FIFRA SCIENTIFIC ADVISORY PANEL (SAP)

 OPEN MEETING

 REEVALUATION OF THE HUMAN HEALTH EFFECTS

 OF ATRAZINE:

 REVIEW OF NON-CANCER EFFECTS AND

 DRINKING WATER MONITORING FREQUENCY

 DOCKET NUMBER: EPA-HQ-OPP-2010-0481

 UNITED STATES ENVIRONMENTAL

 PROTECTION AGENCY

 CONFERENCE CENTER LOBBY LEVEL

 ONE POTOMAC YARD (SOUTH BUILDING)

 2777 SOUTH CRYSTAL DRIVE

 ARLINGTON, VIRGINIA 22202

 SEPTEMBER 17, 2010

 8:35 A.M.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 2

1 FIFRA SCIENTIFIC ADVISORY PANEL

2 MEETING

3 SEPTEMBER17, 2010

4 DR. STEVEN HEERINGA: Good morning,

5 everyone, and welcome back to this fourth and final

6 day of the FIFRA Scientific Advisory Panel Meeting on

7 the topic of the Re-Evaluation of the Human Health

8 Effects of Atrazine: Review of Non-Cancer Effects and

9 Drinking Water Monitoring Frequency.

10 I think since there are very few new

11 faces in this room that we won't go around and have the

12 Panel introduce themselves this morning. I'll just say

13 I'm, I'm Steve Heeringa. I'm the Chair of the

14 proceedings.

15 I want to thank Dr. Portier for filling

16 in for me late yesterday afternoon, and I understand

17 that we have gone through the Charge Question No. 4 and

18 its subparts. Dr. Portier has left it open for any

19 additional comments from Panel Members related to

20 Charge Question No. 4.

21 Any additional thoughts overnight from

22 people, things they would like to add on the of

23 course, until the end of these proceedings if something

24 comes to mind, you're always welcome to bring it

25 forward. So don't hesitate, but in terms of sort of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 3

1 the organization of our discussion, nothing else to

2 add? Wes, Dr. Coupe, others all set? Thank you.

3 SPEAKER: You're okay?

4 DR. STEVEN HEERINGA: Okay. Well, if

5 that is the case, I want to turn briefly to Joe Bailey,

6 the Designated Federal Official for these meetings,

7 just to see if Joe has anything to add before we begin.

8 DR. JOSEPH BAILEY: I really don't have

9 anything to add, I just want to welcome everybody back

10 for the last day. I think we've made good progress on

11 the agenda so far. We're right on target, if not a

12 little bit ahead, so .

13 DR. STEVEN HEERINGA: Do you want to

14 mention hydroxyatrazine?

15 DR. JOSEPH BAILEY: Oh, yes, I will make

16 one comment. Dr. Stone yesterday, I'm sorry, Mr.

17 Stone yesterday in the discussions about the water

18 issues made a reference to two USGS documents that

19 have some information on hydroxyatrazine monitoring.

20 He's going to provide me those references and the link,

21 and I will send that out to the Panel.

22 I believe Syngenta has also provided a

23 little bit of information, which I will also provide to

24 the Panel. It did come in after the Comment period had

25 closed, so I will treat that accordingly and send it to
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 4

1 you as well and put it in the docket. That's all I

2 have.

3 SPEAKER: Last night I downloaded the

4 most recent JNPR evaluation of atrazine and all of its

5 metabolites, so I can provide that reference and the

6 link as well.

7 DR. STEVEN HEERINGA: Thank you very

8 much.

9 DR. JOSEPH BAILEY: Okay, good. Thank

10 you.

11 DR. STEVEN HEERINGA: That's very good.

12 So those materials will all be available to the Panel

13 on the docket, and I think several of these things are

14 in hard copy.

15 DR. JOSEPH BAILEY: It will all be

16 electronic.

17 DR. STEVEN HEERINGA: Okay, thank you

18 very much.

19 Okay. At this point, just to give

20 everybody a sense of what I would anticipate for the

21 day, it is my intent to finish by 12:00, and that gives

22 us well over three hours of total time on two questions

23 and wrap-up, and we should be able to do that. So

24 that's. again, I, if it turns out that we have

25 productive discussions that take us longer we'll do
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 5

1 that, but that's my aim. People are trying to plan

2 their day here.

3 At this point in time, I think I'll turn

4 to maybe Nelson to read the Charge Question No. 5 into

5 the record or

6 DR. JACK FOWLE: I want to introduce

7 myself, my name is Jack Fowle, and I'm the Deputy

8 Director of the Health Effects Division in the Office

9 of Pesticides.

10 DR. STEVEN HEERINGA: Okay.

11 DR. JACK FOWLE: And it clearly must be

12 an atrazine SAP, because Anna has written saying there

13 is a major water-main break and she's got to take a

14 major detour.

15 SPEAKER: Oh, again?

16 DR. JACK FOWLE: So she will be a little

17 bit late, so we'll proceed.

18 DR. STEVEN HEERINGA: What was it, a

19 snowstorm last

20 SPEAKER: I think it was another water

21 main.

22 DR. STEVEN HEERINGA: A water main,

23 okay.

24 DR. JACK FOWLE: Something like that.

25 SPEAKER: Was there an accident at some
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 6

1 point in time?

2 DR. STEVEN HEERINGA: Okay. Well, thank

3 you very much.

4 DR. JACK FOWLE: If you can put up with

5 my scratchy voice, I can read this question, Question

6 5: The Agency requests the Panel to comment on

7 important scientific factors for the Agency to consider

8 in its analysis.

9 Please include in your comments specific

10 consideration of uncertainties in estimating drinking

11 water exposures and remaining uncertainties in

12 atrazine's toxicological profile across life stages,

13 particularly as they pertain to assessing risk to

14 infants and children.

15 DR. STEVEN HEERINGA: Our first...thank

16 you very much first, Dr. Fowle.

17 I want to turn to our lead discussant on

18 this, Dr. Pope.

19 DR. CAREY POPE: Yes, good morning. So

20 Question 5, I saw two parts of it, basically asking

21 about uncertainties regarding drinking water exposures

22 for young individuals and uncertainties in the

23 toxicological profile across life stages.

24 I don't have a whole lot to say about

25 the first aspect, although I did pick up a couple of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 7

1 things that I would consider that evaluating treated

2 water samples for levels seems a better approach than

3 untreated water sources.

4 The other question about the duration of

5 dosing, it would be better you know, currently,

6 there's a 90-day rolling average in whether there may

7 be a better duration of exposure to use. I'm still not

8 certain whether there's in my mind a better duration to

9 point to for either the adults or the developing

10 individuals.

11 Regarding the second part of this

12 question about the profile across life stages, I have a

13 little bit more to say.

14 And by the way, Dr. Meek is not here;

15 but she provided her information to me, and I have that

16 as well.

17 DR. STEVEN HEERINGA: Yeah, she said she

18 would do that. That's very good.

19 DR. CAREY POPE: So while there is a

20 good consensus about atrazine's influence on GnRH21 mediated LH surge and the reproductive or developmental

22 toxicity, there is also some confusion, as would be

23 expected. The Morseth, et al., study, currently used

24 to set the point of departure, has not been replicated

25 in more recent studies from the registrant using
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 8

1 relatively similar dosing strategies, repeated dosing,

2 dietary. And, you know, in the review, it's difficult

3 to reconcile some of these differences in these

4 studies.

5 In the studies using radiolabeled

6 atrazine, it appeared to me that, if anything, there

7 was less uptake of atrazine across a placenta than

8 levels noted in the dam, and these suggest that there

9 may not be selectively higher exposures to the

10 developmental organism during prenatal period.

11 A number of studies examined relative

12 toxicity with either prenatal dosing, postnatal or

13 peripubertal exposures to atrazine. And with the

14 prenatal exposures, generally endpoints like preputial

15 separation and mammary gland development were noted;

16 but the repeated exposures were somewhere between 50

17 and 100 milligrams per kilogram per day. And prenatal

18 combined with lactational exposures showed similar

19 effects on preputial separation and prostatitis; but

20 only 100 milligrams per kilogram per day were used.

21 Several studies evaluated the effects

22 during peripubertal exposures, and again preputial

23 separation was affected. And this, from what I could

24 see, was the lowest dose where you saw a developmental

25 effect, and it was at 12.5 milligrams per kilogram per
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 9

1 day for quite an extended period.

2 Testosterone levels were evaluated with

3 a couple of studies, and I think the lowest dose,

4 effective dose, was 50 milligrams per kilogram per day.

5 Thus, in this collection of studies,

6 there's not much evidence that either prenatal,

7 lactational or peripubertal exposures were leading to a

8 higher sensitivity in development of organisms.

9 We spent quite a bit of time yesterday

10 on a number of occasions talking about the studies with

11 the atrazine mixture by Enoch, et al., on 2007.

12 And also the hydroxyatrazine metabolite

13 has come up a number of times. I want to say here that

14 all hydroxyatrazine metabolites are not created

15 equally. There is a ring structure hydroxylation,

16 which appears to be the one used in Enoch's paper that

17 appears to be an environmental contaminant, and the one

18 set are reported in the metabolism studies for alkyl

19 hydroxylations, including a recent paper by, from

20 Hotchkins Lab showing ethyl and isopropyl

21 hydroxylations.

22 And I'm not sure, Dr. Lowit mentioned

23 yesterday that there are some studies in the literature

24 looking at the hydroxyatrazine metabolite. I'm not

25 sure which ones she's referring to, whether they're the
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 10

1 ring hydroxylations or the alkyl hydroxylations. I

2 think it could be important.

3 But regardless, this paper reported

4 significant changes in mammary gland development with

5 very low levels, down to less than 1 milligram per

6 kilogram per day, with this atrazine mixture.

7 The white paper, one of the kind of

8 overall feelings I had as I went through the white

9 paper is that the study by Enoch and coworkers in 2007

10 was being kind of downgraded, so to speak, as far as

11 its potential influence in the risk-assessment process

12 for a number of reasons.

13 However, I feel that capturing the

14 makeup of water contaminants, it in my mind is a good

15 idea while it's obviously more complex to handle and

16 interpret.

17 There's obviously some legitimate

18 questions noted concerning the date in that paper.

19 We've already talked about the score and the

20 histological lesions and the reporting and the analysis

21 of the lesions, and whether they are histological or

22 morphometric is better.

23 There was obviously some low mean scores

24 in one of the control groups in that mammary

25 development data that kind of weakened the impact of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 11

1 it.

2 There was little change in the effect

3 with the higher dosages across a hundredfold dose

4 range, which could be difficult to interpret; however,

5 I think it's also reasonable to assume that even if

6 results like that don't really fit very well into a

7 risk-assessment process and trying to determine points

8 of departure, I think it's reasonable to think that

9 some kind of developmental alteration could occur at a

10 certain level once a minimal level of exposure is

11 reached. It doesn't really matter if you can have more

12 added on top of it.

13 One interesting piece of information

14 that I haven't heard and didn't key into before this

15 morning when I was kind of looking over these papers

16 again was a paper by Stoker and Cooper in 2007 when

17 they looked at tissue distribution radioactivity

18 following C14 atrazine, and the mammary gland was

19 incredibly packed, relatively speaking, full of

20 atrazine or metabolites. It was the highest percent of

21 radioactivity, higher than liver and kidney; and I made

22 a graph of this, but I'm not sure there's really much

23 reason to show it.

24 DR. STEVEN HEERINGA: We can bring it

25 up. We'll bring it up if you went through all the
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 12

1 trouble to make a graph.

2 DR. CAREY POPE: Yeah, it wasn't that

3 much trouble.

4 So you can see that there's quite a

5 range of tissues here, including tissues from the

6 central nervous system, spleen, liver, kidney, gonads.

7 And, you know, to me, that's pretty striking that there

8 may be something to think about as far as accumulation

9 of atrazine or its metabolites in the mammary gland.

10 And this is the dam following oral dosing, 2 milligrams

11 per kilogram. I think it's 3 hours after dosing.

12 It's not the developing mammary gland;

13 but, you know, if it is, if that was the developing

14 mammary gland, you'd think, "Wow. Maybe putting these

15 two things together, there's something to it".

16 And thus while I think no other studies

17 aside from Enoch, et al., in 2007 have used this

18 mixture, it's a much more complicated thing to think

19 about as far as what these metabolites are, and I think

20 to me it kind of sends up a flag that the mammary gland

21 may be highly exposed and may be highly sensitive

22 during the development.

23 A little bit more about the

24 hydroxyatrazine ring structure hydroxyl group, it's

25 apparently a minimal component in the mammalian
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 13

1 metabolism or maybe not even a component of mammalian

2 metabolism of atrazine; but it appears to be a

3 substantial environmental contaminant.

4 I didn't, however, look at the original

5 papers that was cited in the Enoch, et al., that refers

6 back to the lowest concentrations of that in the water

7 samples.

8 So the very low exposure levels suggest

9 that the mammary gland effects may be sensitive

10 endpoints following gestational exposure to atrazine

11 and/or its metabolites. There is no clear-cut

12 mechanism for what might be happening. These findings

13 which apparently selected the accumulation of atrazine

14 or its metabolites in the mammary gland provide concern

15 for me that the high sensitivity is developing in

16 organisms.

17 And as noted yesterday, I mean, I think

18 standing alone, the Enoch, et al., paper is kind of, is

19 standing alone. There is not much to kind of reinforce

20 those findings, and so I think replication and

21 extension of those findings with dosimetry and looking

22 at individual effects on a mammary gland at low-level

23 exposures are, are necessary to effectively influence

24 the risk assessment.

25 DR. STEVEN HEERINGA: Thank you, Dr.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 14

1 Pope.

2 And Dr. Chambers.

3 DR. JANICE CHAMBERS: Thank you. Just a

4 couple of things that I certainly agree with with what

5 Carey just said. I think the finished water will be a

6 better reflection of what the developing organism human

7 would be exposed to, and also the fact that an awful

8 lot of the data we saw were just on high doses is not

9 reflective of what humans would be exposed to. So we

10 certainly need more low-dose information.

11 I guess a couple of things that I keyed

12 into is with respect to the uncertainties you're

13 dealing with. I think you're doing, we're seeing a lot

14 more of the kinetic studies right now, and I think

15 those are extremely useful in trying to determine what

16 the internal dose of both the moms and the fetuses or

17 the pups would be, so I would encourage doing that.

18 The feeding regimens we were seeing, I

19 think it is a much more realistic paradigm for

20 presenting the delivery or delivering the dose as it

21 would be seen in drinking water exposures, and so I

22 would encourage more of that. It's not drinking water,

23 but it is an exposure that occurs over a period of time

24 as opposed to one bolus and a gavage dosing thing; so I

25 think that probably is useful.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 15

1 The pseudo-steady state data that we saw

2 that was presented to us and everything was very, very

3 useful, I think, in trying to estimate what the

4 internal dose is, which hopefully can then be related

5 to the toxicology data.

6 Another thing that is going to be useful

7 I gather that's on the mill or in the works right now

8 is getting enough data to develop a PBK model, and that

9 would be useful. Certainly to get that appropriate for

10 the developing organism, we're going to need some

11 metabolic parameters on the developing organism fetus

12 and the infant child.

13 Some of the data we saw -- and I think

14 this was from Syngenta's metabolism parameters -- only

15 had one human sample. We're certainly going to need

16 more than one human to get a representative number on

17 that.

18 I guess one of the most equivocal things

19 we've talked about -- and we talked about it at length

20 yesterday and Carey just talked about it quite a bit

21 today -- was that mammary gland issue with the Enoch

22 paper. It's really hard to sort that out; I mean, you

23 struggled with it, and I agreed with your concern about

24 the conduct of that study. If it's real, it certainly

25 needs to be dealt with in risk assessment sooner or
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 16

1 later. I guess Gerry said yesterday we need to

2 determine whether it's an artifact or whether it's

3 real. So it certainly needs to be replicated so that

4 you can sort that out in, in the risk-assessment

5 process.

6 What you just presented with respect to

7 concentrations, that probably is not too surprising;

8 the mammary gland, I assume, would be a pretty lipid9 rich tissue and would accumulate lipophilic compounds.

10 So that's probably not too surprising; whether the fact

11 that it's there and the lipid is actually exerting any

12 toxic mechanisms is hard to know.

13 So, again, that's a big uncertainty that

14 I think we need to sort out. But it's out there, that

15 paper is out there at those low doses, and some sort of

16 replication needs to be done to determine how real that

17 is.

18 DR. STEVEN HEERINGA: Thank you, Dr.

19 Chambers.

20 Dr. Fenner-Crisp, Penny?

21 DR. PENELOPE FENNER-CRISP: A more

22 general statement, comment in addition to the ones that

23 the two have already made; I agree with theirs, as

24 well.

25 This is all about one aspect of the
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 17

1 decision-making process, well, not all about, but

2 incumbent in here is the decision on the 10x safety

3 factor. And embedded in that assessment process is

4 both a qualitative and a quantitative component.

5 The qualitative component being, do you

6 have data, and the appropriate data, that show whether,

7 what the toxicity profile at various life stages looks

8 like, and there's a lot of work going on to describe

9 that at various times.

10 But there is also a quantitative

11 component in here. Once you understand toxicity

12 profiles of various pre-adult stages, how do they

13 compare quantitatively with the adult? And I asked

14 Anna the other day if the Agency thought it had enough

15 data describing the toxicity profile in the adult

16 against which one could make comparisons, and she said

17 yes.

18 So I would submit that incumbent on the

19 Agency when they redo this discussion that that's where

20 you start. Here is what we have acquired in the adult

21 and it says such and so; here is what we've now done

22 with respect to various life stages.

23 The toxicity profiles match up or not,

24 as the case may be, and here are where quantitative

25 differences may exist, and therefore this would be our
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 18

1 decision logic for evaluating the component of the 10x

2 that's dedicated to the toxicology.

3 One of the things I found interesting

4 about the milk data was -- or that kinetic data was the

5 rough equivalence in plasma for the fetus and the

6 adult, but a significant drop-off in the milk.

7 So one can't understand fully what the

8 differential might be in sensitivity or tox profile

9 comparing with an adult there. I'm not suggesting you

10 go back and direct those pups with equivalent doses

11 that match the kinetics in the adult; but if it comes

12 to having to fully understand the kinetics in that life

13 stage, that's one thing that might be appealing.

14 I think at this stage, we can't comment

15 on whether or not the completed studies and those that

16 are in the pipeline are going to be sufficient to

17 answer all the questions on potential pre-adult

18 toxicity and the potential for quantitative

19 differences. So I think we have to, I would have to

20 reserve judgment on that until those studies are

21 finished.

22 DR. STEVEN HEERINGA: Thank you, Dr.

23 Fenner-Crisp.

24 Dr. Pope, could you read Dr. Meek's

25 comments into the record?
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 19

1 DR. CAREY POPE: Okay, this is from

2 Bette Meek, and I'll just have to read it word-for3 word: "Consideration of the value of the FQPA safety

4 factor is seemingly best predicated on transparent and

5 systematic consideration of the most important

6 qualitative and quantitative uncertainties associated

7 with both exposure and effect relevant to susceptible

8 life stages in a context consistent with that for other

9 pesticides.

10 In view of the fact that the database

11 for atrazine relevant to the selection of this factor

12 is still evolving, reference here is to some of the

13 generic aspects that might be explicitly considered

14 based on outcome of additional analysis, including for

15 exposure this could relate to the likelihood of

16 capturing the relevant periods of susceptibility or

17 over- or underestimating exposure for all life stages,

18 with the proposed monitoring strategy, including, for

19 example, consideration of determination of TCT rather

20 than atrazine.

21 "For effect, some critical questions

22 and/or aspects to be addressed in this context include:

23 to what extent does the database on hazard and kinetic

24 and dynamic data inform us about potential increased

25 susceptibility of infants and children?
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 20

1 Is the early key event or late adverse

2 effect for the critical effects sufficiently protective

3 for all age groups based on hazard characterization,

4 including knowledge of mode of action? How protective

5 is it, for example, an early key event protective for

6 later adverse effects?

7 What is the impact to the potential

8 reliance on a benchmark dose versus an effect level in

9 relation to uncertainty in the characterization of the

10 relevant dose-response relationship?

11 Does the degree of conservatism

12 associated with use of a lower confidence interval for

13 a benchmark dose increase confidence? And finally,

14 while the epidemiological data are not considered

15 sufficiently robust for inclusion in quantitative risk

16 assessment, can data from any of the studies that are

17 considered of highest quality be used to provide some

18 idea of relative sensitivity of various age groups of

19 the human population?"

20 DR. STEVEN HEERINGA: Thank you, Dr.

21 Pope. And again, those were Dr. Bette Meek's comments,

22 which she had written up and prepared for us.

23 At this point, I turn to the other

24 members of the Panel for any comments or additional

25 contributions on Charge Question No. 5?
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 21

1 Yes, Dr. McManaman?

2 DR. JAMES McMANAMAN: So in regards to

3 Dr. Chambers' statement that this would be a lipophilic

4 compound, it's unlikely to be lipophilic since it's

5 likely that those nitrogens are charged at

6 physiological pH and it has lots of hydrophilic

7 residues on it; so I think it's unlikely to be

8 lipophilic.

9 And if Dr. Pope could clarify the, that

10 the C14 distribution data, that was in a lactating dam?

11 DR. CAREY POPE: Yes.

12 DR. JAMES McMANAMAN: So during

13 lactation, there is very little adipose remaining in

14 the mammary gland; it's almost all been de-lipidated,

15 if you will, so it's almost all glandular structure.

16 Then regarding the risk assessment, it seems

17 to me that there are two underlying aspects of this.

18 Dr. Fenner-Crisp mentioned that there is qualitative

19 and quantitative.

20 And my concern is that we are trying to

21 - not "We are trying to do this", may be too strong --

22 but there is a move to try to put a square peg in a

23 round hole, in that if atrazine were directly

24 administered regarding the mammary gland, were directly

25 affecting the mammary gland, then that would be a
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 22

1 primary target and we could expect a normal dose2 response curve.

3 But if the mammary gland is a secondary

4 target related to some other aspect of physiology, then

5 I don't know that we would expect it to find a normal

6 dose-response curve.

7 And so my concern is that if it has to

8 have a dose-response curve to be considered as part of

9 the risk assessment, then I think that we're missing,

10 we potentially would be missing secondary effects of

11 which there may not be a normal dose-response curve.

12 Dr. Rayner's study showing that F2 pups

13 had lower weights in the atrazine-treated animals, this

14 suggests that it is a comp...atrazine is having complex

15 physiological effects that, again, would not expect to

16 be a simple dose-response curve, because F2 generation,

17 that's the grandchildren of the dam that was treated.

18 So I think that that needs to be taken into account in

19 assessing risk.

20 And if the models don't fit in a

21 preconceived notion, then I think that they should not

22 just be dismissed, and we should look for further

23 explanations in terms of risk assessment.

24 And then there is one other thing that I

25 want to have, make sure that it's read into the record,
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 23

1 and that is the Syngenta work, it's Figure 2 on Coder

2 D. I have it on my computer, but it's the Coder 2010 D

3 study, it's Figure 2.

4 And what it shows is it's the effect of

5 increasing doses of atrazine on the weights of dams

6 during lactation. And if we were to compare to the

7 pair-fed dam as the control as suggested by Syngenta

8 Group, then we have a dose-response relationship

9 between the 100milligram per kilogram atrazine and the

10 50 milligram per kilogram atrazine in terms of less

11 change in body weight. Okay? So the greatest change

12 in body weight was the pair-fed, and then the next was

13 100, and the next was 50.

14 So if that is, if we can use that as an

15 example, then I suggest that the Agency consider that

16 atrazine may be having metabolic effects and that's on

17 the adult, and I don't know that that -- it certainly

18 wasn't part of our Charge Question; but it's come out

19 of the data -- and that there be more studies related

20 to potential metabolic effects of atrazine on

21 particularly dams during lactation and possibly dams,

22 non-lactating dams and pups.

23 DR. STEVEN HEERINGA: Thank you, Dr.

24 McManaman.

25 Yes, Dr. Schlenk?
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 24

1 DR. DANIEL SCHLENK: Just to clarify on

2 the lipophilicity issues relating to atrazine, I was

3 just looking at the log P; it's 2.75. So it actually

4 is fairly lipophilic; it's about 100 times more likely

5 to be in octanol than water, so it's fairly lipophilic.

6 DR. STEVEN HEERINGA: Dr. Krishnan?

7 DR. KANNAN KRISHNAN: The biological

8 measures of the partition coefficient don't seem to

9 suggest that, from my recollection. But those are

10 within a factor of 1:3, the plasma to various tissues;

11 just an observation, recollection from the data.

12 DR. STEVEN HEERINGA: Dr. Horseman.

13 DR. NELSON HORSEMAN: I would just say

14 it doesn't much matter. There's a lot of it in the

15 mammary gland. And there's just about every kind of

16 metabolite in the lactating mammary gland, lipophilic

17 and hydrophilic and every other sort of so that

18 doesn't really matter. Whether it's surprising or not,

19 it's there.

20 DR. STEVEN HEERINGA: Any other

21 contributions?

22 Dr. Bailar.

23 DR. JOHN BAILAR: Just to have it on the

24 record, I would urge EPA to keep its eye firmly fixed

25 on effects of real concern at doses of real concern.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 25

1 Much of the new information we've received for this

2 meeting falls outside one or both of those limits. I'm

3 not saying it's irrelevant; but every time EPA uses

4 data that are either not focused on effects of real

5 concern at doses of real concern, they should say why

6 it is considered relevant.

7 DR. STEVEN HEERINGA: Thank you, Dr.

8 Bailar.

9 Just again reminding ourselves,

10 consideration of uncertainties in estimating drinking

11 water exposures and any remaining uncertainties in

12 atrazine's toxicological profile across life stages,

13 particularly assessed in infants and children. Any

14 additional comments or input on life stage?

15 We heard some things, and I think the

16 metabolism suggestion was one and there have been

17 others. So, Dr. Pope and Dr. Chambers and Dr. Fenner18 Crisp, other comments people would like to make on this

19 particular question?

20 I'm going to turn to the EPA, and I'll

21 turn to Dr. Fowle or Dr. Lowit?

22 DR. ANNA LOWIT: I think the only thing

23 I would ask is implicit in the rest of the text that's

24 not on the screen is that a lot of the water

25 uncertainties were covered in Question 4, basically.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 26

1 If there were anything that weren't covered in Question

2 4 that are relevant here, to make sure they get put on

3 the record.

4 DR. STEVEN HEERINGA: Right, okay. And

5 I think again if anyone has anything to add before we

6 close these proceedings, any thoughts that come to

7 mind, you'll certainly have a chance to bring them in.

8 And in the preparation of the report, as you well know,

9 there is reorganization of some of the discussion to

10 make it match the organization of the Charge Questions.

11 Okay.

12 Yes, Dr. Horseman?

13 DR. NELSON HORSEMAN: Again, not to drag

14 this out a little bit, but we heard an argument here

15 for monitoring finished drinking water, and clearly the

16 epidemiologists would much prefer that they have that

17 information to understand real exposure.

18 I wonder if given that in general

19 primary and secondary conventional water treatment

20 isn't designed in any sense to remove these components,

21 the extent to which things like atrazine and soluble

22 components are removed in conventional water treatment

23 seems to me sort of accidental and that only tertiary

24 treatment is designed to remove these things.

25 I wonder if aside from the utility of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 27

1 the finished-water information for epidemiology, if

2 this is actually the appropriate charge in terms of

3 knowing finished water and so on.

4 DR. STEVEN HEERINGA: Dr. Chambers?

5 DR. JANICE CHAMBERS: The reason I

6 suggested that and perhaps the reason Carey suggested

7 that is that the epidemiology exposure information is

8 so weak in terms of, you know, proximity to a cornfield

9 or something like that. If you're going to get a more

10 accurate assessment of what people are being exposed

11 to, you need to look at the actual drinking water.

12 DR. STEVEN HEERINGA: Dr. Pope?

13 DR. CAREY POPE: Yes, I agree also with

14 what Jan just said; but I believe someone in the last

15 couple of days also showed some differences in the

16 different treatment facilities as far as the incoming

17 and the outcoming, the contents were that I thought,

18 depending on which community water service was there,

19 there were different clarifications of the chemicals.

20 DR. STEVEN HEERINGA: I think Dr.

21 Thurman presented a comparative chart, and then I think

22 also Syngenta chart or Dr. Hall, Mr. Hall, Dr. Hall

23 had a chart comparing efficacy of it on about 60

24 different sites as to the removal.

25 And clearly the activated-carbon
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 28

1 filtration was the one that appeared to be at least

2 producing null results, and as he went up the ladder

3 where there was no carbon treatment, there was more

4 likely an occurrence of atrazine.

5 Yes, Dr. McManaman?

6 DR. JAMES McMANAMAN: One last thing and

7 very brief. I think there could be a wealth of

8 information obtained by examining in laboratory animal

9 studies the fecal content of atrazine. I asked this

10 question the other day to Syngenta and they didn't have

11 the information regarding the amount of atrazine in the

12 fecal content; but they showed studies in which

13 atrazine, dietary dosing of atrazine, had no effect.

14 Well, the only way that we can

15 understand what those studies mean is if we understand

16 how much is actually coming in, and a very simple

17 procedure that could be used is by just examining the

18 amount that was given, the amount that was absorbed,

19 because it's just a simple subtraction.

20 DR. STEVEN HEERINGA: Okay. Dr.

21 McManaman, do you feel, I thought we heard there was at

22 least a rough estimate of the percent of excretion in

23 fecal matter. Was this a different --

24 DR. JAMES McMANAMAN: That was from a

25 gavage dose, not from a dietary dose.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 29

1 DR. STEVEN HEERINGA: Thank you. Thank

2 you, thank you.

3 Dr. Horseman, you have something

4 additional?

5 DR. NELSON HORSEMAN: No.

6 DR. STEVEN HEERINGA: Any additional

7 comments on this?

8 Okay. Again, we'll return and give

9 everybody a chance for some final wrap-up comments.

10 Let's move on, then. I can see we're

11 going to easily make 12:00 o'clock unless this breaks

12 down.

13 But good, good. I think it's been

14 productive, all of these discussions.

15 So Question 6, I'm going to rotate here.

16 Mr. Fowle or Anna?

17 DR. ANNA LOWIT: Question 6: Please

18 comment on the Agency's analysis and preliminary

19 conclusions contained in Section 8.0 in the draft Issue

20 Paper as it relates to the potential critical windows

21 of exposure. Please include in your comments

22 additional or alternative approaches or data that may

23 inform this issue.

24 DR. STEVEN HEERINGA: For our

25 integrative analysis, we'll turn to Dr. Bucher to
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 30

1 start.

2 DR. JOHN BUCHER: Thank you.

3 So in preparation for this, I sent some

4 preliminary remarks around to the group earlier on, and

5 I got a reality check back from Dr. Coupe on some of

6 the comments I had made with respect to water systems;

7 so I acknowledge his contributions here, and also Dr.

8 Meek sent me some comments to integrate into this

9 document as well.

10 So Section 8 in the Atrazine Issue Paper

11 systematically addresses a number of issues. These

12 include: the use of the LH surge suppression in the

13 rat as a benchmark response; the strength of evidence

14 linking the benchmark response with a variety of

15 endpoints in human epidemiology and experimental animal

16 studies; the comparative timing and extent of exposures

17 with respect to the potential to suppress the LH surge

18 in animals and humans, including kinetic and dynamic

19 considerations; the potential for water atrazine

20 concentrations exceeding a level of concern to be

21 missed by current sampling procedures; and the concept

22 that sampling frequency can be meaningfully adjusted

23 based upon the potential for human health outcomes.

24 The Agency has done a good job of

25 summarizing the situation in each of these areas with
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 31

1 respect to the uncertainties and limitations in both

2 the data and in our scientific understanding of what

3 these data are telling us.

4 The Agency has determined that the

5 collected information suggests a water-sampling

6 frequency of between a few days and four weeks based on

7 durations of exposure considered relevant with respect

8 to potential human health outcomes. Currently, the

9 sampling frequency required to the registrant is once a

10 week during the use season and once every two weeks

11 during the rest of the year.

12 There are a whole series of assumptions

13 and extrapolations that contribute to this proposed

14 critical window of human exposure, and given the

15 collected uncertainties that these assumptions

16 introduce, the imprecision in this proposed sampling

17 frequency seems fully justified.

18 This may be about as precise an estimate

19 as can be obtained when starting with the experimental

20 animal data and the exposure requirements for the LH

21 surge suppression, as opposed to using outcomes that

22 are more unequivocally adverse.

23 In this regard, the consideration of

24 human relevance of the adversity of the LH surge

25 suppression on the basis of both the pharmacokinetics
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 32

1 and the pharmacodynamics, taking into account the

2 broader database, including data on other

3 pharmaceutical agents that have been used to block the

4 LH surge, is to be commended.

5 After all this, the proposed range of

6 human exposures responsible for potential adverse

7 outcomes still appears to be little more than an

8 educated guess.

9 Question 6 specifically requests

10 alternative approaches and, in fact, there is another

11 way of approaching this that may be useful, at least

12 when setting the boundaries of exposures that may

13 present a concern for human health effects.

14 The current epidemiology database is

15 characterized as providing suggestive evidence that the

16 mechanisms of action thought to be operative in rats

17 may be occurring in humans exposed to atrazine. The

18 Agency has appropriately concluded that the limited

19 human evidence is insufficient to establish causality

20 and does not provide sufficient quantitative exposure

21 information to use in a risk assessment.

22 However, what if one assumes that the

23 reported human health outcomes are, in fact, due to

24 current levels of exposure to atrazine? Although the

25 water-sampling data may not be adequate to assure that
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 33

1 atrazine peaks are captured in all water systems,

2 clearly, some of the patterns we have seen are based on

3 rather comprehensive datasets.

4 These patterns of atrazine

5 concentrations in water could provide reasonable

6 estimations of the extent and duration of human

7 consumption of atrazine following agricultural

8 applications for re-emergent weed control.

9 I would suggest that this represents an

10 alternative approach to getting at levels of atrazine

11 in drinking water that may represent risks to human

12 health.

13 These risks could be compared certainly

14 on an order-of-magnitude scale against those calculated

15 from the animal data and may provide a lower bound

16 conservative floor from which to work and provide a

17 different perspective on the water-sampling frequency

18 problem.

19 This would put the Agency in a much

20 better position if, in fact, the agricultural health

21 study or the other epidemiology studies that are

22 ongoing or may be done in the future provide further

23 support for human health effects as the results

24 continue to accumulate and be reported.

25 The other consideration when faced with
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 34

1 an uncertainty over a critical exposure window of a few

2 days to four weeks is whether basing sampling frequency

3 on human health effects is, in fact, the best course of

4 action.

5 Atrazine concentrations in a stream and

6 subsequently in the finished water supply or the

7 community water supply that uses that steam as its

8 water source are dependent upon many factors that vary

9 spatially and temporally.

10 As was discussed yesterday, each

11 community water system is unique in factors that affect

12 the delivery of atrazine, such as a drainage base and

13 size, characteristics of the soils, cropping patterns,

14 slope, et cetera, as well as whether the community

15 water source and water intake is directly in the steam,

16 in a reservoir or in an off-stream storage facility.

17 In addition, there are many factors that

18 affect the ability of a water-treatment system to

19 remove atrazine from water such as use of activated

20 carbon and the type of oxidant. It's also been shown

21 that the amount of atrazine in the system can sometimes

22 be related to the ongoing maintenance of the treatment

23 plant.

24 So, in fact, it may be more useful to

25 consider a strategy that I believe was reflected in
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 35

1 yesterday's discussion of Questions 3 and 4, which was

2 to capture the pattern of atrazine in the source water

3 for each community water system based on the

4 characteristics of that particular water system, as

5 opposed to this one-size-fits-all approach that has

6 been put forth based on the series of health-based

7 considerations by the Agency.

8 Given the collective limitations of the

9 health outcome-based approach, this would seem prudent

10 and would again put the Agency in a better position to

11 take further action, should the results of ongoing

12 epidemiology studies provide more convincing evidence

13 of human health effects.

14 Thank you.

15 DR. STEVEN HEERINGA: Thank you, Dr.

16 Bucher.

17 Dr. Coupe?

18 DR. RICHARD COUPE: Good morning. I

19 don't really have much to say. I just have kind of

20 like a, not even an opinion, really, just kind of a

21 feeling. I appreciate Dr. Bucher putting all that

22 together; that was really nicely done.

23 My feeling is that I'm really kind of

24 somewhat conflicted as I sit here, as after we sit here

25 for a couple of days and we've tried to and not being
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 36

1 a toxicologist, some of it was rather mind-numbing,

2 trying to figure out, you know, does atrazine affect

3 human health in any way, shape or form at levels that

4 are environmentally significant, and it was very

5 difficult for me to see that there was such a thing.

6 Coming from an agricultural background, I know how

7 important atrazine is and I was dying to ask the

8 agricultural people some questions; but then you said,

9 you know, keep it relative to the Charge Questions.

10 But nothing they said was relevant to the Charge

11 Question.

12 But I understand where they're coming

13 from. You know, atrazine is very important to modern

14 agriculture; it's also important in urban areas. I

15 mean, we all probably use atrazine. If you use weed and

16 feed, it's got usually atrazine, may be 24d or

17 something else in it, we all use it. It seems a little

18 unfair based on what we see as the health effect right

19 now to ask the registrant to do more than they are

20 currently doing.

21 You know, we have had this debate about

22 finished water and surface water. I mean, I understand

23 the debate, and I think, you know, let's do both. That

24 seems a lot to ask. I don't want to lose the surface

25 water, because when you go to the finished water,
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 37

1 although it's good for the epidemiologists, you lose

2 kind of the tie to the environmental system.

3 And so it makes it much more difficult

4 to predict what the environmental effects, the slopes

5 and cropping and all that, had to do with how atrazine

6 gets delivered to the intake. So I would hate to see

7 us lose that, but I understand why we'd want to go with

8 finished water.

9 And then that all being said, on the

10 other hand, atrazine is used so much that it is

11 currently found in every environmental compartment that

12 we've looked at: it is in the rainfall, it is in the

13 drinking water, it is in the surface water, it's in

14 reservoirs, it's in lakes, it's in lakes and reservoirs

15 far from any point of application; it's carried by the

16 atmosphere.

17 And so it seems like we ought to, since

18 it is such a widely used one, we do need to kind of be

19 careful with it, 'cause what if it is having some

20 subtle effect? What if what Dr. Bucher said is that

21 we're already seeing the effect; it's just so broad,

22 you know, we can't see it anymore, but it's there. I

23 know that's a bit confusing; but that's just kind of

24 like where I'm conflicted at at this point.

25 I think that's all I want to say.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 38

1 DR. STEVEN HEERINGA: Thank you, Dr.

2 Coupe. Appreciate those thoughts.

3 Dr. Fenner-Crisp?

4 DR. PENELOPE FENNER-CRISP: I should

5 note that even being a toxicologist, it was mind6 numbing.

7 There was a whole lot of data there;

8 talk about supersaturation.

9 Obviously, I'm on board with what John

10 has written, because we've had a chance to work on it.

11 I wanted to add a technical comment from something

12 that's in the chapter.

13 You've offered an example here of what

14 would the numbers look like if you used that allometric

15 scaling? It was Table 8-1 on Page 128. The thing that

16 drew my attention was it was being based on a human

17 female of 60 kilograms.

18 The average human body weight for women

19 in the U.S. hasn't been that low for over 50 years. So

20 I found a National Health and NCHS report that was

21 published in 2008 that captured anthropometric

22 reference data for children and adults for the years

23 between 2003 and 2006.

24 I'll provide the citation. I don't

25 think they published the update for 2006 to 9. But in
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 39

1 this, the average body weight for the U.S. female is

2 165 pounds. So if one chooses to go forward with

3 allometric scaling in testing the possibilities in the

4 quantitative component, I would suggest you update them

5 to some reality. I found that rather startling, quite

6 frankly.

7 DR. STEVEN HEERINGA: Thank you, Dr.

8 Fenner-Crisp.

9 Dr. Greenwood?

10 DR. RICHARD GREENWOOD: Well, I, excuse

11 me, very much agree with the tone of what Dr. Bucher

12 presented, and I agree with the Agency that there's a

13 lot of scientific uncertainty in estimating these

14 critical levels of exposure in terms of critical doses,

15 concern sort of corresponding to any critical plasma

16 concentration and a critical time period of exposure as

17 sort of a duration of critical plasma concentration.

18 And they're trying to sort this out in

19 the absence of knowledge of any primary lesion or of

20 the minimum disruption that will lead to various

21 secondary lesions that we heard a lot about during this

22 week.

23 And so I understand also that they've

24 got difficulty in trying to assess human plasma areas

25 under the plasma-concentration curve in humans that
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 40

1 would correspond to particular intakes of drinking

2 water, and I will sort of come back to that at the end.

3 I found it difficult to assess the

4 relevance of the information on the GnRH antagonist

5 research, because the Mode of Action is quite

6 different.

7 Really, we have no data to provide any

8 guidance at all about what would be the minimum

9 concentration of atrazine that would be needed over a

10 period of exposure that would produce an equivalent

11 reduction in GnRH level to match the antagonism of the

12 receptor that we see with this drug.

13 It's very difficult to tie any of the

14 atrazine data into that, and it's difficult to see how

15 you would use that to identify an exposure to atrazine

16 that would produce a similar effect at that critical

17 period that was identified.

18 I think the data presented by the Agency

19 and by Syngenta demonstrate that repeated dosing, which

20 is the sort of case we'd have with human exposure via

21 drinking water, would lead to some sort of pseudo22 steady state if the dose was constant.

23 And the Syngenta data indicate that the

24 plasma profile is very much smoother when atrazine is

25 presented in food rather than in a discrete bolus by
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 41

1 oral gavage. But administration in drinking water I

2 think would probably fall somewhere between these two

3 scenarios, and it would be depend of course on the time

4 and nature of meals relative to drinking the water.

5 So although the area under the plasma

6 curve sort of represents internal exposure resulting

7 from dose in it, we need to be a little careful.

8 It is important, I think, because this

9 will provide a link between external exposure and site

10 of action, and it could be important if the dose varied

11 from day to day as it may well do in human exposure,

12 because under the regimen of regular dosing over a

13 fixed time with a constant dose, it's just the

14 calculation of the area and the curve is redundant, and

15 the plasma concentration is the only variable needed.

16 And I think it would be helpful for the

17 Agency to have some idea of whether area under the

18 curve really is important, and it's difficult to see

19 that or to conclude that on the basis of the existing

20 data.

21 If we look at the papers of Kamel and

22 Stoker that were provided in the docket, look at the

23 evidence they provided, then I think it's wholly

24 appropriate to use the area under the curve as a

25 measure of exposure, because that does give an idea of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 42

1 the opportunity of exposure of individual tissues.

2 And the work that is being done at the

3 minute to get good estimates of plasma-tissue partition

4 coefficients may overcome some of the problems

5 highlighted by the Agency in the discussion in Section

6 8 of the white paper, because it will give further

7 insight into exposures of individual tissues.

8 I think the whole business has been

9 slighted by the fact that the DACT binds to a range of

10 proteins in each tissue that's being looked at, and

11 this could be a complicating factor, depending on the

12 amount of covalent binding in particular tissues,

13 because then eventually for elimination of the bound

14 material, it will depend on the time scale of turnover

15 of proteins, and of course that can range from hours

16 for enzymes involved in metabolic regulation to weeks

17 for structural proteins; so it would depend on the

18 pattern and extent of binding.

19 Now, this sort of binding would only

20 become important if it was that that produced the

21 primary lesion. I'm not sure whether we're anywhere

22 near understanding that at all; I don't think we are.

23 But I do think I agree with the Agency

24 that the physiologically based pharmacokinetic modeling

25 approach is the ideal route if they want to take all of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 43

1 these uncertainties in account and extrapolate from

2 rodent to human.

3 But I think in the absence of that at

4 the moment, the Agency is taking the best approach

5 that's available to it, and that is to use the

6 pharmacokinetic approach that they have used.

7 But it is I think one question that

8 really should be approached, and that is to try and

9 determine whether there really is a critical area under

10 the curve -- that is, a critical exposure of a target

11 site -- that leads to a given level of suppression of

12 the LH surge, because I think at the moment if you give

13 a constant dose over the four days, it doesn't tell you

14 very much at all.

15 What you really need to do is to get the

16 same area under the curve by different dose regimens,

17 because there is a number of possibilities in there.

18 One is that they're not equally susceptible or equally

19 tolerant, if you like, on all days.

20 It could be, you know, you need 100

21 units exposure on 1 day, but only 50 on the next. Are

22 they equally susceptible over the whole of this

23 critical period that's being used? Do you need all

24 four days, or is it sufficient to do Days 2 and 3?

25 So there could be a critical exposure
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 44

1 time combined with a critical level, and it would have

2 the same nexus area under the curve; but there would be

3 a minimum to it. There would be a minimum exposure

4 time and that would be fixed, and then you may find

5 that there is a minimum concentration that you need to

6 maintain over that period.

7 But at the minute, I don't think any

8 experiments are being done, really, to determine

9 whether it's area under the curve or whether it's just

10 a critical concentration for a critical time, and the

11 two are different, because if you could give, for

12 instance, a low dose on Day 1, a very high dose on Day

13 2, a low dose on Days 2 and 3, or you could give a

14 moderate dose over the four days or any combination

15 that will give the same area under the curve, but do we

16 know whether that would actually give the same

17 biological response? And I think the answer at the

18 minute is no; it's just giving the design of the

19 experiments that are being done.

20 So I think this could be important; it

21 could have important implications for humans besides

22 just another area of uncertainty, unfortunately.

23 But given the variability in the water

24 sources and both temporally and spatially and all of

25 the added variability because you got different
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 45

1 efficiencies of water treatment plants, and even

2 identical water treatment plants could work with

3 different efficiencies --

4 I think that's something that's been

5 observed throughout the world -- it's difficult to see

6 at the minute how more refined monitoring would really

7 help to predict or catch peaks in all the individual

8 community water treatment plants in a sort of cost9 effective way.

10 And I think one of the things the Agency

11 might consider - and this again is something that Dr.

12 Bucher has raised -- is to actually look at what are

13 the likely exposures in humans, given the information

14 we know about the variability in water treatment plants

15 and in the drinking water.

16 And it might be worth just using some

17 simple model to try and estimate internal exposures

18 corresponding to some of the patterns of fluctuation in

19 water concentrations that you see. So if it's a very

20 quick peak going over a day or two days, given the

21 amount of water that a human would drink, what's the

22 implication if that's then followed by three low days?

23 Just going to some of the chemographs that are

24 available, because we've got a lot of good data to play

25 with, it then might be worthwhile to say: what would
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 46

1 happen if then we used an average concentration over

2 the period? What would be the difference in terms of

3 the total exposure that you'd calculate?

4 So at the moment I think, you know,

5 people have been concentrating on the drinking-water

6 variability but maybe not looking at the impact this

7 might have, and then trying to relate that back to some

8 of the other potential endpoints that Dr. Bucher

9 identified.

10 I know that it's very difficult to try

11 and extrapolate from rodents to humans in terms of

12 bioavailability. It's very easy to extrapolate from

13 rodents to humans in terms of absorption from the gut,

14 because they're highly correlated.

15 But the bioavailability is quite

16 different for many pharmaceuticals, for instance,

17 between rat and humans. So that would need to be

18 considered when you do any modeling. But I think Kow

19 and coworkers in 2006 actually gave quite a nice

20 discussion of, you know, how you might move between or,

21 rather, some of the difficulties in moving from rodents

22 to humans.

23 So I've tried not to repeat what's gone

24 before; but I think it's pulling some of the stuff that

25 other people have raised earlier together, and I think
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 47

1 I'll leave it there.

2 DR. STEVEN HEERINGA: Thank you very

3 much, Dr. Greenwood.

4 Dr. Bucher, did Bette leave you any

5 comments on this, or you already incorporated those?

6 DR. JOHN BUCHER: Bette left me a few

7 comments that I did incorporate into the statement that

8 I gave.

9 DR. STEVEN HEERINGA: Thank you.

10 Dr. Mumtaz?

11 DR. MOIZ MUMTAZ: Yeah. The use of any

12 chemical in the environment I believe has consequences

13 good and bad, and John has captured the Panel's views;

14 but I also was thinking about Dr. Coupe's comments.

15 And it is we go to community meetings, and we get that

16 hearing is most of the time is what we hear from the

17 public and the community.

18 So we should neither compromise public

19 health or ecological health, but not impose undue

20 restrictions on the producers of chemicals. And so we

21 try to be as realistic as possible in what we do.

22 In the report and throughout the last

23 three or four days, we have discussed only two issues;

24 one is the LH surge, and I think I've learned enough

25 about it hopefully, I can retain some of it to use in
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 48

1 the future work -- and the other one is the mixture of

2 atrazine and its three metabolites.

3 So as opportunity approaches, one of the

4 things I would like to suggest is to look at methods

5 that can be used to get an idea about the potency of

6 these various chemicals, just the metabolites -- and I

7 said this yesterday about use of computational tools --

8 to build the weight of evidence to have some idea about

9 what these metabolites' potency is and what their

10 relative concentrations would be, and we discussed this

11 in the pharmacokinetic section.

12 Earlier, we talked about children's and

13 infants' health, and that's something also we have to

14 keep in mind in terms of the sensitive populations,

15 their enzyme levels and the quality of the enzyme

16 changes, and so we have to keep that in mind when we

17 think about the toxicity of chemicals in general.

18 And so I want to move away from the LH

19 and look at other toxicities. I think EPA should look

20 into neurotoxicity, hepatotoxicity by the way, there is

21 a toxicologic profile on atrazine and it's a dated

22 document; but it still has a lot of useful information.

23 And there's a lot of data in animals on other

24 toxicities, and that's something we should look at as

25 an Agency.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 49

1 And so when we do that, if we look at

2 greatest toxicities and we are looking at using LH as

3 the driver, it would help us make the case for the

4 decision we are making rather than look at one and hang

5 everything on that one tree or branch or basket or

6 whatever the case may be.

7 So I would like EPA to look at other

8 toxicities and show that this is within a range so that

9 when we make a decision, it will be useful.

10 And so we all talked about PPK model

11 that is ideal. And Karen is sitting next to me, I

12 think, and Janice and Mel, they all have done wonderful

13 job in promoting the PPK modeling concepts.

14 But ultimately it will give us an

15 internal dose, either in a particular tissue of

16 interest or a particular organ; but we still have to

17 determine what is that organ which we're interested in,

18 and so we have to look at what I call legitimate

19 mixtures.

20 So it is great, you know, to have done

21 this research on the limited mixture, but is that a

22 legitimate mixture? Is that the actual exposure that

23 is occurring in the environment, to the public and

24 across the country?

25 As I mentioned, apart from herbicide
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 50

1 triazines, we use organophosphates in farms. There's a

2 lot of other chemicals, the farm chemicals that are

3 being used. And it will be a good idea to look at the

4 U.S. Geological Survey data and see what other

5 possibilities exist and look into the overall joint

6 toxicity of those chemicals in keeping part of this,

7 again making a realistic decision.

8 So having said all that, I don't want

9 this to come as a criticism of EPA; I think they have

10 done a wonderful job and we all, in their world, the

11 issues are quite challenging. And we are making

12 progress and as long we're making progress, I think we

13 are in good shape, and I thank you for the opportunity.

14 DR. STEVEN HEERINGA: Thank you, Dr.

15 Mumtaz.

16 Dr. Chambers?

17 DR. JANICE CHAMBERS: Dr. Mumtaz, you

18 were not at the last atrazine meeting; so you didn't

19 know that we spent several days talking about other

20 types of toxicity. We looked at neuro and immuno and

21 some of the other things, and the conclusion of the

22 Agency and the Panel was that the LH surge data was

23 really the most sensitive and most reliable database

24 for consideration.

25 DR. MOIZ MUMTAZ: But, Dr. Chambers, the
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 51

1 problem is whether this is the primary target, and how

2 do you, you know, the extrapolation from LH surge to

3 actual toxicity in rats has been somewhat established;

4 but whether that same mechanism works in humans is

5 something which we are debating.

6 So I'm not saying that this is the wrong

7 thing; I'm just telling that we should develop a maybe

8 we should put that information as a summary in this

9 report so that people like me can say, "Okay, EPA has

10 done this wonderful job" and I can retract that

11 information.

12 So it will be nice whenever you're

13 presenting something to say, "We looked at all these

14 things, and here's what we think: this is all within

15 this certain range or order of magnitude" or whatever

16 so that we can put the overall profile of the chemical

17 or its mixtures in perspective.

18 DR. STEVEN HEERINGA: I think there were

19 some good suggestions along those lines yesterday in

20 the discussion of the mammary gland.

21 Dr. Horseman?

22 DR. NELSON HORSEMAN: I just wanted to

23 say that there seems to be a sense of things maybe

24 having it both ways, so to speak.

25 So with regard to the notion of
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 52

1 neurotoxicity, we understand maybe that the previous

2 SAPs have looked at neurotoxicity per se; but at the

3 same time, a neural neuroendocrine mechanism is being

4 proposed as the underlying phenomenon that drives this

5 change in LH surge.

6 So clearly you can't say that you have

7 no neurotoxicity, but the toxicity you're using as the

8 driver for this regulatory decision has a neural

9 mechanism underlying it.

10 So I think Dr. Mumtaz's point -- and Dr.

11 McManaman has made it, and several other people have

12 made it -- that these may be, these effects that we're

13 talking mostly about at this meeting may be epi

14 phenomena of some other mechanisms that may not

15 manifest in primary toxicity in the neural system but

16 may drive metabolic and neuroendocrine changes. So I

17 just want to make that distinction.

18 DR. STEVEN HEERINGA: Dr. Legan?

19 DR. SANDRA LEGAN: So in view of the

20 discussions so far this morning, there's a lot of

21 problems with trying to get data about an adverse

22 effect of this pesticide in a rodent population and

23 compare this or extend this somehow to human doses and

24 effects and so forth.

25 And this is going to sound, this is a
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 53

1 little outside the box, but something that I think

2 ought to be just thought about and raised, so I'm

3 raising the issue is that out in the fields and out in

4 the environment where the atrazine is being, you know,

5 put on the fields, there's a lot of rodents.

6 There's field mice involved, et cetera,

7 as we all know, and we're focusing on rodents here.

8 Obviously, there are amphibians and worms, et cetera.

9 But having said that, there is no field

10 biologist here on the Panel, and field biologists

11 routinely fit birds, et cetera, including rodents, with

12 radio frequency chips. I mean, they do it with whales

13 and everything. So we know they can do this, and they

14 can track, you know, where these animals roam.

15 And they already know what the range of

16 where they live, you know, what the range is in their

17 territories. Like for a mouse, it's X -- it's probably

18 less than an acre, but who knows?

19 Okay, but they know. And it seems to me

20 you could sample some of these animals. You could also

21 establish what their range is in relation to where the

22 atrazine, what fields. And apparently, I mean, how in

23 Illinois or Indiana there's thousands of acres. These

24 animals don't probably go much outside of that area

25 where the atrazine is being used.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 54

1 So you could do survival curves on

2 animals. You could just watch until the radio

3 frequency thing stops moving. You know, I mean, for a

4 large length of time, there's got to be a way to do

5 this. You could just do survival curves to see if

6 they're surviving or not.

7 And if you trap, you can live-trap them

8 and then you have a population. If you get high

9 numbers, you can look at their reproductive systems,

10 their brains, et cetera. You can take every piece of

11 tissue and analyze it for atrazine and all its

12 metabolites.

13 I assume. We do that in lab rats, so we

14 just should this is, like I said, is outside the realm

15 of what we've been discussing to some extent; but it's

16 totally relevant if field biologists could do these

17 things and it could be used in areas where we know

18 there's the highest concentrations of atrazine have

19 been used over the last X, 50 fifty years was it in

20 some places we heard from some of the people?

21 So it's a thought, it's not a complete

22 thought; but it's right there out in nature, data. And

23 we wouldn't maybe know their exposure, but still there

24 would be a lot of information that we could glean from

25 that.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 55

1 I think that might be useful in just

2 trying to extend from rodents to humans out where the

3 pesticide is in levels where the organisms are living,

4 whatever the shape of the chemograph, et cetera, et

5 cetera.

6 DR. STEVEN HEERINGA: Thank you, Dr.

7 Legan. There is just a comment here. You know, there

8 is a substantial amount of work on pesticides and

9 herbicides and non-human health effects, environmental.

10 And for those of us who have been here for ages, it

11 seems there have been focused not only on terrestrial

12 but also amphibian and aquatic; and I think, if I

13 recall correctly, a lot of the emphasis on non-human or

14 environmental effects has shifted to aquatic.

15 There has been some work in terrestrial;

16 but, again, there's quite a body of work that's ongoing

17 of that nature, including discussion of field biology

18 and how that can play into informing exposures that are

19 non-human.

20 Dr. Mumtaz - or, Dr. Krishnan and then

21 Dr. Mumtaz.

22 DR. KANNAN KRISHNAN: I just, if you're

23 done with the designated discussants, I thought I would

24 add some comments.

25 I concur with Dr. Bucher's and Dr.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 56

1 Greenwood's analysis and comments. I just want to add

2 a couple. The first one relates to the use of the

3 allometric scaling of the rodent pharmacokinetic data

4 in relating to the duration of human exposure. Some of

5 the results were presented in Table 8-1 and associated

6 discussions.

7 I mean, I agree with those calculations

8 to inform about the duration, the way it was done;

9 however, but the use of such a calculation to derive a

10 human equivalent dose here would not seem appropriate,

11 because there are two things here when you do the

12 allometric scaling or use of the elimination half-life.

13 One is to inform about the possible duration to get to

14 a steady state, if you will.

15 That seems appropriate to me, whereas

16 using the allometric scaling to calculate the human

17 equivalent dose is questionable. I'm not convinced

18 that it's correct, because when we do the allometric

19 scaling or when we apply the body surface scaling to

20 calculate the human equivalent dose from the animal

21 dose, it's to have the same parent chemical

22 concentration in both systems.

23 So we are adjusting for the clearance so

24 that there is equal parent chemical concentration.

25 Here it's a bit tricky, because we know that it's not
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 57

1 just the parent chemical concentration at steady state

2 that's of concern; it's actually the rest of it as

3 well. So it's kind of a mix of both: the clearance of

4 the parent chemical, as well as the clearance of the

5 metabolites.

6 So you have to consider both of them

7 together. The KEL that you do separately to inform

8 about the duration, and then the body surface scaling

9 that you do separately, those have to be really

10 combined to drive it. There is some literature on it;

11 why, we can put it in the report in terms of reference.

12 Then the other comment I want to make in

13 terms of the duration considering the Mode of Action

14 and toxicity profile on water monitoring is that I am

15 thinking about based on the datasets, I mean, tox

16 datasets, it's actually from a few days to four weeks

17 which is fine, because the 28 days or a month, you

18 know, reflects the human exposure during the cycle as

19 the few days as the rat, four or maybe one or two days,

20 questions are being raised.

21 I'm more thinking of one cycle in the

22 rat versus one cycle in the human. But in

23 consideration of that, I think the combined use of the

24 steady-state consideration for pharmacokinetics as well

25 as the similar average attenuation effect across
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 58

1 durations, those two key pieces put together in my mind

2 really make a case as to whether it's really needed to

3 decrease the duration of the monitoring frequency. I

4 mean, that really makes, that really tells me; that's

5 more like a textbook example.

6 It's actually a nice case study, the way

7 the steady-state concentration is being used along with

8 the similar LH across duration; so the way it's

9 presented in Chapter 5 and the way it's brought back

10 into 8. So based on that information, I don't see a

11 compelling argument for less than a weekly monitoring.

12 That's just my thought.

13 DR. STEVEN HEERINGA: Thank you, Dr.

14 Krishnan.

15 Dr. Mumtaz, you had something?

16 DR. MOIZ MUMTAZ: I just wanted to

17 follow up on Dr. Legan's comment that once upon a time

18 when we started talking about hazardous waste sites and

19 looking at health effects, there were a lot of studies

20 done to look at the enzyme levels in wild animals,

21 particularly rats and mice, on the hazardous waste

22 sites, and some of the sites are hundreds of acres;

23 they are not a small site. And I know not far from

24 here, the protected Wildlife Refuge in Maryland, Dr.

25 Ratner, does that kind of work, so there is some
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 59

1 database there we could look into.

2 DR. STEVEN HEERINGA: Okay. At this

3 point, I think it looks like we've sort of reached the

4 coverage on Question No. 6. I'll turn to Dr. Lowit,

5 Nelson Thurman, any okay.

6 At this point in time, what I would like

7 to do is to just go around the Panel once, and I'll

8 start with Wes Stone to see whether there are any

9 additional comments that you'd like to make related to

10 these proceedings to put on the record or

11 MR. WESLEY STONE: Thank you, no, I'm

12 fine.

13 DR. STEVEN HEERINGA: Dr. Coupe?

14 DR. RICHARD COUPE: Fine also, thank

15 you.

16 DR. STEVEN HEERINGA: Dr. Lee.

17 DR. HERBERT LEE: I guess one extra

18 comment I just sort of thought of was that mostly we've

19 been thinking, looking at the question of are we

20 monitoring frequently enough, looking at the water

21 sources, and depending on duration of interest that may

22 or may not be often enough; but on the flip side,

23 outside of the growing season, are we monitoring more

24 often than we need to, is another question possibly to

25 think about. If we're not really ever finding high
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 60

1 atrazine concentrations outside the growing season, we

2 may not need to have samples every two weeks. I don't

3 think we really thought about it at all. Maybe that is

4 worth thinking about a little bit.

5 DR. STEVEN HEERINGA: Thank you, Dr.

6 Lee.

7 Dr. Akana?

8 DR. SUSAN AKANA: Is this on Question 6

9 or the entire meeting?

10 DR. STEVEN HEERINGA: The entire week.

11 DR. SUSAN AKANA: Oh, okay.

12 DR. STEVEN HEERINGA: Including Question

13 6.

14 DR. SUSAN AKANA: I woke up in the

15 middle of last night thinking about Dr. Honda's data.

16 Honest. I did, I did. And I, I've

17 been, my own personal nugget is in the HPA system; I'm

18 still struggling with how atrazine interacts with the

19 HPA system, and I was thinking again specifically of

20 his figure of c-fos in the PVN.

21 And I woke up thinking about this, and I

22 was slightly disturbed because in my own mind the

23 micrograph did not include a landmark that I was

24 looking for. So if you're in PVN and if you're talking

25 about the CRF, I was looking at medial parvocellular.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 61

1 And I didn't see the magnocenter of cells in those

2 micrographs, and it really disturbed me.

3 So then what I keyed, what it keyed me

4 to is on the flight down, I read a new paper, a 2010

5 paper. And it's from the King's College group; it's

6 Kevin O'Byrne and Stafford Lightman's group, and the

7 title of it is "Corticotropin-Releasing Factor Alters

8 the Timing of Puberty in the Female Rat".

9 And I'd like to put this into my notes,

10 because what I know of is that CRF, when you think of

11 stress, you think of the medial parvocellular or PVN.

12 But CRF actually is a distributed system; we find it in

13 many interesting areas, and it's probably an integrated

14 circuit for chronic stress.

15 But CRF, I specifically asked Dr. Honda

16 did he look at areas of the BNST and the amygdala.

17 However, CRF is also found in the MPOA.

18 And in this really interesting paper, they describe

19 what apparently is well-known in the literature, is

20 that the CRF there does have connections to the

21 gonadotropin-releasing hormone neurons; and there are

22 the appropriate receptors, the CRF R1 and R2. And in

23 this paper, if you apply CRF ICV you can delay puberty,

24 and if you give the CRF antagonist you can advance

25 puberty.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 62

1 So I think that this gives an area of

2 connection that we were sort of searching for when

3 we're talking about what are the upstream effects that

4 are modulating the decrease in LH amplitude. So I

5 think there might be more here to work with than I was

6 originally groping for.

7 Thank you.

8 So the paper, I would like to put in my

9 comments.

10 DR. STEVEN HEERINGA: Thank you; and

11 we're sorry we disturbed your REM sleep, but I think

12 we've all been there. So not exactly on the

13 toxicology, but

14 Dr. Fenner-Crisp?

15 DR. PENELOPE FENNER-CRISP: I can't top

16 that, so I'm through.

17 DR. STEVEN HEERINGA: Dr. Gold.

18 DR. ELLEN GOLD: I actually did have one

19 comment. I like Dr. Legan's thinking-outside-the-box

20 approach and I wanted to extend it to thinking about

21 human studies outside the box, because I think a lot of

22 the agricultural health studies, for example, rightly

23 focuses on the series of applicators; but they don't

24 include a lot of women, they aren't very diverse, as I

25 mentioned in my comments.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 63

1 And it actually is possible to study

2 farm workers, for example. And there are thousands of

3 farm workers, for example, working in cornfields, for

4 example. And we've actually been able to do studies of

5 menstrual-cycle characteristics and collect urine

6 samples in such women.

7 So I would encourage in the long-term

8 view to think again outside the human-study box that

9 they seem to be in and extend the research beyond it,

10 actually look at real-life populations that may have

11 exposure that can be documented.

12 DR. STEVEN HEERINGA: Thank you, Dr.

13 Gold.

14 Dr. Harris?

15 DR. SHELLY HARRIS: And I'm going to

16 bring us back to water monitoring. I've been thinking

17 about this for the last few days, and there's an

18 assumption that's being made and I keep hearing around

19 the table that the epidemiologists want measures in

20 finished drinking water.

21 And we've been having a few side

22 conversations about that and I say, "Yes, we would like

23 measures in finished water over top of those in

24 environment"; but I also say, "We would like both,

25 ideally".
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 64

1 But realistically what can we do with

2 those measures in finished drinking water, and we could

3 certainly use those to improve the ecologic studies;

4 but we've really agreed that those are not particularly

5 useful for risk assessment. So do we want to spend a

6 lot of time and effort improving the group-level

7 exposure assessment for ecologic studies? And my short

8 answer would be, "No, that wouldn't be a priority for

9 me".

10 So what can we do with these low-level

11 measures of atrazine and metabolites in drinking water

12 supplies, and if we're going to conduct very good

13 studies, well, we would look at those at the community

14 level and then ideally at the top level, and then we

15 would take additional, collect additional data on

16 whether people filter their water or not; how much

17 bottled water they drink; how much time they spend away

18 traveling away from home.

19 So how much community water did we drink

20 this week; the consumption in canned products such as

21 tomatoes, another major source of water consumption in

22 humans; and the list goes on.

23 So when we design those kinds of

24 exposure-assessment studies to exposure to water or

25 your source of water, these things all become very
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 65

1 important. So what's at the community level that's

2 measured from the treatment facility may have very,

3 very little relation at all to what the human is

4 actually exposed to.

5 And I might suggest a correlation of,

6 you know, 20 percent, if we're lucky, it might 70

7 percent. I'm not sure. We could look at enhanced data

8 and those types of data in relation to some of these

9 finished and unfinished measures and get a feel for

10 that. And we could also conduct some really decent

11 biomonitoring studies. And I think that some of that

12 should be done.

13 But I think before really significant

14 resources go into looking at finished-water supplies

15 where you've got, I'm assuming, a lot of non-tapped

16 that we should look at whether they're going to be

17 relevant for estimating low-level human exposures. We

18 have very little ideas of how frequently we need to do

19 that, the windows of susceptibility and that kind of

20 thing.

21 So that's sort of my wrap-up on my

22 thoughts about that, thanks.

23 DR. STEVEN HEERINGA: Thank you, Dr.

24 Harris.

25 Dr. Bailar.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 66

1 DR. JOHN BAILAR: Nothing to add.

2 DR. STEVEN HEERINGA: Dr. LeBlanc?

3 DR. GERALD LEBLANC: Nothing.

4 DR. STEVEN HEERINGA: We'll go to Dr.

5 Legan?

6 DR. SANDRA LEGAN: No further comments.

7 DR. STEVEN HEERINGA: Okay. Dr.

8 Delclos?

9 DR. BARRY DELCLOS: I'm fine.

10 DR. STEVEN HEERINGA: Dr. Roby?

11 DR. KATHERINE ROBY: I just want to

12 quickly comment that I think the discussants on this

13 final point really did a great job of summing up both

14 what we understand and what we don't yet understand.

15 And with respect to the LH, we don't yet really

16 understand what the critical window is and I think that

17 is the bottom line, and whether new regulation or

18 tighter regulation needs to be imposed or suggested is

19 not sure at this point, not clear.

20 DR. STEVEN HEERINGA: Dr. McManaman?

21 DR. JAMES MCMANAMAN: Yeah, I have one

22 last comment.

23 Dr. Bailar mentioned that we should be

24 focusing on appropriate doses or physiological doses

25 and physiological outcomes.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 67

1 Since we don't know the physiological

2 outcomes yet, I emphasize that we need more study

3 because I think we may be looking at the LH and it may

4 not be the appropriate physiological outcome, because

5 physiological doses, the concentrations that we're

6 looking at as we're focusing on atrazine not as

7 metabolites; metabolites have a lot longer life than

8 the atrazine itself.

9 So again, I think that we should be

10 focusing on, as Dr. Bailar suggested, on the

11 appropriate compounds and we don't know what those

12 appropriate compounds are yet.

13 DR. STEVEN HEERINGA: Dr. Horseman?

14 DR. NELSON HORSEMAN: I have nothing to

15 add; just thank the EPA for the quality of material

16 that we were given, and the Panel for everything I've

17 learned, and Steve for doing such a good job of keeping

18 the meeting on task.

19 DR. STEVEN HEERINGA: Dr. Mumtaz.

20 DR. MOIZ MUMTAZ: I agree with Dr. Lee

21 and Dr. Krishnan, based on the current knowledge that

22 we probably need not monitor more often than we are

23 currently monitoring. But while monitoring for

24 atrazine, I would like to see the analysis extended to

25 other chemicals present in samples so that we have a
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 68

1 better profile of the mixtures of atrazine, of course,

2 within the environment.

3 Also that would help us educate people

4 in terms of bio-availability of what is there. Always

5 when I go to the meetings when I'm in a tight spot

6 trying to explain the Committee, I use the zoo example:

7 that we go to the zoo, we go with our parents, our

8 children and everybody and have fun. There's no

9 problem, even though there are dangerous animals there.

10 But we know we'll not get exposed to unless it's

11 California or...

12 The same thing is true with chemicals:

13 just because they're there, we don't have to really

14 worry about them. What we need to do is see if they

15 are presenting in a completed exposure pathway, which

16 is from the source to the sensitive population.

17 So when we are looking at these samples,

18 if we do a better analysis, I know it will add to the

19 money; but instead of increasing the frequency, do a

20 total job with the sample I think will give a better

21 categorization of risk.

22 The same argument I do with CDC all the

23 time that is in this data they have the 160 chemicals

24 present in my body; but I want to know which of those

25 are present in a given sample so that we can figure out
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 69

1 what are the common mixes where it's potent. And it's

2 a bigger problem than I think, but I still want to make

3 that point.

4 Thank you very much. I enjoyed the

5 participation on this Panel.

6 DR. STEVEN HEERINGA: Thank you, Dr.

7 Mumtaz.

8 Dr. Krishnan?

9 DR. KANNAN KRISHNAN: You woke up in the

10 middle of the night, but I couldn't sleep.

11 I had to talk to the endocrinologists

12 before I could go to bed.

13 You know what I mean? Who wants to talk

14 about the BMR or the benchmark response that we talked

15 about the last afternoon? So I'll just make a couple

16 of comments in closing.

17 And the one paper clearly makes a case

18 for the use of the data on the attenuation of LH,

19 despite the caveats we heard. I don't see it as a

20 NOAEL or NOAEL as the white paper sees it. Rather, I

21 see it as a no observable adverse perturbation level,

22 NOAPL.

23 That's how I present the NAS work to my

24 students, because it's basically no observable adverse

25 perturbation level. It's not a no-effect level,
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 70

1 because, you know, you can really get to the

2 terminologies.

3 But in any case, the Agency here used a

4 one deviation, or standard deviation, from the control.

5 That's how the BMR was defined, and we had some

6 discussions around it.

7 I know it's the Agency policy to use 1SD

8 when a biologically significant deviation of change

9 cannot be defined or clearly defined, and I think the

10 document brings that out. But I still continue to ask

11 myself whether some of the additional data could be

12 analyzed to characterize the spread in the controls at

13 18 hours --

14 I underlined even in my notebook 18

15 hours -- maybe more than one study to provide further

16 support to the use of 1SD, or better define or provide

17 better support to the BMR, because especially when

18 we're using perturbation levels to define the benchmark

19 doses, I think it is important to analyze it in that

20 sense. So I just needed that.

21 DR. STEVEN HEERINGA: Thank you, Dr.

22 Krishnan.

23 Dr. Greenwood?

24 DR. RICHARD GREENWOOD: I think I've

25 said more than enough, thank you.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 71

1 DR. STEVEN HEERINGA: We appreciated

2 your comments.

3 Dr. Schlenk.

4 DR. DANIEL SCHLENK: Nothing to add.

5 DR. STEVEN HEERINGA: Dr. Portier?

6 DR. KENNETH PORTIER: Nothing.

7 DR. STEVEN HEERINGA: Dr. Chambers?

8 DR. JANICE CHAMBERS: Nothing to add.

9 DR. STEVEN HEERINGA: Dr. Pope?

10 Dr. Bucher, you have to say something

11 since this is probably your last 10 minutes on the

12 Panel.

13 DR. JOHN BUCHER: I will. I want to

14 thank the Agency. This four years on this Panel has

15 been very entertaining in many cases and very

16 educational, and I appreciate the opportunity to serve.

17 I compliment the Agency with the

18 atrazine review as tackling one of the most difficult

19 scientific, social and political topics that you could

20 take on. Six meetings may be, five meetings may be too

21 many; but, you know, that's up to you.

22 And finally I want to thank Steve and

23 the rest of the permanent Panel members for a very

24 enjoyable couple of years, and thanks very much to Joe

25 Bailey for reminding me that when he asks which
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 72

1 questions you want to respond to, you really should

2 respond to him instead of just getting stuck with the

3 last one as I have been, but, thank you very much.

4 DR. STEVEN HEERINGA: Well, thank you

5 very much, John. As we said in our little ceremony the

6 other day that I think all of us greatly appreciate

7 your participation on this Panel, and I know personally

8 I've turned to your expertise and your sort of

9 knowledge of not only the field but also all of the

10 players in the field. It's very, very, been very, very

11 helpful and beneficial to this Panel, and I wish you

12 all the best.

13 DR. JOHN BUCHER: Thank you very much.

14 DR. STEVEN HEERINGA: Okay. At this

15 point, I'm going to turn back to Dr. Lowit, Dr. Levine

16 for any .

17 DR. ANNA LOWIT: Now we want to express

18 our appreciation to absolutely every single one of you.

19 As you can see, we have a difficult task and some very

20 difficult issues, and I'm amazed every time I attend

21 one of these meetings how insightful a group of

22 scientists can be when you get together; there's always

23 a synergy around it, and it's quite an amazing process.

24 This one is no different. I appreciate

25 that it takes an enormous amount of effort out of your
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 73

1 personal life and your professional life to read almost

2 700 pages of material, and thousands if you looked at

3 actually some of the raw studies. So this, we really

4 truly appreciate it, and it helps the process and helps

5 the science, and we're going to continue to inch our

6 way one step at a time forward.

7 Thank you to Dr. Bucher for your

8 service.

9 Dr. Joe Bailey and Laura Bailey and the

10 entire CP staff, another phenomenal meeting. Thank you

11 so much for your effort.

12 My personal thanks to the team, and Dr.

13 Mendez for sharing my appreciation for the team. It's

14 an amazing group of people who have done some also

15 another situation you get synergy of dedicated talented

16 people, and it's pretty amazing what you can do.

17 With that, I think that's all.

18 DR. STEVEN HEERINGA: Well, thank you

19 very much, Dr. Lowit. And I want to express my

20 appreciation to all the members of the Panel. It's

21 obviously a busy time of year for many of us, and to be

22 able to gather here with so much expertise, as I say, I

23 learn a tremendous amount every time I attend one of

24 these meetings and I appreciate the expertise and the

25 way that you were able to focus it during this meeting.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 74

1 So the EPA Staff, again, just to

2 reiterate the other comments from Panel members, the

3 quality of the materials and the way it was organized,

4 the sheer volume of material, I know we often get it on

5 a short order; but you have to make it as current as

6 you possibly can, and as we've seen from your work and

7 the public commenters' work, people are working up

8 right to the last moment often on many of these

9 meetings.

10 And so that's all very much appreciated

11 in the way that you presented it and organized it for

12 this Panel, I'll just say thank you.

13 At this point, I turn to our Designated

14 Federal Official, Joe Bailey, for comments on what will

15 happen after this meeting is closed.

16 DR. JOSEPH BAILEY: Thanks, Dr.

17 Heeringa.

18 I want to return some thanks back to

19 Anna Lowit and her colleagues on bearing with me trying

20 to plan the meeting and get everything pulled together.

21 I think it turned out very successful.

22 I want to thank the public commenters

23 for bringing forward their helpful, informative

24 information.

25 I want to thank Dr. Portier and Dr.
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 75

1 Heeringa for chairing the meeting and keeping us on

2 track and actually getting us ahead of time. I thought

3 we were going to be here 'til mid-afternoon, at least.

4 And last but not least, I certainly want

5 to thank each of the Panel members for working with me

6 and agreeing to serve on the Panel. I really

7 appreciate it, I think a lot of good information has

8 come forward for the Agency to consider.

9 I will wish Dr. Bucher the best of luck

10 with his post-SAP endeavors.

11 And the Panel, I'll be working with you

12 over the next couple of months to get the meeting

13 minutes finalized, and those will be done within the

14 usual 90-day period. Once they're completed, they'll

15 be available on the website and in the public docket.

16 So, thank you all.

17 SPEAKER: Timeline for everybody to get

18 the first draft?

19 DR. JOSEPH BAILEY: Well

20 DR. STEVEN HEERINGA: We'll have a break

21 in our meeting in just a moment.

22 SPEAKER: Okay. I didn't want to

23 forget.

24 DR. STEVEN HEERINGA: Again, all the

25 materials that were presented before the Panel in hard
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 76

1 copy or electronic should be available on the docket

2 within a reasonable period of time here.

3 And again, thank you to everybody who

4 participated in this process, the EPA Scientific Staff

5 and public commenters who worked with us on Wednesday

6 and everything that they contributed to this process.

7 And with that, I'll call this meeting to a close.

8 Permanent Panel or Panel members, if we

9 could meet in our breakout room to plan the

10 organization of our first draft and the timeline for

11 that.

12 So, thank you everybody; have a good

13 day.

14 (WHEREUPON, the meeting was concluded 10:17 a.m.)

15

16

17

18

19

20

21

22

23

24

25
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 77

1 CAPTION

2

3 The foregoing matter was taken on the date, and at the

4 time and place set out on the Title page hereof.

5

6 It was requested that the matter be taken by the

7 reporter and that the same be reduced to typewritten

8 form.

9

10 Further, as relates to depositions, it was agreed by

11 and between counsel and the parties that the reading

12 and signing of the transcript, be and the same is

13 hereby waived.

14

15

16

17

18

19

20

21

22

23

24

25
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 78

1 CERTIFICATE OF REPORTER

2 COMMONWEALTH OF VIRGINIA

3 AT LARGE:

4 I do hereby certify that the witness in the foregoing

5 transcript was taken on the date, and at the time and

6 place set out on the Title page hereof by me after

7 first being duly sworn to testify the truth, the whole

8 truth, and nothing but the truth; and that the said

9 matter was recorded stenographically and mechanically

10 by me and then reduced to typewritten form under my

11 direction, and constitutes a true record of the

12 transcript as taken, all to the best of my skill and

13 ability.

14 I further certify that the inspection, reading and

15 signing of said deposition were waived by counsel for

16 the respective parties and by the witness.

17 I certify that I am not a relative or employee of

18 either counsel, and that I am in no way interested

19 financially, directly or indirectly, in this action.

20

21

22

23

24 MARK REIF, COURT REPORTER / NOTARY

25 SUBMITTED ON SEPTEMBER 17, 2010
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 79

1

1 10:5 43:21

44:12

1:3 24:10

10 71:11

10:17 76:14

100 8:17 8:20

23:13 24:4 43:20

100milligram 23:9

10x 17:2 18:1

12.5 8:25

12:00 4:21 29:11

128 38:15

160 68:23

165 39:2

18 70:13 70:14

1SD 70:7 70:16

2

2 12:10 23:1 23:3

43:24 44:13

44:13

2.75 24:3

20 65:6

2003 38:23

2006 38:23

38:25 46:19

2007 9:11 10:9

11:16 12:17

2008 38:21

2010 2:3 23:2

61:4

24d 36:16

28 57:17

3

3 12:11 35:1

43:24 44:13

4

4 2:17 2:20 25:25

26:2 35:1

5

5 5:4 6:6 6:20

20:25 58:9

50 8:16 9:4 23:10

23:13 38:19

43:21 54:19

6

6 29:15 29:17

32:9 59:4 60:8

60:13

60 27:23 38:17

7

70 65:6

700 73:2

8

8 30:10 42:6

58:10

8.0 29:19

8-1 38:15 56:5

9

9 38:25

90-day 7:6 75:14

A

a.m 76:14

ability 34:18

able 4:23 63:4

73:22 73:25

absence 39:19

43:3

absolutely 72:18

absorbed 28:18

absorption 46:13

accident 5:25

accidental 26:23

accordingly 3:25

account 22:18

32:1 43:1

accumulate 16:9

33:24

accumulation 12:8

13:13

accurate 27:10

acknowledge 30:7

acquired 17:20

acre 53:18

acres 53:23 58:22

across 6:12

6:23 7:12 8:7

11:3 25:12 49:24

57:25 58:8

action 20:4 32:16

34:4 35:11

40:5 41:10 57:13

activated 34:19

activatedcarbon 27:25

actual 27:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 80

49:22 51:3

actually 16:11

24:3 27:2

28:16 44:16

45:12 46:19 57:2

57:16 58:6 61:12

62:18 63:1

63:4 63:10

65:4 73:3 75:2

add 2:22 3:2

3:7 3:9 26:5

38:11 55:24 56:1

66:1 67:15 68:18

71:4 71:8

added 11:12 44:25

addition 16:22

34:17

additional 2:19

2:21 19:14 20:24

25:14 29:4

29:6 29:22

59:9 64:15 64:15

70:11

addressed 19:22

addresses 30:11

adequate 32:25

adipose 21:13

adjusted 30:22

adjusting 56:23

administered

21:24

administration

41:1

adult 17:13 17:15

17:20 18:6

18:9 18:11 23:17

adults 7:9 38:22

advance 61:24

adverse 20:1 20:6

31:22 32:6 52:21

69:21 69:24

adversity 31:24

Advisory 2:1 2:6

affect 34:11

34:18 36:2

affected 8:23

affecting 21:25

afternoon 2:16

69:15

against 17:16

33:14

age 20:3 20:18

Agency 6:6 6:7

17:14 17:19

23:15 30:24 31:4

32:18 33:19 35:7

35:10 39:12

40:18 41:17 42:5

42:23 43:4 45:10

48:25 50:22 70:3

70:7 71:14 71:17

75:8

Agency's 29:18

agenda 3:11

agents 32:3

ages 55:10

agreed 15:23 64:4

agreeing 75:6

agricultural 33:7

33:20 36:6

36:8 62:22

agriculture 36:14

ahead 3:12 75:2

aim 5:1

Akana 60:7 60:8

60:11 60:14

al 7:23 9:11

12:17 13:5 13:18

alkyl 9:18 10:1

allometric

38:14 39:3

56:3 56:12 56:16

56:18

alone 13:18 13:19

already 10:19

16:23 37:21 47:5

53:15

alteration 11:9

alternative 29:22

32:10 33:10

Alters 61:7

am 57:14

amazed 72:20

amazing 72:23

73:14 73:16

amount 28:11

28:18 28:18

34:21 42:12

45:21 55:8 72:25

73:23

amphibian 55:12

amphibians 53:8

amplitude 62:4

amygdala 61:16

analysis 6:8

10:20 19:14
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 81

29:18 29:25 56:1

67:24 68:18

analyze 54:11

70:19

analyzed 70:12

and/or 13:11

19:22

animal 28:8 30:15

31:20 33:15

56:20

animals 22:13

30:18 48:23

53:14 53:20

53:24 54:2 58:20

68:9

Anna 5:12 17:14

25:22 29:16

29:17 72:17

74:19

answer 18:17

44:17 64:8

antagonism 40:11

antagonist 40:4

61:24

anthropometric

38:21

anticipate 4:20

anymore 37:22

anyone 26:5

anything 3:7

3:9 8:6 26:1

26:5

anywhere 42:21

apart 49:25

apparently

12:25 13:13

53:22 61:19

appealing 18:13

appeared 8:6 28:1

appears 9:16 9:17

13:2 32:7

application 37:15

applications 33:8

applicators 62:23

apply 56:19 61:23

appreciate

35:21 38:2 71:16

72:6 72:24

73:4 73:24 75:7

appreciated

71:1 74:10

appreciation

72:18 73:13

73:20

approach 7:2

33:10 35:5

35:9 42:25

43:4 43:6 62:20

approached 43:8

approaches

29:22 32:10 48:3

approaching 32:11

appropriate

15:9 17:6 27:2

41:24 56:10

56:15 61:22

66:24 67:4 67:11

67:12

appropriately

32:18

aquatic 55:12

55:14

area 41:5 41:14

41:17 41:24 43:9

43:16 44:2

44:9 44:15 44:22

53:24 62:1

areas 30:25 36:14

39:24 54:17

61:13 61:16

aren't 62:24

argument 26:14

58:11 68:22

artifact 16:2

aside 12:17 26:25

aspect 6:25 16:25

22:4

aspects 19:13

19:22 21:17

assess 39:24 40:3

assessed 25:13

assessing 6:13

22:19

assessment

13:24 15:25 17:3

20:16 21:16 22:9

22:23 27:10

32:21 64:5 64:7

associated 19:6

20:12 56:5

assume 11:5

16:8 54:13

assumes 32:22

assuming 65:15

assumption 63:18

assumptions 31:12
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 82

31:15

assure 32:25

atmosphere 37:16

atrazine 2:8

4:4 5:12 8:6 8:7

8:13 9:11 10:6

11:18 11:20 12:9

13:2 13:10 13:13

19:11 19:20

21:23 23:5

23:9 23:10 23:16

23:20 24:2 26:21

28:4 28:9

28:11 28:13

28:13 30:10

30:19 32:17

32:24 33:1

33:4 33:7

33:10 34:5 34:12

34:19 34:21 35:2

36:2 36:7

36:13 36:15

36:16 37:5 37:10

40:9 40:14 40:15

40:24 48:2 48:21

50:18 53:4 53:22

53:25 54:11

54:18 60:1 60:18

64:11 67:6

67:8 67:24

68:1 71:18

atrazine's 6:12

7:20 25:12

atrazinetreated 22:13

attend 72:20

73:23

attention 38:16

attenuation 57:25

69:18

available 4:12

43:5 45:24 75:15

76:1

average 7:6 38:18

39:1 46:1 57:25

away 48:18

64:17 64:18

awful 14:7

B

background 36:6

bad 47:13

Bailar 24:22

24:23 25:8 65:25

66:1 66:23 67:10

Bailey 3:5 3:8

3:15 4:9 4:15

71:25 73:9

73:9 74:14 74:16

75:19

BARRY 66:9

base 34:12

based 19:14

20:3 30:23

31:6 33:2 35:3

35:6 36:18 38:16

42:24 57:15

58:10 67:21

basically 6:20

25:25 69:24

basing 34:2

basis 31:25 41:19

basket 49:5

bearing 74:19

become 42:20

64:25

bed 69:12

begin 3:7

believe 3:22

27:14 34:25

47:12

benchmark 20:8

20:13 30:13

30:14 69:14

70:18

beneficial 72:11

besides 44:21

best 19:4 34:3

43:4 72:12 75:9

Bette 19:2

20:21 47:4 47:6

better 7:2 7:5

7:7 7:8 10:22

14:6 33:20 35:10

68:1 68:18 68:20

70:16 70:17

beyond 63:9

bigger 69:2

binding 42:12

42:18 42:19

binds 42:9

bioavailability

46:12 46:15

bioavailability

68:4

biological 24:7

44:17

biologically 70:8

biologist 53:10
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 83

biologists

53:10 54:16

biology 55:17

biomonitoring

65:11

birds 53:11

bit 3:12 3:23

5:17 7:13 9:9

12:23 15:20

26:14 37:23

56:25 60:4

block 32:3

BMR 69:14 70:5

70:17

BNST 61:16

board 38:9

body 23:11

23:12 38:18 39:1

55:16 56:19 57:8

68:24

bolus 14:24 40:25

bottled 64:17

bottom 66:17

bound 33:15 42:13

boundaries 32:12

box 53:1 62:21

63:8

brains 54:10

branch 49:5

break 5:13 75:20

breakout 76:9

breaks 29:11

brief 28:7

briefly 3:5

bring 2:24

11:24 11:25 26:7

63:16

bringing 74:23

brings 70:10

broad 37:21

broader 32:2

brought 58:9

Bucher 29:25 30:2

35:16 35:21

37:20 39:11

45:12 46:8

47:4 47:6

71:10 71:13

72:13 73:7 75:9

Bucher's 55:25

build 48:8

business 42:8

busy 73:21

C

C14 11:18 21:10

calculate 46:3

56:16 56:20

calculated 33:14

calculation 41:14

56:9

calculations 56:7

California 68:11

canned 64:20

capture 35:2

captured 33:1

38:21 47:13

capturing 10:13

19:16

carbon 28:3 34:20

careful 37:19

41:7

Carey 6:19 7:19

12:2 14:5

15:20 19:1 21:11

27:6 27:13

carried 37:15

case 3:5 17:24

40:20 49:3

49:6 58:2 58:6

69:17 70:3

cases 71:15

catch 45:7

categorization

68:21

causality 32:19

cause 37:19

caveats 69:19

CDC 68:22

cells 61:1

central 12:6

ceremony 72:5

certain 7:8 11:10

51:15

certainly 14:4

14:10 15:9 15:15

15:24 16:3 23:17

26:7 33:13

64:3 75:4

cetera 34:14 53:6

53:8 53:11 54:10

55:4 55:5

c-fos 60:20

Chair 2:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 84

chairing 75:1

challenging 50:11

Chambers 14:2

14:3 16:19

21:3 25:17

27:4 27:5

50:16 50:17

50:25 71:7 71:8

chance 26:7

29:9 38:10

change 11:2 23:11

23:11 52:5 70:8

changes 10:4

48:16 52:16

chapter 38:12

58:9

characteristics

34:13 35:4 63:5

characterization

20:3 20:9

characterize

70:12

characterized

32:15

charge 2:17

2:20 5:4 20:25

23:18 26:10 27:2

36:9 36:10

charged 21:5

chart 27:21 27:22

27:23

check 30:5

chemical 47:12

51:16 56:21

56:24 57:1 57:4

chemicals 27:19

47:20 48:6 48:17

50:2 50:2 50:6

67:25 68:12

68:23

chemograph 55:4

chemographs 45:23

child 15:12

children 6:14

19:25 25:13

38:22 68:8

children's 48:12

chips 53:12

chooses 39:2

chronic 61:14

circuit 61:14

citation 38:24

cited 13:5

clarifications

27:19

clarify 21:9 24:1

clear 66:19

clearance 56:23

57:3 57:4

clear-cut 13:11

clearly 5:11

26:15 27:25 33:2

52:6 69:17 70:9

close 26:6 76:7

closed 3:25 74:15

closing 69:16

Coder 23:1 23:2

coefficient 24:8

coefficients 42:4

colleagues 74:19

collect 63:5

64:15

collected 31:5

31:15

collection 9:5

collective 35:8

College 61:5

combination 44:14

combined 8:18

44:1 57:10 57:23

comes 2:24 18:11

coming 28:16 36:6

36:12

commended 32:4

comment 3:16 3:24

6:6 16:22

18:14 29:18

38:11 55:7 57:12

58:17 59:18

62:19 66:12

66:22

commenters 74:7

74:22 76:5

comments 2:19 6:9

18:25 20:21

20:24 25:14

25:18 29:7

29:9 29:21

30:6 30:8 47:5

47:7 47:14 55:24

56:1 59:9 62:9

62:25 66:6 69:16

71:2 74:2 74:14

Committee 68:6

common 69:1
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 85

community 27:18

34:7 34:11 34:14

35:3 45:8

47:15 47:17

64:13 64:19 65:1

comp...atrazine

22:14

comparative 27:21

30:16

compare 17:13

23:6 52:23

compared 33:13

comparing 18:9

27:23

comparisons 17:16

compartment 37:11

compelling 58:11

complete 54:21

completed 18:15

68:15 75:14

complex 10:15

22:14

complicated 12:18

complicating

42:11

compliment 71:17

component 12:25

13:1 17:4 17:5

17:11 18:1 39:4

components

26:20 26:22

compound 21:4

compounds 16:9

67:11 67:12

comprehensive

33:3

compromise 47:18

computational

48:7

computer 23:2

concentrating

46:5

concentration

39:16 39:17 40:9

41:15 44:5 44:10

46:1 56:22 56:24

57:1 58:7

concentrations

13:6 16:7

30:20 33:5

34:5 45:19 48:10

54:18 60:1 67:5

concept 30:21

concepts 49:13

concern 13:14

15:23 21:20 22:7

24:25 24:25 25:5

25:5 30:20 32:13

39:15 57:2

concerning 10:18

conclude 41:19

concluded 32:18

76:14

conclusion 50:21

conclusions 29:19

concur 55:25

conduct 15:24

64:12 65:10

confidence

20:12 20:13

conflicted

35:24 37:24

confusing 37:23

confusion 7:22

connection 62:2

connections 61:20

consensus 7:20

consequences

47:12

conservatism

20:11

conservative

33:16

consider 6:7

7:1 23:15

34:25 45:11 57:6

75:8

consideration

6:10 19:3 19:5

19:19 25:10

31:23 33:25

50:24 57:23

57:24

considerations

30:19 35:7

considered

19:13 20:14

20:17 22:8

25:6 31:7 46:18

considering 57:13

consistent 19:8

constant 40:22

41:13 43:13

consumption

33:7 64:20 64:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 86

contained 29:19

contaminant

9:17 13:3

contaminants

10:14

content 28:9

28:12

contents 27:17

context 19:8

19:22

continue 33:24

70:10 73:5

contribute 31:13

contributed 76:6

contributions

20:25 24:21 30:7

control 10:24

23:7 33:8 70:4

controls 70:12

conventional

26:19 26:22

conversations

63:22

convinced 56:17

convincing 35:12

Cooper 11:16

copy 4:14 76:1

cornfield 27:8

cornfields 63:3

correct 56:18

correctly 55:13

correlated 46:14

correlation 65:5

correspond 40:1

corresponding

39:15 45:18

CorticotropinReleasing 61:7

cost 45:8

country 49:24

Coupe 3:2 30:5

35:17 35:18 38:2

59:13 59:14

Coupe's 47:14

couple 6:25 9:3

14:4 14:11 27:15

35:25 56:2 69:15

71:24 75:12

course 2:23

34:3 41:3

42:15 68:1

covalent 42:12

coverage 59:4

covered 25:25

26:1

coworkers 10:9

46:19

CP 73:10

created 9:14

CRF 60:25 61:10

61:12 61:15

61:17 61:20

61:22 61:23

61:24

Crisp 25:18

critical 19:21

20:2 29:20 31:14

34:1 39:14 39:14

39:15 39:16

39:17 40:16 43:9

43:10 43:23

43:25 44:1 44:10

44:10 66:16

criticism 50:9

cropping 34:13

37:5

current 30:21

32:14 32:24

67:21 74:5

currently 7:5

7:23 31:8

36:20 37:11

67:23

curve 22:2 22:6

22:8 22:11 22:16

39:25 41:6 41:14

41:18 41:24

43:10 43:16 44:2

44:9 44:15

curves 54:1 54:5

cycle 57:18 57:21

57:22

D

DACT 42:9

dam 8:8 12:10

21:10 22:17 23:7

dams 23:5 23:21

23:21 23:22

dangerous 68:9

DANIEL 24:1 71:4

data 10:25 14:8

15:1 15:5 15:8

15:13 17:6

17:6 17:15

18:4 18:4
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 87

19:24 20:14

20:16 21:10

23:19 24:11 25:4

29:22 31:2

31:3 31:20

32:2 32:25 33:15

38:7 38:22

40:7 40:14 40:18

40:23 41:20

45:24 48:23 50:4

50:22 52:21

54:22 56:3 60:15

64:15 65:7

65:8 68:23 69:18

70:11

database 19:10

19:23 32:2 32:14

50:23 59:1

datasets 33:3

57:15 57:16

date 10:18

dated 48:21

day 2:6 3:10 4:21

5:2 8:17 8:20

9:1 9:4 10:6

17:14 28:10

41:11 41:11

43:21 44:12

44:12 45:20 72:6

76:13

days 27:15 31:6

34:2 35:25 43:13

43:19 43:24

43:24 44:13

44:14 45:20

45:22 47:23

50:19 57:16

57:17 57:19

57:19 63:17

dealing 14:13

dealt 15:25

debate 36:21

36:23

debating 51:5

decent 65:10

decision 17:2

18:1 49:4 49:9

50:7 52:8

decision-making

17:1

decrease 58:3

62:4

dedicated 18:2

73:15

define 70:16

70:18

defined 70:5 70:9

70:9

degree 20:11

delay 61:23

Delclos 66:8 66:9

de-lipidated

21:14

delivered 37:6

delivering 14:20

delivery 14:20

34:12

demonstrate 40:19

departure 7:24

11:8

depend 41:3 42:14

42:17

dependent 34:8

depending 27:18

42:11 59:21

Deputy 5:7

derive 56:9

describe 17:8

61:18

describing 17:15

design 44:18

64:23

designated 3:6

55:23 74:13

designed 26:20

26:24

despite 69:19

determination

19:19

determine 11:7

14:15 16:2 16:16

43:9 44:8 49:17

determined 31:4

detour 5:14

develop 15:8 51:7

developing 7:9

12:12 12:13

13:15 14:6 15:10

15:11

development

8:15 9:8 10:4

10:25 12:22

developmental

7:21 8:10 8:24

11:9

deviation 70:4

70:4 70:8

dietary 8:2 28:13
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 88

28:25

difference 46:2

differences 8:3

17:25 18:19

27:15

different 27:16

27:19 27:24

28:23 33:17 40:6

43:16 44:11

44:25 45:3 46:16

72:24

differential 18:8

difficult 8:2

11:4 36:5 37:3

40:3 40:13 40:14

41:18 45:5 46:10

71:18 72:19

72:20

difficulties

46:21

difficulty 39:24

direct 18:10

directly 21:23

21:24 34:15

Director 5:8

discrete 40:25

discussant 6:17

discussants 55:23

66:12

discussed 34:10

47:23 48:10

discussing 54:15

discussion 3:1

17:19 26:9

35:1 42:5

46:20 51:20

55:17

discussions

3:17 4:25

29:14 52:20 56:6

70:6

dismissed 22:22

disruption 39:20

distinction 52:17

distributed 61:12

distribution

11:17 21:10

disturbed 60:22

61:2 62:11

diverse 62:24

Division 5:8

docket 4:1 4:13

41:22 75:15 76:1

document 30:9

48:22 70:10

documented 63:11

documents 3:18

done 16:16

17:21 30:24

33:22 35:22 42:2

44:8 44:19 49:12

49:20 50:10

51:10 55:23 56:8

58:20 65:12

73:14 75:13

dosages 11:3

dose 8:24 9:3 9:4

11:3 14:16 14:20

15:4 20:8

20:13 22:1 28:25

28:25 40:22 41:7

41:10 41:13

43:13 43:16

44:12 44:12

44:13 44:14

49:15 56:10

56:17 56:20

56:21

dose-response

20:10 22:6

22:8 22:11 22:16

23:8

doses 14:8

16:15 18:10 23:5

24:25 25:5 39:14

52:23 66:24

66:24 67:5 70:19

dosimetry 13:21

dosing 7:5 8:1

8:1 8:12 12:10

12:11 14:24

28:13 40:19

41:12

downgraded 10:10

downloaded 4:3

Dr 2:4 2:15

2:18 3:2 3:4 3:8

3:13 3:15 3:16

4:7 4:9 4:11

4:15 4:17 5:6

5:10 5:11 5:16

5:18 5:22 5:24

6:2 6:4 6:15

6:16 6:18 6:19

7:14 7:17 7:19

9:22 11:24

12:2 13:25 13:25

14:2 14:3

16:18 16:18

16:20 16:21

18:22 18:22
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 89

18:24 18:24 19:1

20:20 20:20

20:21 21:1

21:2 21:3 21:9

21:11 21:12

21:18 22:12

23:23 23:23

23:25 24:1

24:6 24:6 24:7

24:12 24:12

24:13 24:20

24:22 24:23 25:7

25:7 25:17 25:17

25:17 25:21

25:21 25:22 26:4

26:12 26:13 27:4

27:4 27:5

27:12 27:12

27:13 27:20

27:20 27:22

27:22 28:5

28:6 28:20 28:20

28:24 29:1

29:3 29:5 29:6

29:17 29:24

29:25 30:2

30:5 30:7

35:15 35:15

35:17 35:18

35:21 37:20 38:1

38:1 38:3 38:4

39:7 39:7 39:9

39:10 39:11

45:11 46:8

47:2 47:3 47:4

47:6 47:9

47:10 47:11

47:14 50:14

50:14 50:16

50:17 50:17

50:25 50:25

51:18 51:21

51:22 52:10

52:10 52:18

52:18 52:19 55:6

55:6 55:20 55:20

55:21 55:22

55:25 55:25

58:13 58:13

58:15 58:16

58:17 58:24 59:2

59:4 59:13 59:13

59:14 59:16

59:16 59:17 60:5

60:5 60:7 60:8

60:10 60:11

60:12 60:14

60:15 61:15

62:10 62:14

62:15 62:17

62:17 62:18

62:19 63:12

63:12 63:14

63:15 65:23

65:23 65:25 66:1

66:2 66:2 66:3

66:4 66:4 66:6

66:7 66:7 66:9

66:10 66:10

66:11 66:20

66:20 66:21

66:23 67:10

67:13 67:13

67:14 67:19

67:19 67:20

67:20 67:21 69:6

69:6 69:8 69:9

70:21 70:21

70:23 70:24 71:1

71:3 71:4 71:5

71:5 71:6 71:7

71:7 71:8 71:9

71:9 71:10 71:13

72:4 72:13 72:14

72:15 72:15

72:17 73:7

73:9 73:12 73:18

73:19 74:16

74:16 74:25

74:25 75:9 75:19

75:20 75:24

draft 29:19 75:18

76:10

drag 26:13

drainage 34:12

drew 38:16

drink 45:21 64:17

64:19

drinking 2:9 6:10

6:21 14:21 14:22

25:10 26:15

27:11 33:11

37:13 40:1 40:21

41:1 41:4

45:15 63:20 64:2

64:11

drinking-water

46:5

drive 52:16 57:10

driver 49:3 52:8

drives 52:4

drop-off 18:6

drug 40:12

due 32:23

duration 7:4

7:7 7:8 33:6

39:17 56:4

56:8 56:13

57:8 57:13

58:3 58:8 59:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 90

durations 31:7

58:1

during 8:10

8:22 12:22 21:12

23:6 23:21 31:10

31:11 39:21

57:18 73:25

dying 36:7

dynamic 19:24

30:18

E

earlier 30:4

46:25 48:12

early 20:1 20:5

easily 29:11

easy 46:12

ecologic 64:3

64:7

ecological 47:19

educate 68:3

educated 32:8

educational 71:16

effect 8:25

11:2 19:7

19:21 20:2

20:8 23:4

28:13 36:18

37:20 37:21

40:16 52:22

57:25

effective 9:4

45:9

effectively 13:23

effects 2:8 2:8

5:8 8:19 8:21

13:9 13:22

20:2 20:6

22:10 22:15

23:16 23:20

24:25 25:4 32:13

33:23 34:3 35:13

37:4 52:12 52:24

55:9 55:14 58:19

62:3

efficacy 27:23

efficiencies 45:1

45:3

effort 64:6 72:25

73:11

either 7:9 8:12

9:6 25:4 49:15

electronic 4:16

76:1

elimination 42:13

56:12

ELLEN 62:18

else 3:1 36:17

embedded 17:3

emphasis 55:13

emphasize 67:2

encourage 14:17

14:22 63:7

endeavors 75:10

endocrinologists

69:11

endpoints 8:14

13:10 30:15 46:8

enhanced 65:7

enjoyable 71:24

enjoyed 69:4

Enoch 9:11 10:9

12:17 13:5 13:18

15:21

Enoch's 9:16

enormous 72:25

entertaining

71:15

entire 60:9 60:10

73:10

environment 47:12

49:23 53:4 63:24

68:2

environmental

9:17 13:3 37:2

37:4 37:11

55:9 55:14

environmentally

36:4

enzyme 48:15

48:15 58:20

enzymes 42:16

EPA 24:24 25:3

25:20 48:19 49:7

50:9 51:9

67:15 74:1 76:4

epi 52:13

epidemiological

20:14

epidemiologists

26:16 37:1 63:19

epidemiology 27:1

27:7 30:15 32:14

33:21 35:12

equal 56:24

equally 9:15

43:18 43:18
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 91

43:22

equivalence 18:5

equivalent

18:10 40:10

56:10 56:17

56:20

equivocal 15:18

especially 70:17

establish 32:19

53:21

established 51:3

estimate 15:3

28:22 31:18

45:17

estimates 42:3

estimating 6:10

25:10 39:13

65:17

estimations 33:6

et 7:23 9:11

12:17 13:5 13:18

34:14 53:6

53:8 53:11 54:10

55:4 55:4

ethyl 9:20

evaluated 8:21

9:2

evaluating 7:1

18:1

evaluation 4:4

event 20:1 20:5

eventually 42:13

everybody 3:9

4:20 29:9 68:8

75:17 76:3 76:12

everyone 2:5

everything 15:2

49:5 53:13 67:16

74:20 76:6

evidence 9:6

30:13 32:15

32:19 35:12

41:23 48:8

evolving 19:12

exactly 62:12

examined 8:11

examining 28:8

28:17

example 19:19

20:5 23:15 38:13

58:5 62:22

63:2 63:3 63:4

68:6

exceeding 30:20

excretion 28:22

excuse 39:10

exerting 16:11

exist 17:25 50:5

existing 41:19

expect 22:1

22:5 22:15

expected 7:23

experimental

30:15 31:19

experiments

44:8 44:19

expertise 72:8

73:22 73:24

explain 68:6

explanations

22:23

explicitly 19:13

exposed 12:21

14:7 14:9

27:10 32:17 65:4

68:10

exposure 7:7

11:10 13:8 13:10

14:23 19:7 19:15

19:17 26:17 27:7

29:21 31:7 31:14

31:20 32:20

32:24 34:1 39:14

39:16 40:10

40:15 40:20 41:6

41:9 41:11 41:25

42:1 43:10 43:21

43:25 44:3

46:3 49:22 54:23

56:4 57:18 63:11

64:7 64:24 68:15

exposureassessment 64:24

exposures 6:11

6:21 8:9 8:13

8:14 8:16 8:18

8:22 9:7 13:23

14:21 25:11

30:16 32:6 32:12

42:7 45:13 45:17

55:18 65:17

express 72:17

73:19

extend 52:23 55:2

62:20 63:9

extended 9:1

67:24

extension 13:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 92

extent 19:23

26:21 30:16 33:6

42:18 54:15

external 41:9

extra 59:17

extrapolate

43:1 46:11 46:12

extrapolation

51:2

extrapolations

31:13

extremely 14:15

eye 24:24

F

F2 22:12 22:16

faced 33:25

faces 2:11

facilities 27:16

facility 34:16

65:2

fact 14:7 16:10

19:10 32:10

32:23 33:20 34:3

34:24 42:9

factor 17:3

19:4 19:11 24:10

42:11 61:7

factors 6:7

34:8 34:11 34:17

fairly 24:4 24:5

fall 41:2

falls 25:2

farm 50:2 63:2

63:3

farms 50:1

fecal 28:9

28:12 28:23

Federal 3:6 74:14

feed 36:16

feeding 14:18

feel 10:13

28:21 65:9

feeling 35:21

35:23

feelings 10:8

female 38:17 39:1

61:8

Fenner 25:17

Fenner-Crisp

16:20 16:21

18:23 21:18 38:3

38:4 39:8

62:14 62:15

fetus 15:11 18:5

fetuses 14:16

field 53:6 53:9

53:10 54:16

55:17 72:9 72:10

fields 53:3

53:5 53:22

FIFRA 2:1 2:6

fifty 54:19

figure 23:1

23:3 36:2

60:20 68:25

filling 2:15

filter 64:16

filtration 28:1

final 2:5 29:9

66:13

finalized 75:13

finally 20:13

71:22

finding 59:25

findings 13:12

13:20 13:21

fine 57:17

59:12 59:14 66:9

finish 4:21

finished 14:5

18:21 26:15 27:3

34:6 36:22 36:25

37:8 63:20 63:23

64:2 65:9

finished-water

27:1 65:14

firmly 24:24

first 6:16 6:25

56:2 75:18 76:10

first...thank

6:15

fit 11:6 22:20

53:11

five 71:20

fixed 24:24 41:13

44:4

flag 12:20

flight 61:4

flip 59:22

floor 33:16

fluctuation 45:18

focus 73:25
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 93

focused 25:4

55:11

focuses 62:23

focusing 53:7

66:24 67:6 67:10

food 40:25

forget 75:23

form 36:3

forth 35:6 52:24

forward 2:25 39:2

73:6 74:23 75:8

fourth 2:5

Fowle 5:6 5:7

5:11 5:16 5:24

6:4 6:16 25:21

29:16

FQPA 19:3

frankly 39:6

frequency 2:9

30:22 31:6

31:9 31:17 33:17

34:2 53:12

54:3 58:3 68:19

frequently

59:20 65:18

full 11:19

fully 18:7

18:12 31:17

fun 68:8

future 33:22 48:1

G

gather 15:7 73:22

gavage 14:24

28:25 41:1

general 16:22

26:18 48:17

generally 8:14

generation 22:16

generic 19:13

Geological 50:4

GERALD 66:3

Gerry 16:1

gestational 13:10

gets 37:6

getting 15:8

33:10 72:2 75:2

given 26:18 28:18

31:14 35:8 43:11

44:23 45:13

45:20 67:16

68:25

gives 4:21 62:1

giving 44:18

gland 8:15 10:4

11:18 12:9 12:12

12:14 12:20 13:9

13:14 13:22

15:21 16:8 21:14

21:24 21:25 22:3

24:15 24:16

51:20

glandular 21:15

glean 54:24

GnRH 7:20 40:4

40:11

Gold 62:17

62:18 63:13

gonadotropinreleasing 61:21

gonads 12:6

gone 2:17 46:23

grandchildren

22:17

graph 11:22 12:1

great 49:20 66:13

greatest 23:11

49:2

greatly 72:6

Greenwood 39:9

39:10 47:3 70:23

70:24

Greenwood's 56:1

groping 62:6

group 12:24

23:8 30:4 61:5

61:6 72:21 73:14

group-level 64:6

groups 10:24 20:3

20:18

growing 59:23

60:1

guess 14:11 15:18

16:1 32:8 59:17

guidance 40:8

gut 46:13

H

half-life 56:12

Hall 27:22

27:22 27:22

hand 37:10

handle 10:15

hang 49:4
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 94

happen 46:1 74:15

hard 4:14 15:22

16:12 75:25

Harris 63:14

63:15 65:24

hate 37:6

haven't 11:14

having 18:12

22:14 23:16

37:19 50:8 51:24

53:9 63:21

hazard 19:23 20:3

hazardous 58:18

58:21

health 2:7 5:8

30:23 31:8 32:13

32:23 33:12

33:20 33:23 34:3

35:9 35:13

36:3 36:18 38:20

47:19 47:19

48:13 55:9 58:19

62:22

health-based 35:6

hear 47:16

heard 11:14 25:15

26:14 28:21

39:21 54:20

69:19

hearing 47:16

63:18

Heeringa 2:4 2:13

3:4 3:13 4:7

4:11 4:17 5:10

5:18 5:22 6:2

6:15 7:17

11:24 13:25

16:18 18:22

20:20 23:23 24:6

24:12 24:20 25:7

26:4 27:4

27:12 27:20

28:20 29:1

29:6 29:24 35:15

38:1 39:7 47:2

47:9 50:14 51:18

52:18 55:6 58:13

59:2 59:13 59:16

60:5 60:10 60:12

62:10 62:17

63:12 65:23 66:2

66:4 66:7

66:10 66:20

67:13 67:19 69:6

70:21 71:1

71:5 71:7 71:9

72:4 72:14 73:18

74:17 75:1 75:20

75:24

help 45:7 49:3

68:3

helpful 41:16

72:11 74:23

helps 73:4 73:4

hepatotoxicity

48:20

HERBERT 59:17

herbicide 49:25

herbicides 55:9

here's 51:14

He's 3:20

hesitate 2:25

high 13:15 14:8

44:12 54:8 59:25

higher 8:9 9:8

11:3 11:21

highest 11:20

20:17 54:18

highlighted 42:5

highly 12:21

12:21 46:14

histological

10:20 10:21

hole 21:23

home 64:18

Honda 61:15

Honda's 60:15

Honest 60:16

hopefully 15:4

47:25

hormone 61:21

Horseman 24:12

24:13 26:12

26:13 29:3

29:5 51:21 51:22

67:13 67:14

Hotchkins 9:20

hours 4:22

12:11 42:15

70:13 70:15

HPA 60:17 60:19

human 2:7 14:6

15:15 15:16

20:19 30:15

30:23 31:8 31:14

31:24 32:6 32:13

32:19 32:23 33:6

33:11 33:23 34:3

35:13 36:3 38:16

38:18 39:24

40:20 41:11 43:2
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 95

45:21 52:23 56:4

56:10 56:16

56:20 57:18

57:22 62:21 65:3

65:17

humans 14:9 30:18

32:17 39:25

44:21 45:13

46:11 46:13

46:17 46:22 51:4

55:2 64:22

human-study 63:8

hundredfold 11:3

hundreds 58:22

hydrophilic

21:6 24:17

hydroxyatrazine

3:14 3:19 9:12

9:14 9:24 12:24

hydroxyl 12:24

hydroxylation

9:15

hydroxylations

9:19 9:21 10:1

10:1

I

ICV 61:23

I'd 61:9

idea 10:15

20:18 41:17

41:25 48:5

48:8 50:3

ideal 42:25 49:11

ideally 63:25

64:14

ideas 65:18

identical 45:2

identified

40:17 46:9

identify 40:15

I'll 2:12 5:3

19:2 25:20 38:24

47:1 59:4 59:7

69:15 74:12

75:11 76:7

Illinois 53:23

I'm 2:13 2:13

2:13 3:16 5:7

7:7 9:22 9:24

11:22 18:9

25:2 25:20 29:15

35:23 37:24 38:9

42:21 51:6

51:7 53:2

56:17 57:21

59:11 60:17

62:16 63:15 65:7

65:15 66:9

68:5 72:15 72:20

immuno 50:20

impact 10:25 20:7

46:6

implication 45:22

implications

44:21

implicit 25:23

important 6:7

10:2 19:5 36:7

36:13 36:14 41:8

41:10 41:18

42:20 44:20

44:21 65:1 70:19

impose 47:19

imposed 66:18

imprecision 31:16

improve 64:3

improving 64:6

inch 73:5

include 6:9 19:22

29:21 30:12

60:23 62:24

including 9:19

12:5 19:14 19:18

20:4 30:18

32:2 53:11 55:17

60:12

inclusion 20:15

incoming 27:16

incorporate 47:7

incorporated 47:5

increase 20:13

increased 19:24

increasing 23:5

68:19

incredibly 11:19

incumbent 17:2

17:18

Indiana 53:23

indicate 40:23

individual

13:22 42:1

42:7 45:7

individuals

6:22 7:10

infant 15:12

infants 6:14
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 96

19:25 25:13

48:13

influence 7:20

10:11 13:23

inform 19:24

29:23 56:8 56:13

57:7

information

3:19 3:23 7:15

11:13 14:10 25:1

26:17 27:1

27:7 28:8

28:11 31:5 32:21

40:4 45:13 48:22

51:8 51:11 54:24

58:10 74:24 75:7

informative 74:23

informing 55:18

input 25:14

insight 42:7

insightful 72:21

instance 44:12

46:16

instead 68:19

72:2

insufficient

32:19

intake 34:15 37:6

intakes 40:1

integrate 30:8

integrated 61:13

integrative 29:25

intent 4:21

interacts 60:18

interest 49:16

59:21

interested 49:17

interesting 11:13

18:3 61:13 61:18

internal 14:16

15:4 41:6

45:17 49:15

interpret 10:16

11:4

interval 20:12

introduce 2:12

5:6 31:16

involved 42:16

53:6

irrelevant 25:3

isn't 26:20

isopropyl 9:20

issue 15:21 29:19

29:23 30:10 53:3

issues 3:18

24:2 30:11 47:23

50:11 72:20

it's 8:2 10:15

11:5 11:8

12:11 12:12

12:18 12:24

14:22 15:22

15:24 16:2

16:2 16:11 16:14

21:4 21:4 21:7

21:14 21:15

22:25 23:1

23:2 23:3 23:4

23:18 24:3

24:4 24:5

24:18 24:19 25:3

28:19 29:13

34:20 36:14

36:16 37:1 37:13

37:14 37:14

37:15 37:21

37:22 40:13

40:14 41:13

41:18 41:23 44:9

44:9 44:18

45:5 45:19 46:10

46:12 46:24

48:21 53:17

53:17 54:15

54:21 54:21

54:22 56:18

56:21 56:25

56:25 57:2

57:3 57:16

58:2 58:6 58:8

58:9 61:5 61:5

61:13 68:10 69:1

69:1 69:24 69:25

70:7 72:10 72:23

73:13 73:16

73:20

I've 46:23

47:24 60:16

63:16 67:16

70:24 72:8

J

Jack 5:6 5:7 5:11

5:16 5:24 6:4

JAMES 21:2

21:12 28:6 28:24

66:21

Jan 27:14

Janice 14:3

27:5 49:12 50:17

71:8

JNPR 4:4
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 97

job 30:24 49:13

50:10 51:10

66:13 67:17

68:20

Joe 3:5 3:7 71:24

73:9 74:14

John 24:23 30:2

38:9 47:6

47:13 66:1 71:13

72:5 72:13

joint 50:5

JOSEPH 3:8 3:15

4:9 4:15 74:16

75:19

judgment 18:20

justified 31:17

K

Kamel 41:21

KANNAN 24:7 55:22

69:9

Karen 49:11

KATHERINE 66:11

KEL 57:7

KENNETH 71:6

Kevin 61:6

key 11:14 20:1

20:5 58:1

keyed 14:11

61:3 61:3

kidney 11:21 12:6

kilogram 8:17

8:20 8:25 9:4

10:6 12:11

23:9 23:10

kilograms 38:17

kinds 64:23

kinetic 14:14

18:4 19:23 30:18

kinetics 18:11

18:12

King's 61:5

knowledge 20:4

39:19 67:21 72:9

Kow 46:18

Krishnan 24:6

24:7 55:20 55:22

58:14 67:21 69:8

69:9 70:22

L

lab 9:20 54:13

laboratory 28:8

lactating 21:10

24:16

lactation 21:13

23:6 23:21

lactational

8:18 9:7

ladder 28:2

lakes 37:14 37:14

landmark 60:23

large 54:4

last 3:10 4:3

5:19 27:14

28:6 47:22 50:18

54:19 60:15

63:17 66:22

69:15 71:11 72:3

74:8 75:4

late 2:16 5:17

20:1

later 16:1 20:6

Laura 73:9

lead 6:17 39:20

40:21

leading 9:7

leads 43:11

learn 73:23

learned 47:24

67:17

least 28:1

28:22 32:11 75:3

75:4

leave 47:1 47:4

LeBlanc 66:2 66:3

Lee 59:16 59:17

60:6 67:20

Legan 52:18 52:19

55:7 66:5 66:6

Legan's 58:17

62:19

legitimate

10:17 49:18

49:22

length 15:19 54:4

lesion 39:19

42:21

lesions 10:20

10:21 39:21

less 8:7 10:5

23:10 53:18

58:11

let's 29:10 36:23

level 11:10 11:10

20:8 30:20 40:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 98

43:11 44:1 64:14

64:14 65:1 69:21

69:25 69:25

levels 7:2 8:8

9:2 10:5 13:8

32:24 33:10 36:3

39:14 48:15 55:3

58:20 70:18

Levine 72:15

LH 7:21 30:12

30:17 31:20

31:24 32:4 43:12

47:24 48:18 49:2

50:22 51:2

52:5 58:8 62:4

66:15 67:3 69:18

life 6:12 6:23

7:12 17:7

17:22 18:12 19:8

19:17 25:12

25:14 67:7

73:1 73:1

Lightman's 61:6

likelihood 19:15

likely 21:5

24:4 28:4 45:13

limitations

31:1 35:8

limited 32:18

49:21

limits 25:2

line 66:17

lines 51:19

link 3:20 4:6

41:9

linking 30:14

lipid 16:8 16:11

lipophilic 16:9

21:3 21:4 21:8

24:4 24:5 24:16

lipophilicity

24:2

list 64:22

literature 9:23

57:10 61:19

little 3:12

3:23 5:16 7:13

11:2 12:23 21:13

26:14 32:7 36:17

41:7 53:1 60:4

65:3 65:18 72:5

live 53:16

liver 11:21 12:6

live-trap 54:7

living 55:3

log 24:3

logic 18:1

long 50:12

longer 4:25 67:7

long-term 63:7

lose 36:24 37:1

37:7

lot 6:24 14:8

14:13 17:8 24:14

25:24 36:24 38:7

39:13 39:21

45:24 48:22

48:23 50:2 52:20

53:5 54:24 55:13

58:19 62:21

62:24 64:6 65:15

67:7 75:7

lots 21:6

low 10:5 10:23

13:8 16:15 38:19

44:12 44:13

45:22

low-dose 14:10

lower 20:12 22:13

33:15

lowest 8:24 9:3

13:6

Lowit 9:22

25:21 25:22

29:17 59:4 72:15

72:17 73:19

74:19

low-level 13:22

64:10 65:17

luck 75:9

lucky 65:6

M

magnitude 51:15

magnocenter 61:1

main 5:21 5:22

maintain 44:6

maintenance 34:22

major 5:13 5:14

64:21

makeup 10:14

mammalian 12:25

13:1

mammary 8:15 10:4

10:24 11:18 12:9

12:12 12:14

12:20 13:9 13:14

13:22 15:21 16:8
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 99

21:14 21:24

21:25 22:3 24:15

24:16 51:20

manifest 52:15

Maryland 58:24

match 17:23 18:11

26:10 40:11

material 42:14

67:15 73:2 74:4

materials 4:12

74:3 75:25

matter 11:11

24:14 24:18

28:23

may 7:6 8:9

12:8 12:21 12:21

13:9 17:24 17:25

21:21 22:11

23:16 29:22

31:18 32:11

32:12 32:17

32:25 33:11

33:15 33:22

34:24 36:16

41:11 42:4

44:4 49:6

52:12 52:13

52:14 52:16

59:21 59:22 60:2

63:10 65:2

67:3 67:3

71:20 71:20

maybe 5:4 12:14

13:1 46:6 51:7

51:23 52:1 54:23

57:19 60:3 70:15

mcmanaman 21:2

21:12 28:6 28:24

66:21

McManaman 21:1

23:24 28:5 28:21

52:11 66:20

meals 41:4

mean 10:23

13:17 15:22

28:15 36:15

36:22 53:12

53:22 54:3

56:7 57:15

58:4 69:13

meaningfully

30:22

measure 41:25

measured 65:2

measures 24:8

63:19 63:23 64:2

64:11 65:9

mechanism 13:12

51:4 52:3 52:9

mechanisms

16:12 32:16

52:14

medial 60:25

61:11

mediated 7:21

Meek 7:14 19:2

30:8

Meek's 18:24

20:21

meet 76:9

meeting 2:2 2:6

25:2 50:18 52:13

60:9 67:18 73:10

73:25 74:15

74:20 75:1 75:12

75:21 76:7 76:14

meetings 3:6

47:15 68:5 71:20

71:20 72:21

73:24 74:9

Mel 49:12

members 2:19

20:24 71:23

73:20 74:2

75:5 76:8

Mendez 73:13

menstrual-cycle

63:5

mention 3:14

mentioned 9:22

21:18 49:25

62:25 66:23

metabolic 15:11

23:16 23:20

42:16 52:16

metabolism 9:18

13:1 13:2

15:14 25:16

metabolite 9:12

9:24 24:16

metabolites 4:5

9:14 11:20

12:9 12:19 13:11

13:14 48:2

48:6 48:9

54:12 57:5 64:11

67:7 67:7

methods 48:4

mice 53:6 58:21

micrograph 60:23
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 100

micrographs 61:2

mid-afternoon

75:3

middle 60:15

69:10

milk 18:4 18:6

mill 15:7

milligram 10:5

23:10

milligrams 8:17

8:20 8:25 9:4

12:10

mind 2:24 7:8

10:14 26:7

38:5 48:14 48:16

58:1 60:22

mind-numbing 36:1

minimal 11:10

12:25

minimum 39:20

40:8 44:3 44:3

44:5

minute 42:3

44:7 44:18 45:6

minutes 71:11

75:13

missed 30:21

missing 22:9

22:10

mix 57:3

mixes 69:1

mixture 9:11 10:6

12:18 48:1 49:21

49:22

mixtures 49:19

51:17 68:1

mode 20:4 40:5

57:13

model 15:8

45:17 49:10

modeling 42:24

46:18 49:13

models 22:20

moderate 44:14

modern 36:13

modulating 62:4

MOIZ 47:11

50:25 58:16

67:20

moment 43:4 43:12

46:4 74:8 75:21

moms 14:16

money 68:19

monitor 67:22

monitoring 2:9

3:19 19:18 26:15

45:6 57:14

58:3 58:11 59:20

59:23 63:16

67:23 67:23

month 57:17

months 75:12

morning 2:4

2:12 6:19

11:15 35:18

52:20

morphometric

10:22

Morseth 7:23

mostly 52:13

59:18

mouse 53:17

move 21:22

29:10 46:20

48:18

moving 46:21 54:3

MPOA 61:17

Mumtaz 47:10

47:11 50:15

50:17 50:25

55:20 55:21

58:15 58:16

67:19 67:20 69:7

Mumtaz's 52:10

myself 5:7 70:11

N

NAS 69:23

National 38:20

nature 41:4 54:22

55:17

NCHS 38:20

necessary 13:23

neither 47:18

Nelson 5:4

24:13 26:13 29:5

51:22 59:5 67:14

nervous 12:6

neural 52:3

52:8 52:15

neuro 50:20

neuroendocrine

52:3 52:16

neurons 61:21

neurotoxicity
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 101

48:20 52:1

52:2 52:7

nexus 44:2

nice 46:19

51:12 58:6

nicely 35:22

night 4:3 60:15

69:10

nitrogens 21:5

NOAEL 69:20 69:20

NOAPL 69:22

no-effect 69:25

Non-Cancer 2:8

non-human 55:9

55:13 55:19

non-lactating

23:22

non-tapped 65:15

normal 22:1

22:5 22:11

note 38:5

notebook 70:14

noted 8:8 8:15

10:18 13:17

notes 61:9

nothing 3:1 36:10

66:1 66:3

67:14 71:4

71:6 71:8

notion 22:21

51:25

nugget 60:17

null 28:2

numbing 38:6

O

observable

69:21 69:24

observation 24:11

obtained 28:8

31:19

obviously 10:15

10:17 10:23 38:9

53:8 73:21

O'Byrne 61:6

occasions 9:10

occur 11:9

occurrence 28:4

occurring 32:17

49:23

occurs 14:23

o'clock 29:11

octanol 24:5

offered 38:13

Office 5:8

Official 3:6

74:14

off-stream 34:16

Oh 3:15 5:15

60:11

okay 3:3 3:4

4:9 4:17 4:19

5:10 5:23 6:2

19:1 23:11

26:4 26:11 28:20

29:8 51:9

53:19 59:2

59:5 60:11

66:7 72:14 75:22

ones 9:25 16:22

one-size-fits-all

35:5

ongoing 33:22

34:22 35:11

55:16

open 2:18

operative 32:16

opinion 35:20

opportunity

42:1 48:3

50:13 71:16

opposed 14:24

31:21 35:5

oral 12:10 41:1

order 51:15 74:5

order-ofmagnitude 33:14

organ 49:16 49:17

organism 8:10

14:6 15:10 15:11

organisms 9:8

13:16 55:3

organization

3:1 26:10 76:10

organized 74:3

74:11

organophosphates

50:1

original 13:4

originally 62:6

others 3:2 25:17

ought 37:17 53:2

ourselves 25:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 102

outcome 19:14

67:4

outcome-based

35:9

outcomes 30:23

31:8 31:21

32:7 32:23 66:25

67:2

outcoming 27:17

outside 25:2 53:1

53:24 54:14

59:23 60:1 62:21

63:8

overall 10:8 50:5

51:16

overcome 42:4

overnight 2:21

oxidant 34:20

P

packed 11:19

Page 38:15

pages 73:2

pair-fed 23:7

23:12

Panel 2:1 2:6

2:12 2:19 3:21

3:24 4:12 6:6

20:24 50:22

53:10 59:7 67:16

69:5 71:12 71:14

71:23 72:7 72:11

73:20 74:2 74:12

75:5 75:6

75:11 75:25 76:8

76:8

Panel's 47:13

paper 9:16 9:19

10:3 10:7 10:9

10:18 11:16

13:18 15:22

16:15 29:20

30:10 42:6

61:4 61:5

61:18 61:23 62:8

69:17 69:20

papers 11:15 13:5

41:21

paradigm 14:19

parameters

15:11 15:14

parent 56:21

56:24 57:1 57:4

parents 68:7

participated 76:4

participation

69:5 72:7

particular

25:19 35:4

40:1 42:12 49:15

49:16

particularly 6:13

23:21 25:13

58:21 64:4

partition 24:8

42:3

parvocellular

60:25 61:11

pathway 68:15

pattern 35:2

42:18

patterns 33:2

33:4 34:13 45:18

PBK 15:8

peak 45:20

peaks 33:1 45:7

peg 21:22

PENELOPE 16:21

38:4 62:15

Penny 16:20

people 2:22 5:1

25:18 27:10 36:8

46:5 46:25

51:9 52:11 54:20

64:16 68:3 73:14

73:16 74:7

per 8:17 8:17

8:20 8:20 8:25

8:25 9:4 9:4

10:5 10:6

12:11 23:9 23:10

52:2

percent 11:20

28:22 65:6 65:7

perhaps 27:6

period 3:24

8:10 9:1 14:23

39:16 40:10

40:17 43:23 44:6

46:2 75:14 76:2

periods 19:16

peripubertal 8:13

8:22 9:7

permanent 71:23

76:8

personal 60:17

73:1 73:12

personally 72:7

perspective 33:17
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 103

51:17

pertain 6:13

perturbation

69:21 69:25

70:18

pesticide 52:22

55:3

pesticides 5:9

19:9 55:8

pH 21:6

pharmaceutical

32:3

pharmaceuticals

46:16

pharmacodynamics

32:1

pharmacokinetic

42:24 43:6 48:11

56:3

pharmacokinetics

31:25 57:24

phenomena 52:14

phenomenal 73:10

phenomenon 52:4

physiological

21:6 22:15 66:24

66:25 67:1

67:4 67:5

physiologically

42:24

physiology 22:4

pick 6:25

piece 11:13 54:10

pieces 58:1

pipeline 18:16

placenta 8:7

places 54:20

plan 5:1 74:20

76:9

plant 34:23

plants 45:1

45:2 45:8 45:14

plasma 18:5 24:10

39:15 39:17

39:24 40:24 41:5

41:15

plasmaconcentration

39:25

plasma-tissue

42:3

play 45:24 55:18

players 72:10

Please 6:9

29:17 29:21

point 4:19 5:3

6:1 7:9 7:24

20:23 37:15

37:24 52:10 59:3

59:6 66:13 66:19

69:3 72:15 74:13

points 11:7

policy 70:7

political 71:19

Pope 6:18 6:19

7:19 12:2 14:1

18:24 19:1 20:21

21:9 21:11 25:17

27:12 27:13 71:9

population

20:19 52:22 54:8

68:16

populations 48:14

63:10

Portier 2:15 2:18

71:5 71:6 74:25

position 33:20

35:10

possibilities

39:3 43:17 50:5

possible 47:21

56:13 63:1

possibly 23:21

59:24 74:6

postnatal 8:12

post-SAP 75:10

potency 48:5 48:9

potent 69:1

potential 10:11

18:17 18:18

19:24 20:7 23:20

29:20 30:17

30:19 30:23 31:8

32:6 46:8

potentially 22:10

pounds 39:2

PPK 49:10 49:13

pre-adult 17:12

18:17

precise 31:18

preconceived

22:21

predicated 19:4

predict 37:4 45:7
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 104

prefer 26:16

preliminary 29:18

30:4

prenatal 8:10

8:12 8:14 8:17

9:6

preparation

26:8 30:3

prepared 20:22

preputial 8:14

8:19 8:22

present 32:13

67:25 68:24

68:25 69:23

presented 15:2

16:6 27:21 39:12

40:18 40:25 56:5

58:9 74:11 75:25

presenting

14:20 51:13

68:15

pretty 12:7

16:8 73:16

previous 52:1

primary 22:1

26:19 39:19

42:21 51:1 52:15

priority 64:8

probably 14:25

16:7 16:10 36:15

41:2 53:17 53:24

61:13 67:22

71:11

problem 33:18

51:1 68:9 69:2

problems 42:4

52:21

procedure 28:17

procedures 30:21

proceed 5:17

proceedings

2:14 2:23 26:6

59:10

process 10:11

11:7 16:5 17:1

17:3 72:23

73:4 76:4 76:6

produce 40:10

40:16

produced 42:20

producers 47:20

producing 28:2

productive 4:25

29:14

products 64:20

professional 73:1

profile 6:12 6:23

7:12 17:7

17:15 18:8 25:12

40:24 48:21

51:16 57:14 68:1

profiles 17:12

17:23

progress 3:10

50:12 50:12

promoting 49:13

proposed 19:18

31:13 31:16 32:5

52:4

prostatitis 8:19

protected 58:24

protective 20:2

20:4 20:5

proteins 42:10

42:15 42:17

provide 3:20 3:23

4:5 13:14

20:17 32:20 33:5

33:15 33:16

33:22 35:12

38:24 40:7

41:9 70:15 70:16

provided 3:22

7:15 41:22 41:23

providing 32:15

proximity 27:8

prudent 35:9

pseudo 40:21

pseudo-steady

15:1

puberty 61:8

61:23 61:25

public 47:17

47:18 49:23 74:7

74:22 75:15 76:5

published 38:21

38:25

pulled 74:20

pulling 46:24

pups 14:17

18:10 22:12

23:22

putting 12:14

35:21

PVN 60:20 60:24

61:11
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 105

Q

qualitative

17:4 17:5 19:6

21:18

quality 20:17

48:15 67:15 74:3

quantitative 17:4

17:10 17:24

18:18 19:6 20:15

21:19 32:20 39:4

quantitatively

17:13

question 2:17

2:20 5:4 6:5 6:5

6:20 7:4 7:12

20:25 23:18

25:19 25:25 26:1

28:10 29:15

29:17 32:9 36:11

43:7 59:4

59:19 59:24 60:8

60:12

questionable

56:17

questions 4:22

10:18 18:17

19:21 26:10 35:1

36:8 36:9

57:20 72:1

quick 45:20

quickly 66:12

quite 9:1 9:9

12:4 15:20

39:5 40:5

46:15 46:19

50:11 55:16

72:23

R

R1 61:22

R2 61:22

radio 53:12 54:2

radioactivity

11:17 11:21

radiolabeled 8:5

rainfall 37:12

raised 45:12

46:25 53:2 57:20

raising 53:3

range 11:4 12:5

32:5 42:9

42:15 49:8 51:15

53:15 53:16

53:21

rat 30:13 46:17

57:19 57:22 61:8

rather 19:19 33:3

36:1 39:5

40:25 46:21 49:4

69:20

Ratner 58:25

rats 32:16 51:3

54:13 58:21

raw 73:3

Rayner's 22:12

reached 11:11

59:3

real 15:24 16:3

16:16 24:25

24:25 25:4

25:5 26:17

realistic 14:19

47:21 50:7

realistically

64:1

reality 30:5 39:5

real-life 63:10

really 3:8 11:6

11:11 11:22

15:22 24:18

35:19 35:20

35:22 35:23 40:7

41:18 43:8

43:9 43:15

44:8 45:6

50:23 57:9

58:2 58:2 58:4

58:4 59:25

60:3 61:2

61:18 64:4 65:10

65:13 66:13

66:15 68:13 70:1

72:1 73:3 75:6

realm 54:14

reason 11:23 27:5

27:6

reasonable 11:5

11:8 33:5 76:2

reasons 10:12

recall 55:13

received 25:1

recent 4:4 7:25

9:19

receptor 40:12

receptors 61:22

recollection 24:9

24:11

reconcile 8:3

record 5:5
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 106

18:25 22:25

24:24 26:3 59:10

redo 17:19

reduction 40:11

redundant 41:14

re-emergent 33:8

Re-Evaluation 2:7

reference 3:18

4:5 19:12

38:22 57:11

references 3:20

referring 9:25

refers 13:5

refined 45:6

reflected 34:25

reflection 14:6

reflective 14:9

reflects 57:18

Refuge 58:24

regard 31:23

51:25

regarding 6:21

7:11 21:16 21:24

28:11

regardless 10:3

regards 21:2

regimen 41:12

regimens 14:18

43:16

registrant 7:25

31:9 36:19

regular 41:12

regulation

42:16 66:17

66:18

regulatory 52:8

reinforce 13:19

reiterate 74:2

relate 19:15 46:7

related 2:19 15:4

22:4 23:19 34:22

59:9

relates 29:20

56:2

relating 24:2

56:4

relation 20:9

53:21 65:3 65:8

relationship

20:10 23:8

relative 8:11

20:18 36:9

41:4 48:10

relatively 8:1

11:19

relevance 31:24

40:4

relevant 19:7

19:11 19:16

20:10 25:6

26:2 31:7

36:10 54:16

65:17

reliable 50:23

reliance 20:8

REM 62:11

remaining 6:11

21:13 25:11

remarks 30:4

reminding 25:9

71:25

removal 27:24

remove 26:20

26:24 34:19

removed 26:22

reorganization

26:9

repeat 46:23

repeated 8:1 8:16

40:19

replicated 7:24

16:3

replication 13:20

16:16

report 26:8 38:20

47:22 51:9 57:11

reported 9:18

10:3 32:23 33:24

reporting 10:20

represent 33:11

representative

15:16

represents 33:9

41:6

reproductive 7:21

54:9

requests 6:6 32:9

required 31:9

requirements

31:20

research 40:5

49:21 63:9
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 107

reserve 18:20

reservoir 34:16

reservoirs

37:14 37:14

residues 21:7

resources 65:14

respect 14:12

16:6 17:22

30:6 30:17

31:1 31:7 66:15

respond 72:1 72:2

response 22:2

30:13 30:14

44:17 69:14

responsible 32:6

rest 25:23

31:11 57:2 71:23

restrictions

47:20

resulting 41:6

results 11:6 28:2

33:23 35:11 56:5

retain 47:25

retract 51:10

return 29:8 74:18

review 2:8 8:2

71:18

rich 16:9

RICHARD 35:18

39:10 59:14

70:24

rightly 62:22

ring 9:15 10:1

12:24

risk 6:13 13:24

15:25 20:15

21:16 22:9 22:19

22:23 32:21 64:5

68:21

risk-assessment

10:11 11:7 16:4

risks 33:11 33:13

roam 53:14

robust 20:15

Roby 66:10 66:11

rodent 43:2 52:22

56:3

rodents 46:11

46:13 46:21 53:5

53:7 53:11 55:2

rolling 7:6

room 2:11 76:9

rotate 29:15

rough 18:5 28:22

round 21:23

route 42:25

routinely 53:11

S

safety 17:2 19:3

sample 15:15

53:20 68:20

68:25

samples 7:2

13:7 60:2 63:6

67:25 68:17

sampling 30:21

30:22 31:9 31:16

34:2

SANDRA 52:19 66:6

SAP 5:12

SAPs 52:2

saw 6:20 8:24

14:8 15:1 15:13

scale 33:14 42:14

scaling 38:15

39:3 56:3

56:12 56:16

56:19 56:19 57:8

scenarios 41:3

Schlenk 23:25

24:1 71:3 71:4

science 73:5

scientific 2:1

2:6 6:7 31:2

39:13 71:19 76:4

scientists 72:22

score 10:19

scores 10:23

scratchy 6:5

screen 25:24

se 52:2

searching 62:2

season 31:10

59:23 60:1

second 7:11

secondary 22:3

22:10 26:19

39:21

section 29:19

30:10 42:5 48:11

seeing 14:13

14:18 37:21
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 108

seem 24:8 35:9

56:10 63:9

seemingly 19:4

seems 7:2 21:16

26:23 31:17

36:17 36:24

37:17 51:23

53:19 55:11

56:15

seen 14:21 33:2

74:6

sees 69:20

selected 13:13

selection 19:11

selectively 8:9

send 3:21 3:25

sends 12:20

sense 4:20

26:20 51:23

70:20

sensitive 12:21

13:9 48:14 50:23

68:16

sensitivity 9:8

13:15 18:8 20:18

sent 30:3 30:8

separately 57:7

57:9

separation 8:15

8:19 8:23

SEPTEMBER17 2:3

series 31:12 35:6

62:23

serve 71:16 75:6

service 27:18

73:8

setting 32:12

several 4:13 8:21

50:19 52:11

shape 36:3

50:13 55:4

sharing 73:13

sheer 74:4

SHELLY 63:15

she's 5:13 9:25

shifted 55:14

short 64:7 74:5

showed 8:18 27:15

28:12

showing 9:20

22:12

shown 34:20

shows 23:4

significant

10:4 18:6 36:4

65:13 70:8

similar 8:1

8:18 40:16 57:25

58:8

simple 22:16

28:16 28:19

45:17

single 72:18

sit 35:24 35:24

site 41:9 43:11

58:23

sites 27:24 58:18

58:22 58:22

sitting 49:11

situation 30:25

73:15

Six 71:20

size 34:13

sleep 62:11 69:10

slighted 42:9

slightly 60:22

slope 34:14

slopes 37:4

small 58:23

smoother 40:24

snowstorm 5:19

social 71:19

soils 34:13

soluble 26:21

somehow 52:23

someone 27:14

somewhat 35:24

51:3

somewhere 8:16

41:2

sooner 15:25

sorry 3:16 62:11

sort 2:25 15:22

16:4 16:14 16:15

24:17 26:23

39:15 39:17

39:18 40:2 40:20

40:21 41:6 42:19

45:8 59:3

59:18 62:2 65:21

72:8

sound 52:25

source 34:8 34:15
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 109

35:2 64:21 64:25

68:16

sources 7:3 44:24

59:21

spatially 34:9

44:24

speak 10:10 51:24

SPEAKER 3:3 4:3

5:15 5:20 5:25

75:17 75:22

speaking 11:19

specific 6:9

specifically 32:9

60:19 61:15

spend 64:5 64:17

spent 9:9 50:19

spleen 12:6

spot 68:5

spread 70:12

square 21:22

staff 73:10

74:1 76:4

Stafford 61:6

stage 18:13 18:14

25:14

stages 6:12

6:23 7:12 17:7

17:12 17:22 19:8

19:17 25:12

standard 70:4

standing 13:18

13:19

start 17:20

30:1 59:8

started 58:18

starting 31:19

startling 39:5

state 15:1

40:22 56:14 57:1

statement 16:22

21:3 47:7

steady 40:22

56:14 57:1

steady-state

57:24 58:7

steam 34:7 34:15

step 73:6

Steve 2:13

67:17 71:22

STEVEN 2:4 3:4

3:13 4:7 4:11

4:17 5:10 5:18

5:22 6:2 6:15

7:17 11:24 13:25

16:18 18:22

20:20 23:23 24:6

24:12 24:20 25:7

26:4 27:4

27:12 27:20

28:20 29:1

29:6 29:24 35:15

38:1 39:7 47:2

47:9 50:14 51:18

52:18 55:6 58:13

59:2 59:13 59:16

60:5 60:10 60:12

62:10 62:17

63:12 65:23 66:2

66:4 66:7

66:10 66:20

67:13 67:19 69:6

70:21 71:1

71:5 71:7 71:9

72:4 72:14 73:18

75:20 75:24

Stoker 11:16

41:22

Stone 3:16 3:17

59:8 59:11

stops 54:3

storage 34:16

strategies 8:1

strategy 19:18

34:25

stream 34:5

strength 30:13

stress 61:11

61:14

striking 12:7

strong 21:21

structural 42:17

structure 9:15

12:24 21:15

struggled 15:23

struggling 60:18

stuck 72:2

students 69:24

studies 7:25

8:4 8:5 8:11

8:21 9:3 9:5

9:10 9:18 9:23

12:16 14:14

18:15 18:20

20:16 23:19 28:9

28:12 28:15

30:16 33:21

35:12 58:19
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 110

62:21 62:22 63:4

64:3 64:7

64:13 64:24

65:11 73:3

stuff 46:24

submit 17:18

subparts 2:18

subsequently 34:6

substantial

13:3 55:8

subtle 37:20

subtraction 28:19

successful 74:21

sufficient

18:16 32:20

43:24

sufficiently 20:2

20:15

suggest 8:8

13:8 23:15

24:9 33:9 39:4

48:4 65:5

suggested 23:7

27:6 27:6

66:18 67:10

suggesting 18:9

suggestion 25:16

suggestions 51:19

suggestive 32:15

suggests 22:14

31:5

summarizing 30:25

summary 51:8

summing 66:13

supersaturation

38:8

supplies 64:12

65:14

supply 34:6 34:7

support 33:23

70:16 70:17

suppress 30:17

suppression 30:12

31:21 31:25

43:11

sure 9:22 9:25

11:22 22:25 26:2

42:21 65:7 66:19

surface 36:22

36:24 37:13

56:19 57:8

surge 7:21

30:12 30:17

31:21 31:24 32:4

43:12 47:24

50:22 51:2 52:5

surprising 16:7

16:10 24:18

Survey 50:4

survival 54:1

54:5

surviving 54:6

SUSAN 60:8

60:11 60:14

susceptibility

19:16 19:25

65:19

susceptible

19:7 43:18 43:22

synergy 72:23

73:15

Syngenta 3:22

23:1 23:7

27:22 28:10

40:19 40:23

Syngenta's 15:14

system 12:6 34:11

34:18 34:21 35:3

35:4 37:2

52:15 60:17

60:19 61:12

systematic 19:5

systematically

30:11

systems 30:6 33:1

54:9 56:22

T

table 38:15

56:5 63:19

tackling 71:18

taking 32:1 43:4

talented 73:15

talk 38:8 69:11

69:13

talked 10:19

15:19 15:19

15:20 48:12

49:10 69:14

talking 9:10

50:19 52:13

58:18 60:24 62:3

target 3:11

22:1 22:4

43:10 51:1

task 67:18 72:19
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 111

TCT 19:19

team 73:12 73:13

technical 38:11

temporally 34:9

44:24

terminologies

70:2

terms 2:25

22:23 23:10 27:2

27:8 39:14

46:2 46:11 46:13

48:14 57:11

57:13 68:4

terrestrial 55:11

55:15

territories 53:17

tertiary 26:23

testing 39:3

Testosterone 9:2

text 25:23

textbook 58:5

thank 2:15 3:2

4:7 4:9 4:17 6:2

13:25 14:3 16:18

18:22 20:20

23:23 25:7

29:1 29:1 29:2

30:2 35:14 35:15

38:1 39:7 47:2

47:9 50:13 50:14

55:6 58:13 59:11

59:14 60:5

62:7 62:10 63:12

65:23 67:15 69:4

69:6 70:21 70:25

71:14 71:22 72:3

72:4 72:13

73:7 73:10 73:18

74:12 74:22

74:25 75:5 75:16

76:3 76:12

thanks 65:22

71:24 73:12

74:16 74:18

that's 4:1 4:11

4:24 5:1 7:18

12:7 15:7

16:10 16:13

17:19 18:2 18:13

22:17 23:16

25:23 37:23

37:23 37:25

38:12 42:10 43:5

43:23 45:4

45:4 45:22 48:13

48:24 55:16 57:2

58:4 58:12 63:18

65:1 65:21 69:23

70:5 71:21 73:17

74:10

theirs 16:23

themselves 2:12

therefore 17:25

there's 7:6 7:8

9:6 10:17

11:22 12:4 12:15

17:8 24:14 24:15

39:12 48:23 50:1

52:20 53:5

53:6 53:23

54:4 54:18 55:16

63:17 68:8 72:22

they'll 75:14

they're 9:25

36:12 39:18

43:18 46:14 54:6

65:16 68:13

75:14

they've 39:23

thinkingoutside-thebox 62:19

thoughts 2:21

26:6 38:2 65:22

thousands 53:23

63:2 73:2

throughout 45:5

47:22

Thurman 27:21

59:5

thus 9:5 12:16

tie 37:2 40:13

tight 68:5

tighter 66:18

til 75:3

timeline 75:17

76:10

tissue 11:17 16:9

42:10 49:15

54:11

tissues 12:5 12:5

24:10 42:1

42:7 42:12

title 61:7

today 15:21

tolerant 43:19

tomatoes 64:21

tone 39:11

tools 48:7

top 11:12 62:15
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 112

63:23 64:14

topic 2:7

topics 71:19

total 4:22 46:3

68:20

totally 54:16

tox 18:8 57:15

toxic 16:12

toxicities

48:19 48:24 49:2

49:8

toxicity 7:22

8:12 17:7

17:11 17:15

17:23 18:18

48:17 50:6 50:20

51:3 52:7

52:15 57:14

toxicologic 48:21

toxicological

6:12 6:23 25:12

toxicologist 36:1

38:5

toxicology 15:5

18:2 62:13

track 53:14 75:2

transparent 19:4

trap 54:7

traveling 64:18

treat 3:25

treated 7:1 22:17

treatment 26:19

26:22 26:24

27:16 28:3 34:22

45:1 45:2 45:8

45:14 65:2

tree 49:5

tremendous 73:23

triazines 50:1

tricky 56:25

tried 35:25 46:23

trouble 12:1 12:3

true 68:12

truly 73:4

try 21:22 43:8

45:17 46:10

47:21

trying 5:1 11:7

14:15 15:3 21:20

21:21 36:2 39:18

39:24 46:7 52:21

55:2 68:6 74:19

turn 3:5 5:3 6:17

20:23 25:20

25:21 29:25 59:4

72:15 74:13

turned 72:8 74:21

turnover 42:14

turns 4:24

type 34:20

types 50:20 65:8

U

U.S 38:19 39:1

50:4

ultimately 49:14

uncertainties

6:10 6:11 6:21

6:22 14:12

19:6 25:10 25:11

25:25 31:1 31:15

43:1

uncertainty 16:13

20:9 34:1

39:13 44:22

underestimating

19:17

underlined 70:14

underlying

21:17 52:4 52:9

understand 2:16

17:11 18:7 18:12

26:17 28:15

28:15 36:12

36:22 37:7 39:23

52:1 66:14 66:14

66:16

understanding

31:2 42:22

undue 47:19

unequivocally

31:22

unfair 36:18

unfinished 65:9

unfortunately

44:22

unique 34:11

units 43:21

unless 29:11

68:10

unlikely 21:4

21:7

untreated 7:3

update 38:25 39:4

upon 30:23 34:8
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 113

58:17

upstream 62:3

uptake 8:7

urban 36:14

urge 24:24

urine 63:5

useful 14:15

14:25 15:3

15:6 15:9

32:11 34:24

48:22 49:9

55:1 64:5

USGS 3:18

usual 75:14

usually 36:16

utility 26:25

V

value 19:3

variability 44:23

44:25 45:14 46:6

variable 41:15

varied 41:10

variety 30:14

various 17:7 17:9

17:12 17:22

20:18 24:10

39:20 48:6

vary 34:8

versus 20:8 57:22

via 40:20

view 19:10

52:19 63:8

views 47:13

voice 6:5

volume 74:4

W

wasn't 12:2 23:18

waste 58:18 58:21

watch 54:2

water 2:9 3:17

5:20 5:22 6:11

6:21 7:2 7:3

10:14 13:6

14:5 14:21 14:22

24:5 25:11 25:24

26:15 26:19

26:22 27:3 27:11

27:18 30:6 30:19

33:1 33:5

33:11 34:6

34:7 34:8

34:11 34:15

34:15 34:19 35:2

35:3 35:4

36:22 36:22

36:25 36:25 37:8

37:13 37:13 40:2

40:21 41:1

41:4 44:23

45:1 45:2 45:8

45:14 45:15

45:19 45:21

57:14 59:20

63:16 63:20

63:23 64:2 64:11

64:16 64:17

64:19 64:21

64:24 64:25

water-main 5:13

water-sampling

31:5 32:25 33:17

water-treatment

34:18

ways 51:24

weak 27:8

weakened 10:25

wealth 28:7

website 75:15

we'd 37:7 40:20

Wednesday 76:5

weed 33:8 36:15

week 31:10

39:22 60:10

64:20

weekly 58:11

weeks 31:6

31:10 34:2 42:16

57:16 60:2

weight 23:11

23:12 38:18 39:1

48:8

weights 22:13

23:5

welcome 2:5

2:24 3:9

we'll 4:25 5:17

11:25 29:8 29:25

66:4 68:10 75:20

well-known 61:19

we're 3:11

14:13 15:10

15:15 22:9 29:10

37:21 42:21

49:17 50:12

52:12 53:7 59:25

62:3 62:11 64:12

65:6 67:5 67:6
FIFRA SCIENTIFIC ADVISORY PANEL 09/17/10 CCR#15732-8 114

70:18 73:5

Wes 3:2 59:8

WESLEY 59:11

we've 3:10

10:19 15:19

17:21 25:1 35:25

37:12 38:10

45:24 54:15 59:3

59:18 62:12 63:4

63:21 64:4 74:6

whales 53:12

whatever 49:6

51:15 55:4

whenever 51:12

whereas 56:15

WHEREUPON 76:14

whether 7:6 7:8

9:25 10:21

16:2 16:2

16:10 17:6 18:15

24:18 34:2 34:14

41:17 42:21 43:9

44:9 44:9

44:16 51:1

51:4 58:2 59:8

64:16 65:16

66:17 70:11

white 10:7 10:8

42:6 69:20

whole 6:24

31:12 38:7

42:8 43:22

wholly 41:23

widely 37:18

wild 58:20

Wildlife 58:24

window 31:14 34:1

66:16

windows 29:20

65:19

wish 72:11 75:9

woke 60:14

60:21 69:9

women 38:18 62:24

63:6

wonder 26:18

26:25

wonderful 49:12

50:10 51:10

word-for 19:2

work 17:8 23:1

33:16 38:10 42:2

45:2 48:1 55:8

55:15 55:16

58:25 62:5 69:23

74:6 74:7

worked 76:5

workers 63:2 63:3

working 63:3 74:7

75:5 75:11

works 15:7 51:4

world 45:5 50:10

worms 53:8

worry 68:14

worth 45:16 60:4

worthwhile 45:25

Wow 12:14

wrap-up 4:23 29:9

65:21

written 5:12

20:22 38:10

wrong 51:6

Y

yesterday 2:16

3:16 3:17 9:9

9:23 13:17 15:20

16:1 34:10

48:7 51:19

yesterday's 35:1

yet 66:14 66:15

67:2 67:12

you'll 26:7

young 6:22

you've 38:13

65:15

Z

zoo 68:6 68:7