estimates are manageable. And the exposure 17



### part of the equation is maybe two or three orders of 18



### magnitude easier to come to resolution on than the 19



### duration of exposure in organism that's of concern. 20

21



### It's kind of perspective on the answer rather than adding 22



### to the statistics, but I think all the exposure 23



### statistical issues

-- and there were a lot of great 24



### comments made to consider and work in

-- but it's 25



### relatively manageable. 26

27



### DR. DANIEL SCHLENK : Anyone else? Okay. Dr. Mendez, d o you 28



### have any questions o f clarification? Or Mr. Thurman? 29

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### DR. NELSON THURMAN: I just want to say I agree with Bob 1



### Gilliom that as I was listening to this, I was thinking 2



### those are things that we can account for , w e can do it. 3

4



### DR. DANIEL SCHLENK : S ounds promising. Okay. At this point, 5



### what I think we'll do is we'll just go around the table 6



### once. This is your chance to provide your final 7



### comments, anything that you would like to add to the 8



### record. Then we'll go back to the Agency and have some 9



### cl osing comments from them as well. Dr. Hayton, do you 10



### want to start us off? 11

12



### DR. WILLIAM HAYTON : Nothing too profound. I guess the 13



### frustration is after so many years of looking at 14



### atrazine, we still don't really understand its chemical 15



### initiating event a nd all of that toxicodynamics. And if 16



### we knew that story, I think we would be quite a bit 17



### further down the road to solving a number of the 18



### questions. 19

20



### DR. DANIEL SCHLENK : Dr. Greenwood? 21

22



### DR. RICHARD GREENWOOD : I think we've seen a lot of progress 23



### over the last couple of years on the pharmacokinetic 24



### side. That's for sure. I feel quite confident with the 25



### way that's going forward , that w e're going to have tools 26



### that are going to be able to help us with the internal 27



### exposure, just as we're get ting the ext ernal exposure 28



### better defined. But I just echo what Dr. Hayton said, I 29



### really feel that until we can get hold of this primary 30



### lesion

, at least one of them and maybe more, then we're 31



### still in the dark. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Dr. Meek? 2

3



### DR. BETTE MEEK : Yea h. I'm really encouraged by the progress 4



### on , for example, development of the physiologically based 5



### pharmacokinetic model. I think integration of information 6



### at the moment is a challenge

, again, for the reasons that 7



### others have mentioned

, but perhaps not i nsurmountable, 8



### given how much progress was made on the PBPK side in a 9



### very short period of time. 10

11



### DR. DANIEL SCHLENK : Dr. Fenner

- Crisp? 12

13



### DR. PENELOPE FENNER

- CRISP : I've been mulling over again the 14



### issue of determination of whether or not there is life 15



### st ate differences in sensitivities. And thinking again 16



### about the methodology that was used to determine whether 17



### or not that exists. And it‟s coming out in my mind to be 18



### an apples and oranges kind of thing. 19

20



### On the one hand, one's using an apparently not adverse 21



### effect precursor event to an apical event in the adult, 22



### the four

- day LH surge suppression, comparing it against 23



### NOAEL 's and LOAE L's for apical effects, generated in data 24



### for other life stages than the adult. And I'm wondering 25



### if it might not be ap propriate to also do an analysis 26



### where you select an apical event in an adult that's a 27



### consequence of the LH surge suppression and compare it 28



### with the set of NOAE L's and LOAEL 's that were used in the 29



### first instance ; and then ask the question again, "Do you 30



### see a differential sensitivity" , a nd compare it with the 31



### original analysis. It may well turn out to be you would 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### conclude the same thing. Obviously, in that amount of 1



### time

, I haven't done that analysis, but in might be an 2



### interesting exercise to see if you could, in fact, come 3



### to the same conclusion. 4

5



### DR. DANIEL SCHLENK : Dr. Jerde? 6

7



### DR. TRAVIS JERDE : Yeah, I agree. It‟s great to see progress 8



### on pharmacokinetics because I think what those of us on 9



### the cellular and molecular side need is to be able to 10



### c onduct mechanistic studies on how atrazine and its 11



### metabolites may affect cells, tissues, and organisms as a 12



### whole; using concentrations that are reasonable, in terms 13



### of exposure and ground water exposure to effected 14



### populations. And that's kind of what I think this side 15



### of the field has been waiting for. And I also think 16



### maybe that‟s what epidemiology has been waiting for as 17



### well because they need to

-- it‟s clear that we're not 18



### ready to make a conclusion, definitely yet, particularly 19



### in terms of cancer or non

- cancer effects until we know 20



### what the exposure are and we can effectively study it, 21



### epidemiologically in the human and molecularly in models. 22

23



### DR. DANIEL SCHLENK : Dr. Timms? 24

25



### DR. BARRY TIMMS : Yes. I concur with Dr. Jerde that I think 26



### it‟s importa nt to look at molecular mechanisms of action 27



### and with regard to that, it‟s also going to be important 28



### to determine the actual level of human exposure so we can 29



### be working in a framework of exposure that we can mimic 30



### in model systems. 31

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### DR. DANIEL SCHLENK : Dr. Roby? 1

2



### DR. KATHERINE ROBY : I really just agree with everything 3



### that's just been said down the table, understanding the 4



### mechanism, the actual exposure and the kinetics of the 5



### relevance to those two endpoints. That's all I have. 6



### Thank you. 7

8



### DR. DANIEL SCHLENK : Dr. O'Byrne? 9

10



### DR. KEVIN O'BYRNE : Well, I remain optimistic because the 11



### levels of atrazine that are needed to effect elements of 12



### the reproductive system are just extremely high. And in 13



### addition, my thoughts that the reproductive system has 14



### got such a huge margin of robustness that I have very 15



### little disquiet about atrazine. 16

17



### DR. DANIEL SCHLENK : Dr. Akana? 18

19



### DR. SUSAN AKANA : Much to my amazement, I concur with Dr. 20



### O'Byrne. When I first was invited to the panel s and 21



### started reading the litera ture, every alarm in my head 22



### was going off, in terms of stress and energy imbalance. 23



### And through the long process, I am really persuaded that 24



### the margins of safety

-- or at least the effective doses 25



### that are affecting animals are not a major concern for m y 26



### favorite endocrine axis. 27

28



### DR. DANIEL SCHLENK : I'm glad you're relaxed. Bob Gilliom. 29

30



### DR. ROBERT GILLIOM : I guess one of the main gaps in our 31



### knowledge that‟s frustrating to me

-- and this has come 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### in a few side discussions

-- is that there's so much m ore 1



### we could do with available data to look at the 2



### relationships between the population served by specific 3



### drinking water supplies and what's actually in the 4



### supplies. So I don‟t know enough about whether I'm 5



### calling it right, but to me, it‟s a category o f an 6



### epidemiological study that can now be done fairly 7



### comprehensively and it‟s one of the main missing pieces, 8



### from what I hear, of linking all these theories and 9



### possibilities to increased incidence of adverse outcomes 10



### in people. 11

12



### So the real life experi ment is out there. We haven't 13



### sampled it or analyzed it. I would say we probably have 14



### sampled it, but we haven't organized and analyzed it yet. 15



### So whoever is to do it, I think there's a lot that could 16



### be done by mining the data and evaluating the 17



### relati onships between these patterns of outcomes and the 18



### actual exposure that's happened over the last couple of 19



### decades. So that's my main point. 20

21



### The secondary point, I would add that has just kind of 22



### come up in thinking about the future is that we're using 23



### past records of observations to reconstruct a lot of 24



### assumptions and understandings about future exposure and 25



### how to monitor it and so forth. And I think what we've 26



### seen with other chemicals

-- and atrazine kind of stands 27



### out as an exception

-- is that u sually these things are 28



### going through changes over time that span over several to 29



### a few years and systematic downtrends or uptrends. 30

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### So I think I just want to put in the marker that we have 1



### to be aware that when we design the monitoring 2



### approaches, we h ave to anticipate that the re are likely 3



### going to be long

- term changes and shifts in regionality, 4



### perhaps, that just happen because of changing crop 5



### patterns

- maybe genetically

- modified crop come in and 6



### market forces, things like that , r eplacement compound s. 7



### So that we just have to have that built into the thinking 8



### of how we track future exposure and not assume it's a 9



### steady state. Thank you. 10

11



### DR. DANIEL SCHLENK : Dr. Griffith? 12

13



### DR. DANIEL GRIFFITH : Well, I guess I'd like to echo two 14



### things that were raised yesterday, and one has to do with 15



### when we look at the impact on drinking water, what are 16



### the actual dosages for exposure and will they really have 17



### a consequence when humans are exposed to them? 18

19



### And a second point that was raised that I think needs to 20



### be thought about is sort of void in the analysis so far

, 21



### of the water data , i s the whole notion of repetition . I f 22



### you have repeated exposure, even at small levels, but it 23



### has cumulative damage, then you need to be looking at 24



### long

- time series of water l evels

- atrazine levels in 25



### water, not just one year, and then the confounding factor 26



### that's going to impact on that is people move all the 27



### time and so what happens as people move in and out of 28



### these water systems. 29

30



### DR. DANIEL SCHLENK : Okay. Dr. McMana man? 31

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### DR. JAMES MCMANAMAN : I was struck last time and continue to 1



### be struck this time by the difference between what the 2



### epidemiology data is telling us and what the toxicology 3



### data is telling us. And I'm concerned that we really 4



### don‟t have a way of int egrating those two and we may not 5



### be using the correct animal models by focusing a lot on 6



### the rat. It‟s a convenient system. We understand its 7



### biology pretty well, but I think we might be getting 8



### mixed signals about mechanisms. So it makes it really 9



### dif ficult for those of us who are interested in 10



### mechanisms to say very much about it. 11

12



### DR. DANIEL SCHLENK : Dr. Horseman? 13

14



### DR. NELSON HORSEMAN : The only thing I would add and I would 15



### echo the thoughts of some of the other panel members that 16



### it seems obvious that the EPA, and for that matter, the 17



### participation of the registrants and everyone else is 18



### doing a good job of regulating this in a safe way. 19

20



### But I do think that one of the issues I don't think we 21



### have come to grips with is that the mode of action a nd 22



### maybe in both the cancer side and this other reproductive 23



### toxicology side, but maybe not

, there's an implication 24



### that this has to do with effects that are happening in 25



### the brain, particularly in the hypothalamus. But we 26



### really don‟t have any studies, a t least good studies, 27



### focused on that organ. And I would think that if that's 28



### the mode of action everyone feels like is relevant , then 29



### direct studies on the brain as an organ

-- and the 30



### hypothalamus as an organ

-- need really to be 31



### prioritized. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DAN IEL SCHLENK : Dr. Young? 2

3



### DR. HEATHER YOUNG : I just want to say I was encouraged by the 4



### fact that the Agency undertook a comprehensive review of 5



### the cancer epidemiology literature. I think it was a 6



### major step in the right direction. So I hope that they 7



### continue to do that. A lso to echo R obert Gilliom's 8



### comment in that there are big gaps in the literature with 9



### regard to community exposures and the data there, the 10



### water monitoring data is there. There are cancer 11



### registries , t here are birth defect registr ies. And so 12



### it‟s a matter of really combining those and getting some 13



### information on what some of the reproductive effects may 14



### be, and also looking at the community effects for cancer. 15

16



### DR. DANIEL SCHLENK : Dr. Bove? 17

18



### DR. FRANK BOVE : Ditto. I don‟t think it would take that much 19



### effort either, to do these types of studies. It could be 20



### done rather quickly. The states have the data. Simple 21



### data linkage would be important. Moving away from the 22



### studies we evaluated last time, the ecologic study and 23



### doing i ndividual level studies using the cancer 24



### registries and birth defect registries. 25

26



### DR. DANIEL SCHLENK : Dr. Gold? 27

28



### DR. ELLEN GOLD : Well, being toward the end here, I'm not sure 29



### I have a lot to add. I concur with just about everything 30



### that's been said. I think the importance of looking at 31



### community water supply exposure is important because it's 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### chronic low

- dose, as opposed to the high

- dose that you 1



### see either in the applicators or the manufacturing 2



### workers or in the animals for that matter. So it might b e 3



### more relevant. 4

5



### I just wanted to make one comment about the potential 6



### effect on menopause, age at menopause, which seems like 7



### it‟s not all that important, but there actually is a huge 8



### literature on age at menopause being an indicator for 9



### lo ts of long

- te rm disease risk and life expectancy. 10

11



### But I would also note that oral contraceptive use in high 12



### parity usually delay with the age of menopause, which is 13



### usually a good indicator of long

- term survival, life 14



### expectancy, early age at menopause associated wi th 15



### smoking is usually a bad thing. 16

17



### DR. DANIEL SCHLENK : Dr. Kla i ne? 18

19



### DR. STEPHEN KLA I NE: I wanted to comment on challenges with 20



### analyzing episodic exposure data and make the comment 21



### that, or suggest that in addition to looking at durations 22



### of exposure , you might also want to look at the duration 23



### of the periods between exposures. And they might be just 24



### as important. 25

26



### I think that as you get to the point of understanding the 27



### atrazine receptor better and the reversibility of that 28



### particular process, i t'll probably better drive how you 29



### analyze your exposure data. So it's just something to 30



### keep in mind. 31

32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### DR. DANIEL SCHLENK : Dr. Chambers? 1

2



### DR. JANICE CHAMBERS : I'll just kind of go back to the initial 3



### comments that were made at the first part of the ta ble 4



### here ; encourage d by the pharmacokinetics progress; kind 5



### of discouraged about not knowing what the mechanism is 6



### and do hope that a little bit more about that is known so 7



### that a good human relevant risk assessment can be done 8



### when you get to that in a co uple of years. 9

10



### DR. DANIEL SCHLENK : Dr. Portier? 11

12



### DR. KENNETH PORTIER : I just wanted to point out, this is 13



### probably the first time in about 60 years that every 14



### member on the panel has had closing remarks to make. I 15



### think it speaks to the fact that every body is engaged 16



### with EPA on this. The panel that has been here a number 17



### of times, those of us on the p ermanent panel
, really want 18



### to kind of see this work. I f we haven't answered all of 19



### your questions, it's probably because those questions 20



### can't be answe red at this point in time and that there's 21



### a lot of research, epi and mechanism research, that needs 22



### to be done that we just kind of keep pointing at. 23

24



### Unfortunately, we don‟t know who's going to do it and who 25



### is going to pay for it, but if you're going to answer the 26



### questions, someone is going to have to do it and someone 27



### is going to have to pay for it. 28

29



### DR. DANIEL SCHLENK : Yeah, I'll do it. Just closing comments: 30



### I also applaud the Agency's framework for this approach 31



### as we've had several panels, recent ly even, that have 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### pursued the adverse outcome pathway approach. I think 1



### it‟s the way to go. 2

3



### I would like to encourage the Agency, even though things 4



### may not be going as quickly as possible, but in my 5



### opinion, I think you're on the right track. It's just a 6



### matter of time to get those linkages that are out there 7



### that we've seen with other compounds, such as some of the 8



### c holin esterase inhibitors and thing of that nature, where 9



### there's been some success in that capacity. I think it's 10



### just a matter of ti me, I think, before the top down and 11



### bottom up actually meet in the middle, perhaps, in terms 12



### of the effects that are present. So I'm encouraged. 13

14



### As usual, when we come to these things, the amount of 15



### information we learn is amazing. So I‟d like to app laud 16



### the Agency for the presentations and the questions that 17



### you are asking. I think that's very encouraging. With 18



### that, I'll turn it over to Dr. Mendez, if you have any 19



### closing comments for yourself and the Agency. 20

21



### DR. ELIZABETH MENDEZ : On behalf of t he team and the Agency, I 22



### want to express our deepest gratitude to the panel for 23



### their thoughtful considerations and deliberations during 24



### this process. 25

26



### As Dr. Portier alluded to, there are a lot of questions. 27



### There are some questions that you couldn‟t a nswer because 28



### the data is just not available

. I'm personally a little 29



### bit encouraged by the fact that I think we're wrestling 30



### with the right issues. T hat, to me, is encouraging that 31



### we are looking where we need to be looking at. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### As you may have noticed , during the past few days I have 2



### been furiously taking notes. You have given us a lot to 3



### think about, and as we move forward with this process, we 4



### will take your advice under consideration. 5

6



### As always, we remain committed to keep vigilant to any 7



### new de velopments, and as those become available, we will 8



### try to integrate it into our evaluations and we 9



### appreciate all the hard work. I mean, we understand that 10



### 600 pages plus of documentation to go through is a lot 11



### and the fact that you've gone through it wit h such care 12



### and such precision, we truly appreciate that. 13

14



### DR. DANIEL SCHLENK : Thanks. I'd also like to express my 15



### appreciation to the panel for working together as well as 16



### you have. You know, on the permanent panel, we see a lot 17



### of these things and o ften times there's not the congruity 18



### or collaboration that takes place. And it's obvious you 19



### guys have gone the extra mile in working together to get 20



### us through a fairly lengthy process about a day ahead of 21



### schedule, and I really appreciate that and I app reciate 22



### you working together for that. That doesn't always 23



### happen and my thanks, at least personally, for that. 24

25



### I'd also like to appreciate or give thanks to the EPA, 26



### again, for their staff for the presentations, the PIs for 27



### the research that they are doing, and the FIFRA staff, 28



### Laura Bailey and the staff for making it as easy as 29



### possible to get here and to get away and making our stay 30



### as comfortable as possible. They‟ve done a great job for 31



### that. With that, I'll turn it over to Joe Bailey. 32FIFRA SCIENTIFIC ADVISORY PAN E L DOCKET #EPA

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### JOSEPH BA ILEY : Dan certainly covered all of the thanks that 2



### I wanted to make, but first and foremost, I do want to 3



### thank the panel for their commitment to come here and 4



### take the time out of their schedules and prepare as well 5



### as they did for the meeting; the time at the meeting as 6



### well as the follow

- up work we'll be working on to get the 7



### report finished. Thanks to EPA, OPP, and ORD for working 8



### with us to coordinate all of this information. And the 9



### public commenters for bringing their thoughts forward. 10



### T he final report, we will have it done within 90 days 11



### after the meeting. So thank you all very much. 12

13



### DR. DANIEL SCHLENK : Meeting is adjourned. 14

15



### (Whereupon, at 2:15 p.m., the meeting was adjourned.) 16



### * * * * * 17