OFFICE OF CHEMICAL SAFETY

AND POLLUTION PREVENTION

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460

RE: Meeting between Dow AgroSciences and EPA to Discuss Chlorpyrifos and 

Recent Epidemiology Studies, the April 2012 SAP, and Dose Reconstruction

Meeting Summary

On Wednesday, August 21, 2012, EPA’s Office of Pesticide Programs met with Dow AgroSciences

(DAS) to hear their interpretation of three recently released epidemiology studies in light of the recently 

released April 2012 SAP minutes. The meeting also included a discussion regarding dose reconstruction 

challenges and limitations.

List of Documents

1. Meeting Summary Page 1

2. Meeting Sign in Sheet Page 2

3. DAS PowerPoint Page 3

a. Epidemiology Summary

4. EPA Memo to File Regarding DAS Slide #2 Page 22

5. DAS PowerPoint Page 23

a. Using Exposure Information and PBPK Models to Improve the 

Chlorpyrifos Risk Assessment

Epidemiology Summary

Carol J. Burns, MPH, PhD

August 21, 2012
Meeting outline

• DAS view of the best available science 

utilizing 2010 guidance on integrating 

epidemiology

• What is EPA view of recent publications for 

WoE?

• Actionable items

• Discussion
Hypothesis based WoE

H1: Chlorpyrifos induces NDT at 

doses below those that cause brain 

AChEI

• Epidemiology is 

compelling (association is 

causation)

• Animal models 

underestimate toxicity by 

a factor >1,000

• Must assume existence 

of unknown mechanism 

for low dose effects

H2: Chlorpyrifos induces NDT only at 

doses that cause brain AChEI

• Epidemiology is not 

compelling (association 

not causation)

• High dose animal data 

defines MOA

• No low dose mechanism 

is needed

Based on Prueitt 2011, pages 885 - 886
Epidemiology data not compelling and high 

dose animal data defines the MOA:

– Columbia study findings are not replicated

• Chance, bias and confounding can not be ruled out 

with reasonable confidence

– No AChEI in epidemiology studies 

• See DAS comments for SAP

DAS View (H2)
Columbia hypotheses not replicated

(Full DAS review submitted Nov. 2011)

Endpoints 

hypothesized to be 

affected by chlorpyrifos

Supporting 

studies

p<0.05

Fail to support

p<0.05

Comments

Birth weight 0 4

Some interaction of ∑DEP and PON1, but not seen with TCPy

Birth length 0 3

Not reported by AHS

PDI scores 0 2

Columbia rejected at 12 and 24 months

No others tested at 36 months

MDI scores 0 2

Columbia rejected at 12 and 24 months, 

No others tested at 36 months

ADHD 0 1

Tested only with ∑DEP 

TCPy not analyzed at 3.5 and 5 y

Attention problems 0 1

Tested only with ∑DEP, TCPy not analyzed at 3.5 and 5 y

PDD 0 1

None tested at 36 months

Full Scale IQ 1 (p = 0.05) 1

Tested only with ∑DEP, 

TCPy not analyzed in Berkeley or Mt. Sinai

Working Memory 0 2

Tested only with ∑DEP, 

TCPy not analyzed in Berkeley or Mt. Sinai
Agency will place “higher confidence in results which are 

replicated or reproduced from multiple studies (EPA draft 

framework)

Replication across studies
SAP minutes: 

– “Total DAPS are not selective enough to be a 

useful biomarker for chlorpyrifos”

– “TCPy is a better measure than 

dialkylphosphates”

Discuss

Evaluating consistency

CHLORPYRIFOS vs. DAP
Author, 

year

OR

PDD

CI Sig? CIR Comment

Rauh 

2006

CPF* 5.4 1.2-24.1 Yes 19.9 Strong assn.

Least stable

Eskenazi 

2007

DAP 2.3 0.99-5.2 No 5.2 Strong assn.

More stable

“ “ DMP 2.2 1.1-4.6 Yes 4.4 Most precise

Malathion?

“ “ DEP 0.9 0.4–2.1 No 5.6 Weak assn.

Chlorpyrifos and 

diazinon?

“ “ TCPy NR NR No Not reported

Example: No consistency of association 

of PDD and chlorpyrifos

*Only hi vs. low reported, no results for continuous results or air, urine, meconium

PDD: Pervasive Developmental Disorder
• DISCUSS

– How do strength or precision play a role in 

the EPA draft framework?

– What about the confidence interval?

– Are all non significant data presented?

Statistical testing
Author, year Beta LL UL Sig Comment

Rauh 2006 CPF* -0.003

-0.006

-0.006

-0.006

0.001

0.000

No 

Yes

N= 265

Adjusted, Age 7

Bouchard 

2011**

DAP -5.6 -9.0 -2.2 Yes N=297

Bouchard 2011 DMP -4.7 -7.7 -1.6 Yes Malathion?

Bouchard 2011 DEP -2.1 -5.6 0.3 No Model 2 age 7

Chlorpyrifos and diazinon?

Engel 2011** DAP -1.4

-1.1

-1.1

-4.5

-5.0

-4.6

1.8

2.8

2.3

No

No

No

N=140

N=115

N= 98

Engel 2011 DMP -0.5

-0.4

-0.6

-3.2

-3.6

-3.7

2.3

2.9

2.6

No

No

No

Engel 2011 DEP -2.9

-3.2

-1.4

-6.2

-7.2

-5.3

0.4

0.9

2.5

No

No

No

Model 1 age 6-9

Model 2 age 7-9

WPPSI-III age 6

Example: No consistency of association 

of FSIQ and chlorpyrifos

*continuous, IQ on log scale; **TCPy not analyzed

•FSIQ: Full Scale IQ
• Human data have many “inconsistencies in the 

results both within and among the cohort 

studies” (Prueitt 2011)

• Human evidence for causality is “weak” (Li 2012)

• “Maternal RBC AChE inhibition is a more 

sensitive endpoint for risk assessment than 

somatic developmental effects “ (Mink 2012)

3 review papers: 

Epidemiology data inconclusive

Discuss
Poverty, poor quality 

home, low education, 

poor parenting skills

Poor childhood 

outcome High Pesticide Use

Confounding, pesticides

Maternal factors

correlate with poor

outcomes

Insect infestation in

low income housing

leads to high use.

Observed outcome
“May be related to reason for being exposed to chlorpyrifos or 

other OP (e.g., cockroach infestation associated with poor 

housing maintenance, hygiene, and care environment; extent 

of participation in agricultural work) as well as factors related 

to higher versus lower exposure (e.g., following instruction 

labels regarding proper use). These factors could also be 

related to the learning and developmental environment, which 

may affect the test scores in the child...”

Page 133, Li et al., 2012

Li et al. on confounding
1. Other pesticides should be correlated with 

developmental effects 

– Piperonyl butoxide and MDI score (Horton 2011)

2. Levels of adverse effects do not change 

when exposure reduced

– “Post-ban” MDI and PDI scores are not better than 

“pre-ban” (Rauh 2006)

3. Different exposure opportunities would not 

have same correlations

– CHAMACOS results for TCPy and DEP are not 

significantly associated with neurodevelopment

If confounding...
1. Analysis of CCCEH birth cohort 

born <2001 vs. 2001 and after

– This is the counter factual analysis that 

controls for the home environment and 

removes the reduction in chlorpyrifos use 

and increase in other uses

– Note: This was Question 3 submitted 

November 2009, with Columbia response on 

March 2010

Actions?
2. Pooling all three studies to increase 

statistical power for dose-response 

and interaction analyses

– Note: this was Question 4 submitted in November 

2009

– Was also recommended by 2012 SAP

– NIEHS has awarded $568,000 to Brenda Eskenazi at 

Berkeley to conduct this analysis (~2009)

Actions?
3. Evaluate CHAMACOS results

– Cord and maternal blood reported for 

234 mothers and 256 infants (Huen

2012)

– Test associations using urinary TCPy

Actions?
• Evaluation of neurodevelopmental instruments

• Other chemical exposures in the CCCEH

• Non chemical risk factors in the CCCEH

• Examine NHANES for OP data

• Feasibility of accessing raw data in all 3 cohorts 

with an SAP

DAS research considerations
To Paul Price...
OFFICE OF CHEMICAL SAFETY 

AND POLLUTION PREVENTION 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460 

MEMO TO FILE 

DATE: October 17, 2012 

RE: Slide #2 of Dow AgroSciences’ PowerPoint Presentation “Using Exposure 

Information and PBPK Models to Improve the Chlorpyrifos Risk Assessment”, 

August 21, 2012 

FROM: Joel Wolf 

 Slide number 2 in Dow AgroSciences’ PowerPoint presentation indicates that hypothesis 

number 3 was “suggested by EPA”. This statement does not accurately reflect the position of 

EPA and its attribution to EPA is incorrect from EPA’s point of view.
Using Exposure Information and 

PBPK Models to Improve the 

Chlorpyrifos Risk Assessment 

Paul Price

The Dow Chemical Company

August 21, 2012

Presented to 

US Environmental Protection Agency
A Third Hypothesis

H1: Chlorpyrifos induces 

NDT at doses below 

those that cause brain 

AChEI

• Epidemiology is 

compelling 

(association is 

causation)

• Animal models 

underestimate 

toxicity by a 

factor >1,000

• Must assume 

existence of 

unknown 

mechanism for 

low dose effects

H2: Chlorpyrifos induces 

NDT only at doses that 

cause brain AChEI

• Epidemiology is 

not compelling 

(association not 

causation)

• High dose 

animal data 

defines MOA

• No low dose 

mechanism is 

needed

H3 (Suggested by EPA): Chlorpyrifos induces 

NDT only at doses that cause brain AChEI and

exposures in Epi studies were sufficiently 

high to cause brain AChEI 

• Epidemiology is compelling 

(association is causation)

• Consistent with belief that high 

dose animal data defines MOA

• No low dose mechanism is 

needed

Page 2
Key question for Hypothesis 3

• Do the data on chlorpyrifos suggest that mothers in the Columbia 

cohort were exposed to levels that could have caused significant 

inhibition of RBC or brain ACHE? Considering: 

– Data published by the authors

– Data published in earlier studies of exposures from residential uses

– Data from occupational exposures

Page 3
Blood levels indicate no AChEI at the time of birth

• Blood levels at time of birth:

– 75% of participants had levels that were similar to the general public

– The max blood level (Columbia) was 15 fold higher then the upper bound level 

predicted for the dietary exposures general population (35 vs. 2 ng/l)

– Existing studies in of workers and worst-case residential exposures confirm that 

blood levels in this range do not cause RBC AChEI (Garabrant, Dow studies) 

• Modeling suggest that:

– Blood concentrations >30,000 ng/l cause 10% RBC AChEI

– Blood concentrations >100,000 ng/l are required for apical effects

Page 4
Blood Concentration of Chlorpyrifos vs. RBC AChEI

1.00E-02

1.00E-01

1.00E+00

1.00E+01

1.00E+02

0.1 1 10 100 1000 10000 100000 1000000 10000000 100000000

Maximum ChEI % of control

Maximum Blood Concentration ng/l

Blood levels associated 

with 10% RBC AChEI

Range of blood levels 

reported in Wyatt, 2004 

for years < 2002

Blood levels associated 

with apical effects

Page 5
Could levels have been higher earlier?

• PBPK modeling states:

– The levels could have been 10-20 fold higher on the prior day for dose received by oral or 

inhalation routes of exposures 

– Smaller differences for doses that occur by the dermal route

• PBPK modeling indicates:

– Measurements do not reflect exposures that occurred more than 2-3 days before 

measurements

– Measures do not directly reflect peak or average doses in the first or second trimester 

• Estimates of dose received from early exposures (and associated 

blood levels and AChEI) and must be estimated from

– Worker studies

– Human exposure studies

– Exposure SOPs

Page 6
Blood Concentration of Chlorpyrifos vs. RBC AChEI

1.00E-02

1.00E-01

1.00E+00

1.00E+01

1.00E+02

0.1 1 10 100 1000 10000 100000 1000000 10000000 100000000

Maximum ChEI % of control

Maximum Blood Concentration ng/l

Range of blood levels 

reported in Wyatt, 2004 

for years < 2002

Blood levels associated 

with apical effects

Page 7
Blood Concentration of Chlorpyrifos vs. RBC AChEI

1.00E-02

1.00E-01

1.00E+00

1.00E+01

1.00E+02

0.1 1 10 100 1000 10000 100000 1000000 10000000 100000000

Maximum ChEI % of control

Maximum Blood Concentration ng/l

Range of blood levels 

reported in Wyatt, 2004 

for years < 2002

Blood levels associated 

with apical effects

Page 8

Residential Exposure Studies
Blood Concentration of Chlorpyrifos vs. RBC AChEI

1.00E-02

1.00E-01

1.00E+00

1.00E+01

1.00E+02

0.1 1 10 100 1000 10000 100000 1000000 10000000 100000000

Maximum ChEI % of control

Maximum Blood Concentration ng/l

Range of blood levels 

reported in Wyatt, 2004 

for years < 2002

Blood levels associated 

with apical effects

Page 9

Residential Exposure Studies

Egyptian Worker Studies

(Worst case exposures)
Conclusions

• There is considerable uncertainty in chlorpyrifos 

exposures in the first and second trimesters

– Who used what products

– Importance of difference routes of exposure

• Occupational exposures and exposures for off label uses 

in Egyptian studies as an upper bound to the range of 

exposures for the Columbia participants

• Brain inhibition and apical effects are not likely to have 

occurred

Page 10
Proposal 1: Refine blood data

Hypothesis

Blood levels are greatly dependent on the time since last 

exposure. PBPK models could be used to estimate a 

standard measure of blood for each mother that would be a 

better estimate of recent exposures.

Project:

Model the blood level at the time the person entered the 

hospital based on cord and maternal blood concentrations, 

timing of samples, and predicted routes of exposures 

Page 11
• Blood levels reflect recent exposure not exposure during the critical windows for fetal 

development 

• The assumption is implicitly made that recent exposures are correlated with early 

exposures

3 Birth rd

Trimester

2

ed

 

Trimester

1

st

Trimester

Window of concern Recent Exposures

Blood Measurements

Proposal 2: Develop estimates of early exposures
• The analysis does not use the other data in the exposure assessment

• Develop a categorical approach (e.g. no exposure, low exposure, high exposure) to 

1

st and 2ed

 trimester exposures that uses data on blood, air monitoring, residential 

mobility, pest pressure, and pesticide usage.

• Use the criteria to determine if the association holds for early exposures

3 Birth rd

Trimester

2

ed

 

Trimester

1

st

Trimester

Window of concern

Air monitoring

Recent Exposures

Survey Data Blood Measurements

Proposal 2: Develop estimates of early exposures
Proposal 3: Develop a BE

Hypothesis

An understanding of the blood levels in multiples studies will be 

improved by having a BE value. 

Project:

Develop a BE for chlorpyrifos.

Page 14