OFFICE OF CHEMICAL SAFETY 

AND POLLUTION PREVENTION 

UNITED STATES ENVIRONMENTAL PROTECTION AGENCY

WASHINGTON, D.C. 20460 

RE: Meeting between Dow AgroSciences (DAS) and EPA for DAS to present 

additional PBPK modeling for chlorpyrifos for life-stage corresponding to 

pregnancy

List of Documents

1. Meeting Summary Page 1 

2. Meeting Sign in Sheet Page 2 

3. DAS PowerPoint Presentation Page 3 

Meeting Summary 

On Thursday, April 2, 2015, EPA met with DAS to discuss their PBPK model. Since the release 

of the chlorpyrifos revised human health risk assessment (RHHRA) in January 2015, DAS has 

been working on a pregnancy component for the PBPK model. Currently the model cannot 

account for women of child-bearing age. DAS anticipates submitting this pregnancy component 

as part of their comments on the RHHRA. EPA will be evaluating this new component of the 

PBPK model in order to determine whether it is appropriate to support refinements to the risk 

assessment. 

Additional PBPK modelling for Chlorpyrifos during the lifestage during pregnancy

George Oliver, US Regulatory Leader, Dow AgroSciences

April 2, 2015
• Introductions and objectives

• New modeling results (Mike Bartels, Torka Poet)

• Discussion 

• Further actions

Agenda for today

2
• George Oliver, US Regulatory Leader for Chlorpyrifos, Dow AgroSciences

• Michael J. Bartels, Associate TERC Fellow- Toxicology, The Dow Chemical 

Company

• Daland Juberg, Global Leader, Human Health Assessment, Dow AgroSciences

• Torka S Poet, Sr. Associate, Summit Toxicology, LLP (Richland, Washington)

Attendees

3
• Share additional PBPK modeling for chlorpyrifos for life-stage 

corresponding to pregnancy.

• Present results which indicate the existing intraspecies UF of 4X 

is appropriate for this life stage.

• Gain an understand of what and how EPA would like DAS to 

submit this information

Objectives

4
Chlorpyrifos PBPK Pregnancy Model

• The Draft Risk assessment for Chlorpyrifos 

(CPF) of 2011 was based on a Margin of 

Exposure of 100 for Dermal exposures:

• POD for RBC cholinesterase effects in rats = 5 mg/kg

• Interspecies Uncertainty Factor (UFa) = 10x

• Intraspecies Uncertainty Factor (UFh) = 10x

• FQPA Safety Factor = 1x

• POD for sensitive humans = 0.05 mg/kg

5
Chlorpyrifos PBPK Pregnancy Model

– The Revised Risk assessment of 2014 is based on the 

DAS PBPK/PD model, validated for rats and humans, 

across lifestages and varying physiology

– Margin of Exposure now set to 40x by EPA for 

Dermal exposures:

• Interspecies Uncertainty Factor (UFa) = 1x

• POD for cholinesterase effects in human = 3.63mg/kg

• Intraspecies Uncertainty Factor (UFh) = 4x 

• FQPA Safety Factor = 10x

• POD for sensitive humans = 0.09 mg/kg

6
Chlorpyrifos PBPK Pregnancy Model

– Since the PBPK/PD model (as of 2014) did not allow 

for simulations in pregnant women, the EPA set the 

intraspecies Uncertainty Factor (UFh) for pregnant 

workers to 10x:

• Interspecies Uncertainty Factor (UFa) = 1x

• POD for cholinesterase effects in human = 3.63 mg/kg

• Intraspecies Uncertainty Factor (UFh) = 10x 

• FQPA Safety Factor = 10x

• POD for sensitive humans = 0.036 mg/kg

7
Chlorpyrifos PBPK Pregnancy Model

• To investigate the appropriateness of the default 

10x UFhfor pregnant workers, it was decided to 

expand the current Multi-Route PBPK/PD model 

to include systemic exposure and RBC effects 

predictions during all stages of human pregnancy

– Step 1: compare the predicted exposure levels that 

would result in 10% RBC cholinesterase inhibition for 

an “average” non-pregnant or pregnant woman, by 

oral, dermal or inhalation routes

– Step 2: evaluate the impact of pregnancy on the intrahuman variability in RBC effects 

• Calculation of DDEF

8
Chlorpyrifos PBPK Pregnancy Model

• Started with Multi-Route PBPK/PD model...

9
Chlorpyrifos PBPK Pregnancy Model

• Which accommodates changes across lifestages...

Smith et al. 2014

10
Chlorpyrifos PBPK Pregnancy Model

Then modified to include changes due to Gestation:

Addition of placenta, uterine and fetal compartments, which grow over the 

course of pregnancy

Tissue Changes 

Pregnancy specific changes in the slow compartment.

Pregnancy specific changes in the fat compartment

Pregnancy specific changes in the rapid compartment

Pregnancy changes in blood composition result in increased blood volume, 

decreased hematocrit

Pregnancy specific changes in metabolism

CYP450s – based on literature data for various isozymes

PON1 – based on longitudinal studies

 -

11
Step 1 Results: 

- New Gestational compartments match empirical data

Figure 1. Growth of the fetus (black), uterus (orange), and placenta 

(blue) from GD 0 through parturition. Lines are model predictions, data 

are from (Abduljalil et al., 2012). 

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

1

2

3

4

T im e ( d a y )

T i s s u e V o l u m e ( K g )

12
Step 1 Results: 

Changes in existing tissue physiology match published data

Figure 2. Increases in fat (orange) and slow (green) from GD 0 through 

parturition. Lines are model predictions, data are from (Abduljalil et 

al., 2012). Dashed lines show model-predicted weight in a nonpregnant woman over the same span of time.

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

5

1 0

1 5

2 0

2 5

3 0

3 5

T im e ( d a y )

W e i g h t ( K g )

F a t M a s s S lo w M a s s

Figure 3. Increases in rapid (purple) and slow (green) compartments 

from GD 0 through parturition. Lines are model predictions in pregnant 

women, dashed lines show model-predicted weight in a non-pregnant 

woman over the same span of time. The symbols are total fat free mass 

less muscle and bone, which are already included in the model

(Abduljalil et al., 2012), dotted black line represents the sum of the 

slow and rapid compartments. 

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

5

1 0

1 5

2 0

2 5

3 0

T im e ( d a y )

W e i g h t ( K g )

13
Step 1 Results: 

Changes in other physiology parameters also match published 

data

Figure 4. Increases in blood volume from GD 0 through parturition. 

Blood volume increases slowly by more than 30% greater than

nonpregnant levels over gestation (Corley et al., 2003). Dashed lines 

show model-predicted weight in a non-pregnant woman over the same 

span of time.

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

3 . 5

4 . 0

4 . 5

5 . 0

5 . 5

6 . 0

6 . 5

T im e ( d a y )

B l o o d V o l u m e ( K g )

Figure 5. Changes in total cardiac output over the course of pregnancy. 

Line is model predicted, symbols are from Abduljalil et al., 2012.

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

2 0 0

4 0 0

6 0 0

T im e ( d a y ) T o t a l C a r d ia c O u t p u t ( L / h r )

. 

Figure 7. Decrease in hematocrit from GD 0 through parturition. Lines 

shows model-predicted decrease, data are from Abduljalil et al., 2012.

0 1 0 0 2 0 0 3 0 0

0 . 0

0 . 1

0 . 2

0 . 3

0 . 4

0 . 5

T im e ( d a y )

H e a m a t o c r it ( fr a c t io n )

14
Step 1 Results: 

Changes in Metabolism predict higher rate of Oxon formation during 

pregnancy

Table 1. Relative activities of CYP450 enzymes toward CPF metabolism

Oxon TCPy Reference

CYP450¥ Vmax∞ CLint Vmax∞ CLint Change

1A2 1193 3.1 892 1.4 Decreases up 

to 60%

(Tracy et al., 2005)

2B6 12544 16 1545 0.74 RNA levels 

increase

(Dickmann and 

Isoherranen, 2013)

2C19 2470 2.0 13128 8.1 Decreases up 

to 50%

(Pennell, 2003; Sit 

et al., 2008)

3A4 11946 0.44 12667 0.38 Increases up to 

30%

(Tracy et al., 2005)

3A5 2569 0.155 2141 0.09 Increases up to 

2x (Mohamed, 2013)

¥All CPY450 Kinetic values are from (Foxenberg et al., 2007), shown are 

the top 4 enzymes, enzymes with Clint < 0.3 are not shown.

§ Methadone clearance has been shown to be increased in pregnancy, 

but methadone is metabolized by several other P450s, including 2B6 

and 3A, which are known to increase during pregnancy.

∞ pmol/min/nmol

Table 2. Contribution of each enzyme and extrapolation to late pregnancy

Non-Pregnant Predicted Late Pregnancy

Oxon (%) of 

total

TCPy(%) of 

total

Oxon (%) of 

total

TCPy(%) of 

total

CYP450¥ Vmax CLint Vmax CLint Vmax CLint Vmax CLint

1A2 4.2 14 1.3 13 1.7 5.7 1.3 5.2

2B6 45 74 8.8 6.9 71 118 8.8 11

2C19 8.8 9.2 19 76 4.4 4.6 23 38

3A4 42 2.0 72 3.5 55 2.6 58 4.6

3A5 9.1 0.71 12 0.8 18 1.4 15 1.7

Total % 100 100 100 100 133 132 92 60

Figure 9. Predicted increased rate of bioactivation (red line) and 

decreased detoxification (blue line) over the course of pregnancy. 

Dashed lines show predicted metabolic rates in age -matched nonpregnant women.

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

5 0 0

1 0 0 0

1 5 0 0

2 0 0 0

T i m e ( d a y )

V m a x ( μ m o l / h r )

O x o n

T C P y

15
Step 1 Results: 

Changes in PON-1 levels included in model

Figure 10. Predicted decreased detoxification rate in plasma (black 

line) and liver (dashed line) over the course of pregnancy. Symbols are 

activity levels extrapolated from Huen et al 2010 and Sarandöl et al., 

2010, green triangles are for CPF-oxonase, black symbols represent 

data describing the related paraoxonase.

0 5 0 1 0 0 1 5 0 2 0 0 2 5 0

0

1 0 0 0 0 0

2 0 0 0 0 0

3 0 0 0 0 0

4 0 0 0 0 0

5 0 0 0 0 0

T im e ( d a y )

P O N 1 A c t i v i t y

( μ m o l/ h r / k g t i s s u e )

16
Chlorpyrifos PBPK Pregnancy Model

REFERENCES for pregnancy-based changes in physiology and metabolism

Abduljalil, K., Furness, P., Johnson, T.N., Rostami-Hodjegan, A., Soltani, H., 2012. Anatomical, physiological and metabolic changes with gestational age during normal 

pregnancy: a database for parameters required in physiologically based pharmacokinetic modelling. Clin. Pharmacokinet. 51, 365–96.

Anderson, G.D., 2006. Using pharmacokinetics to predict the effects of pregnancy and maternal-infant transfer of drugs during lactation. Expert Opin. Drug Metab. 

Toxicol. 2, 947–60.

Corley, R.A., Mast, T.J., Carney, E.W., Rogers, J.M., Daston, G.P., 2003. Evaluation of physiologically based models of pregnancy and lactation for their application in 

children’s health risk assessments. Crit. Rev. Toxicol. 33, 137–211.

Cunningham, G.F., 2010. Protocols for High-Risk Pregnancies: Appendix B. Laboratory Values in Normal Pregnancy. Wiley-Blackwell, Oxford, UK.

Dickmann, L.J., Isoherranen, N., 2013. Quantitative prediction of CYP2B6 induction by estradiol during pregnancy: potential explanation for increased methadone 

clearance during pregnancy. Drug Metab. Dispos. 41, 270–4.

Foxenberg, R.J., McGarrigle, B.P., Knaak, J.B., Kostyniak, P.J., Olson, J.R., 2007. Human hepatic cytochrome p450-specific metabolism of parathion and chlorpyrifos. 

Drug Metab. Dispos. 35, 189–93.

Gentry, P.R., Covington, T.R., Clewell, H.J., 2003. Evaluation of the potential impact of pharmacokinetic differences on tissue dosimetry in offspring during pregnancy 

and lactation. Regul. Toxicol. Pharmacol. 38, 1–16.

Huen, K., Harley, K., Bradman, A., Eskenazi, B., Holland, N., 2010. Longitudinal changes in PON1 enzymatic activities in Mexican-American mothers and children with 

different genotypes and haplotypes. Toxicol. Appl. Pharmacol. 244, 181–9.

Hytten, F., 1985. Blood volume changes in normal pregnancy. Clin. Haematol. 14, 601–12.

Kopp-Hoolihan, L.E., van Loan, M.D., Wong, W.W., King, J.C., 1999. Fat mass deposition during pregnancy using a four-component model. J Appl Physiol 87, 196–202.

Lippi, G., Albiero, A., Montagnana, M., Salvagno, G.L., Scevarolli, S., Franchi, M., Guidi, G.C., 2007. Lipid and lipoprotein profile in physiological pregnancy. Clin. Lab. 53, 

173–7.

Pennell, P.B., 2003. Antiepileptic drug pharmacokinetics during pregnancy and lactation. Neurology 61, S35–42.

Sarandöl, E., Dirican, M., Eröz, E., Serdar, Z., Uncu, G., 2010. SERUM PARAOXONASE AND ARYLESTERASE ACTIVITIES THROUGHOUT NORMAL PREGNANCY. Nobel Med. 

19, 49–55.

Sit, D.K., Perel, J.M., Helsel, J.C., Wisner, K.L., 2008. Changes in antidepressant metabolism and dosing across pregnancy and early postpartum. J. Clin. Psychiatry 69, 

652–8.

Tracy, T.S., Venkataramanan, R., Glover, D.D., Caritis, S.N., 2005. Temporal changes in drug metabolism (CYP1A2, CYP2D6 and CYP3A Activity) during pregnancy. Am. J. 

Obstet. Gynecol. 192, 633–9.

Weitman, S.D., Vodicnik, M.J., Lech, J.J., 1983. Influence of pregnancy on parathion toxicity and disposition. Toxicol. Appl. Pharmacol. 71, 215–24.

Weitman, S.D., Vodicnik, M.J., Lech, J.J., 1986a. Mechanism of enhanced parathion/paraoxon toxicity during pregnancy in the mouse. Fundam. Appl. Toxicol. 6, 155–

61.

Weitman, S.D., Vodicnik, M.J., Lech, J.J., 1986b. Influence of pregnancy on the hepatic metabolism of parathion. Dev. Pharmacol. Ther. 9, 23–31.

Young, J.F., Branham, W.S., Sheehan, D.M., Baker, M.E., Wosilait, W.D., Luecke, R.H., 1997. Physiological “constants” for PBPK models for pregnancy. J. Toxicol. 

Environ. Health 52, 385–401
Step 1 Results: 

- model output for nonpregnant women matches 

prior EPA results (see X values)

1 1 0 1 0 0 1 0 0 0

0

2 5

5 0

7 5

1 0 0

C P F (m g /k g )

P e a k R B C In h ib itio n

(% o f C o n tro l)

3 rd T rim e s te r A c u te

2 n d T rim e s te r A c u te

1 s t T rim e s te r A c u te N o n -P re g n a n t

D a s h e d lin e s = re p e a t, 4 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 4 h r

E P A ta b le 4 .8 .4

1 1 0 1 0 0 1 0 0 0 1 0 0 0 0

0

2 5

5 0

7 5

1 0 0

C P F (m g /m

3

)

P e a k R B C In h ib itio n

(% o f C o n tro l) D a s h e d lin e s = re p e a t, 1 .5 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 1 .5 h r

2 n d T rim e s te r 1 s t T rim e s te r 3 rd T rim e s te r N o n -P re g n a n t

E P A ta b le 4 .8 .4

0 .0 1 0 .1 1 1 0

0

2 0

4 0

6 0

8 0

1 0 0

C P F (m g /k g )

P e a k R B C In h ib itio n

(% o f C o n tro l)

3 rd T rim e s te r

n o n -P re g n a n t 2 n d T rim e s te r 1 s t T rim e s te r D a s h e d lin e s = re p e a t E P A T a b le 4 .8 .4 S o lid lin e s = a c u te

O ra l

D e r m a l

In h a la tio n

18
Step 1 Results: 

- Oral Exposures

0 .0 1 0 .1 1 1 0

0

2 0

4 0

6 0

8 0

1 0 0

C P F (m g /k g )

P e a k R B C In h ib itio n

(% o f C o n tro l)

3 rd T rim e s te r

n o n -P re g n a n t

2 n d T rim e s te r

1 s t T rim e s te r

D a s h e d lin e s = re p e a t E P A T a b le 4 .8 .4

S o lid lin e s = a c u te

Average 3rd trimester female ~10% more sensitive than non-pregnant female

19
Step 1 Results: 

- Oral Exposures

 - Predicted levels of CPF and 

Oxon metabolite in blood

0 6 1 2 1 8 2 4

0 .0

0 .2

0 .4

0 .6

0 .8

1 .0

T im e (h r)

C irc u la tin g C P F

(μM )

0 .0 1 m g /kg

0 .0 5 m g /kg

0 .1 m g /kg

0 .5 m g /kg

1 m g /kg

2 .5 m g /kg

0 .0 0 5 m g /kg

A - N P (d a s h e d ) c o m p a re d to 3 rd T rim e s te r (s o lid )

0 6 1 2 1 8 2 4

0 .0 0 0

0 .0 0 1

0 .0 0 2

0 .0 0 3

0 .0 0 4

0 .0 0 5

T im e (h r)

C irc u la tin g C P F -o x o n

(μM )

0 .0 1 m g /kg

0 .0 5 m g /kg

0 .1 m g /kg

0 .5 m g /kg

1 m g /kg

2 .5 m g /kg

0 .0 0 5 m g /kg

B - N P (d a s h e d ) c o m p a re d to 3 rd T rim e s te r (s o lid )

20
Step 1 Results: 

- Dermal Exposures

1 1 0 1 0 0 1 0 0 0

0

2 5

5 0

7 5

1 0 0

C P F (m g /k g )

P e a k R B C In h ib itio n

(% o f C o n tro l)

3 rd T rim e s te r A c u te

2 n d T rim e s te r A c u te

1 s t T rim e s te r A c u te N o n -P re g n a n t

D a s h e d lin e s = re p e a t, 4 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 4 h r

E P A ta b le 4 .8 .4

Average 2rd trimester female <10% more sensitive than non-pregnant

Average 3rd trimester less sensitive than non-pregnant

21
Step 1 Results: 

- Inhalation Exposures

1 1 0 1 0 0 1 0 0 0 1 0 0 0 0

0

2 5

5 0

7 5

1 0 0

C P F (m g /m

3

)

P e a k R B C In h ib itio n

(% o f C o n tro l)

D a s h e d lin e s = re p e a t, 1 .5 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 1 .5 h r

2 n d T rim e s te r 1 s t T rim e s te r

3 rd T rim e s te r

N o n -P re g n a n t

E P A ta b le 4 .8 .4

All trimesters comparable to non-pregnant

22
Step 1 Results: - exposure levels resulting in 

10% RBC inhibition for 

pregnant women (1st, 2nd or 3rd

trimester) are all within 15% of 

non-pregnant levels

- a more comprehensive 

evaluation of impacts of 

pregnancy on CPF biological 

effects in a simulated 

population was therefore 

conducted... 1 1 0 1 0 0 1 0 0 0 0 2 5 5 0 7 5 1 0 0 C P F (m g /k g ) P e a k R B C In h ib itio n (% o f C o n tro l) 3 rd T rim e s te r A c u te 2 n d T rim e s te r A c u te 1 s t T rim e s te r A c u te N o n -P re g n a n t D a s h e d lin e s = re p e a t, 4 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 4 h r E P A ta b le 4 .8 .4 1 1 0 1 0 0 1 0 0 0 1 0 0 0 0 0 2 5 5 0 7 5 1 0 0 C P F (m g /m 3 ) P e a k R B C In h ib itio n (% o f C o n tro l) D a s h e d lin e s = re p e a t, 1 .5 h r/d a y fo r 2 1 d a y s S o lid lin e s = S in g le 1 .5 h r 2 n d T rim e s te r 1 s t T rim e s te r 3 rd T rim e s te r N o n -P re g n a n t E P A ta b le 4 .8 .4 0 .0 1 0 .1 1 1 0 0 2 0 4 0 6 0 8 0 1 0 0 C P F (m g /k g ) P e a k R B C In h ib itio n (% o f C o n tro l) 3 rd T rim e s te r n o n -P re g n a n t 2 n d T rim e s te r 1 s t T rim e s te r D a s h e d lin e s = re p e a t E P A T a b le 4 .8 .4 S o lid lin e s = a c u te O ra l D e r m a l In h a la tio n

23
Step 2 Methods: 

- used data-rich oral route linked model for comparison 

with prior Variation modeling

- dietary values and model parameters consistent with 

DAS October 2014 report

24
Step 2 Results:

Simulation of RBC cholinesterase inhibition in cohorts of 10,000 

women following dietary exposure to CPF

N=10,000 / lifestage

0 .1 1

0

2 0

4 0

6 0

8 0

1 0 0

C P F (m g /k g )

P e a k R B C In h ib itio n

(% o f C o n tro l)

x Non-pregnant o 3 rd T rim e s te r

25
0 2 5 5 0 7 5 1 0 0

0 .0

0 .5

1 .0

1 .5

2 .0

P e rc e n tile

D o s e (m g /k g )

N o n -p re g n a n t fe m a le

3 rd T rim e s te r fe m a le

M a le a n d fe m a le

T h e m o s t s e n s itiv e in d iv id u a ls in e a c h

p o p u la tio n e x h ib it th e s a m e R B C in h ib itio n

a t th e s a m e d o s e (m e n , w o m e n , p re g n a n t w o m e n a re n o t d iffe re n t)

T h e m e d ia n E D 10fo r p re g n a n t w o m e n is w ith in 2 0 % o f th e o th e r p o p u la tio n s

T h e in te r-in d iv id u a l d iffe re n c e s

fo r p re g n a n t w o m e n a re le s s

th a n fo r th e o th e r p o p u la tio n s

Step 2 Results:

Percentile analysis of predicted RBC cholinesterase inhibition in 

cohorts of 10,000 following dietary exposure to CPF

26
Step 2 Results: 

- Data Derived 

Extrapolation Factors

27
0 25 50 75 100

0.0

0.5

1.0

1.5

2.0

Percentile

Dose (mg/kg)

Non-pregnant female

3rd Trimester female

Male and female

The most sensitive individuals in each

population exhibit the same RBC inhibition

at the same dose (men, women, pregnant

women are not different)

The median ED10 for pregnant women is

within 20% of the other populations

The inter-individual differences

for pregnant women are less

than for the other populations

Step 2 Results: 

- Data Derived Extrapolation Factors

Table 1. Data used in deriving the values of the Chemical Specific Assessment Factors for intraspecies extrapolation (DDEFH):

Multi-Lifestage Pregnancy Model

Male and Female Non-pregnant female 3

rd Trimester Female

50th 

percentile

Fifth 

percentile

First 

percentile

50th 

percentile

Fifth 

percentile

First 

percentile

50th 

percentile

Fifth 

percentile

First 

percentile

ED10 (mg/kg/day) 0.44 0.18 0.12 0.46 0.20 0.14 0.39 0.18 0.12

95% Lower Confidence 

Limit

of ED10 (mg/kg/day)

0.43 0.17 0.11 0.45 0.19 0.13 0.38 0.17 0.11

28
Step 2 Results: 

- Data Derived Extrapolation Factors

Table 2. Estimates of DDEFH for chlorpyrifos 

DDEFH is the difference between the 50th and the 5th or 1st percentiles for Monte Carlo simulation of 20,000 

individuals. (from Tables 1 and 2).

Multi-Lifestage Pregnancy Model – using percentiles

Male and Female Non-pregnant female 3

rd Trimester

PODSH (5t h

percentile)

PODSH (1st 

percentile)

PODSH (5t h

percentile)

PODSH (1st 

percentile)

PODSH (5t h

percentile)

PODSH (1st 

percentile)

DDEFH 2.7 4.1 2.5 3.6 2.5 3.5

0 2 5 5 0 7 5 1 0 0

0 .0

0 .5

1 .0

1 .5

2 .0

P e rc e n tile

D o s e (m g /k g )

N o n -p re g n a n t fe m a le

3 rd T rim e s te r fe m a le M a le a n d fe m a le T h e in te r-in d iv id u a l d iffe re n c e s

fo r p re g n a n t w o m e n a re le s s

th a n fo r th e o th e r p o p u la tio n s

29
Conclusions: 

Initial modeling results for pregnant women are well 

within 20% of cholinesterase response for general 

population and non-pregnant women, by any of the 

three exposure routes

A more refined “Variation” analysis in a population of 

10,000 pregnant women shows biological effects 

comparable to non-pregnant women, and both are less 

than men + women

The existing UFhvalue of 4x for male and female adults 

should therefore be protective of pregnant women in 

occupational settings 

30
Questions / Discussion

31