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1 APPENDIX

2

3 CASE STUDIES TO ACCOMPANY DATA DERIVED EXTRAPOLATION FACTOR 

4 DOCUMENT

5

6 This document is an Appendix to the draft document on Data Derived Extrapolation

7 Factors. It presents examples where the availability of data for given chemicals support the 

8 derivation of non-default values for components of uncertainty factors. Each of the chemicals 

9 examined has an existing IRIS file and/or U.S. EPA Program Office risk assessment, although 

10 the derivation of DDEFs contained in these examples may not be found in the those documents. 

11 The intent of this Case Study document is to present examples that instruct the calculation of 

12 DDEF values; Reference values derived in these case studies should not be used in place of 

13 values found in IRIS or Program Office risk assessments. 

14

15 A consistent format, below, has been developed and applied to the case studies. 

16 However, different components of case studies are more extensively described for some 

17 chemicals for others. Differences are due to chemical-specific data sets, which may be more 

18 informative for some areas than others. 

19

20 1. Summary

21 This section communicates the current assessment(s) (e.g., IRIS, PPRTV, RED, 

22 PMN/existing chemical, IPCS) and reference values. It includes the individual and 

23 composite UFs, and indicates how the DDEF was applied. 

24

25 2. Hazard Identification and Dose Response

26 This section lists the key studies, identifying the principal study and critical effect including 

27 supplemental studies which might help to inform the decision. It describes the methods to 

28 characterize the dose response relationship and models or data describing response as a 

29 function of internal (target tissue) concentration. It also includes information on the 

30 mode/mechanism of action. It is not intended to be a compendium of data; rather it should 

31 communicate the information necessary to serve as a basis for the case study. 

32

33 3. Basis for DDEF

34 This section provides the rationale for developing a DDEF rather than relying on default 

35 values. It identified models or data available for evaluation, describes the basis for selection 

36 of DDEF method and highlights the connection between the measure of dose and adverse 

37 effect. 38

39 4. DDEF Derivation

40 This section presents the computation of the DDEF value. It should be presented in a level of 

41 detail so that the reader can follow the derivation. Comparison to other possible values for 

42 the UF component should be presented. 

43

44 Each of the case studies illustrates different principles described in the Document. Table 

45 1 provides a summary of the principles illustrated in each. Note that the Agency does not yet 

46 have experience with deriving a DDEF for intra-species extrapolation with regard to TD. As 

47 such, no case study for that component is provided here.

48
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1 Table 1. DDEF Case Study Chemicals and Issues

2

Data Derived 

Extrapolation

Factor

Chemical Other Principles or Issues

Animal to Human, 

Toxicokinetics 

(EFAK)*

Ethylene glycol 

Monobutyl Ether 

(EGBE)

Choice among dose metrics, PBPK modeling, BMD 

applied to internal, not external doses

Vinyl chloride MOA analysis to identify dose metric, internal dose 

of reactive metabolite in liver chosen as basis for 

toxicokinetic equivalency between species

Animal to Human, 

Toxicodynamics 

(EFAD)

Ethylene glycol 

Monobutyl Ether 

(EGBE)

In vivo toxicity results identified effects to quantify 

in both species in vitro

Dimethyl arsenic 

acid (DMA)

Mode of action analysis, use of in vitro data, use of 

genomics data

N-methyl 

carbamate 

pesticides

Application of a DDEF to a common mechanism 

group of chemicals, use of DDEF approach to 

identify data gaps

Within Human 

Variability, 

Toxicokinetics 

(EFHK)

Boron Clearance mechanism identified, surrogate measures 

of clearance employed for quantitation

Methyl mercury Toxicokinetic model developed using human data 

from dietary exposures, choice of dose metric from 

among several surrogates

3

4 * The IRIS Assessments for these chemicals calculate a HED based on the results from PBPK Modeling. This draft 

5 document guides the development of a DDEF that results in the same human external dose, when adjusted for 

6 interspecies differences in dosimetry. The DDEF concept applied to interspecies differences in dosimetry makes 

7 explicit the magnitude of species differences, whereas methods that calculate a Human Equivalent Dose or 

8 Concentration do not make that calculation explicit. 

9
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1 INTERSPECIES ADJUSTMENT FOR TOXICOKINETICS

2

3 Ethylene Glycol Monobutyl Ether (EGBE)—EFAK

4 Case Study

5

6 Summary

7

8 Ethylene glycol monobutyl ether (EGBE; 2-butoxy ethanol) has an established RfD of 

9 0.1 mg/kg-d on the U.S. EPA’s Integrated Risk information System (IRIS) database (U.S. EPA, 

10 2010). This value is based on a human equivalent dose developed from the results of a chronic 

11 inhalation study (NTP, 2000). Internal doses resulting in hemosiderin deposition in liver were 

12 extrapolated via PBPK modeling to identify the human equivalent dose. 

13

14 As described below, the IRIS RfD is based on a PBPK modeling approach that identified 

15 an HED of 1.4 mg/kg-d. To this value, a combined uncertainty factor of 10 was applied, which 

16 comprised a single UF value of 10 for variation in sensitivity within the human population 

17 (UFH). The UFAK was reduced to 1 on the basis of the dosimetry adjustments for TK, and the 

18 UFAD was reduced to 1 based on the relatively greater sensitivity of the rat compared to the 

19 human (as discussed in the EGBE EFAD case study presented later in this appendix). 

20

21 Hazard Identification and Dose Response

22

23 No chronic oral studies are currently available for EGBE; there are only two 

24 subchronic 91-day drinking water studies in rats and mice (NTP, 1993), and a chronic 

25 inhalation study in rats and mice (NTP, 2000). Based on a comparison of NOAELs and 

26 LOAELs for hematologic and liver effects, rats are clearly more sensitive than mice. 

27 Hematologic and hepatocellular changes were noted in both sexes of rats. Hemosiderin 

28 accumulation in liver of male rats, a consequence of hemolysis, was chosen as the critical 

29 effect. Hemolysis in humans has been demonstrated to result in hemosiderin accumulation 

30 in the liver; and acute exposure to EGBE has been shown to produce hematological changes 

31 in humans (in US EPA, 2010). 

32

33 In the 2010 IRIS Assessment, PBPK modeling was employed to convert each of the inhalation 

34 exposures to levels of internal dose, and this measure of dose was combined with response 

35 levels; and a benchmark dose analysis revealed the BMDL 10 value which was chosen as the 

36 point of departure. The BMDL10 value (expressed as internal dose) was 133 μmol butoxy acetic 

37 acid/liter-hour; this was used as the starting point in the development of the IRIS RfD for 

38 hemosiderin deposition in male rat liver (NTP, 2000). In the IRIS assessment, the dose-response 

39 relationship was developed by combining PBPK modeling with BMD analysis as shown in 

40 Figure 1. 

41
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1

2

3 Figure 1. Analysis Approach for Developing the Human Equivalent Dose with 

4 Values Shown

5

6

7 Basis for DDEF

8

9 AUC values for the EGBE metabolite 2-butoxyacetic acid (BAA) in arterial blood of 

10 male rats following oral exposure was estimated using the PBPK model of Corley et al. (1994) as 

11 modified by Corley et al. (1997). BAA levels, rather than EGBE levels, were deemed 

12 appropriate measures of exposure based on the findings of Carpenter et al. (1956), which

13 demonstrated in vitro that concentrations of 0.1% BAA induced hemolysis; whereas, hemolysis 

14 was not induced by EGBE until concentrations of approximately 2.5% were reached. PBPK 

15 modeling was used to translate each of the external concentrations to levels of the dose metric, 

16 AUC. 

17

18 Next, benchmark dose modeling was applied to the results of the PBPK modeling. The 

19 results of this analysis indicated that an AUC value of 133 μmol/L-hr BAA in arterial blood is

20 the BMDL10 for increased hemosiderin deposition in liver in male rats. 

21

22 The AUC value for BAA of 133 μmol/L-hr in arterial blood was chosen as the POD for 

23 interspecies extrapolation. Next, a human PBPK model was employed to translate this level of 

24 the dose metric to an HED of 1.4 mg/kg-d. 

25

26 DDEF Derivation

27

28 The PBPK modeling approach described above was used as the basis for the development 

29 of the DDEF. In addition to the data presented in the IRIS file, the rat PBPK model was run to 

30 identify that an external dose of 5.83 mg/kg-d in the rat would produce this BMDL10

31 concentration (133 μmol/L-hr) of the BAA metabolite (Dr Richard Corley, personal 

32 communication, 2010). The human PBPK model was run to identify the external dose that 

33 produced the same level of the dose metric (133 μmol/L-hr); this value of the dose metric was 

34 produced by an external dose of 1.4 mg/kg-d in the human. The AUC dose metric was used as 

35 the basis for human equivalence. 

36

37 An alternative approach for deriving the DDEF illustrated in this case study would be to 

38 use the ratio of rat:human external doses derived from the PBPK model to derive EFAK (see 

Rat

External

Conc.

Rat

PBPK

Model

Dose

Metric

Values

BMD

Modeling

POD as

Dose

Metric

Human

PBPK

Model

Human

Equivalent

Dose

350 – 3500 

μmol/L-hr 

BAA

133 μmol/L-hr 

BAA 1.4 mg/kg-d

5.83 mg/kg-d

POD as

Rat 

External 

Dose

150 – 600 

mg/m3 EGBE
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1 Eq. 1, Section 3.2.2.2). Using the data described above, a comparison of the external doses 

2 would yield a EFAK value of 5.83 mg/kg-d ÷ 1.4 mg/kg-d = 4.2. The 4.2-fold DDEF would 

3 replace the default UFAK 3-fold factor. 

4

5 Applying the EFA-TK 4.2-fold* to the rat external dose (5.83 mg/kg-d) yields an HED of 

6 1.4 mg/kg-d. This HED is identical to that derived in the IRIS assessment (U.S. EPA, 2010).

7

8 The above methods can also be compared to the default methodology that is based on 

9 body weight scaling (U.S. EPA, 2006). Using a study-specific female rat body weight of 0.188 

10 kg, and a default human body weight of 70 kg, these values would result in a default dosimetric 

adjustment factor (DAF) = (0.188 ÷ 70)1/4 11 = 0.23. The DAF is multiplied by the animal external 

12 dose (5.83 mg/kg-d) to yield an HED of 1.3 mg/kg-d. The reciprocal of the 0.23 DAF is 

13 analogous to EFAK and would be 4.3. The 4.3-fold factor would replace the default 3-fold UFAK. 

14 In this case study, the body weight scaling default approach yields a similar RfD as the data 

15 derived approaches described above. However, the DDEF approach makes use of quantitative 

16 TK data for EGBE.

17 ______________

18 (*)Note: for EGBE, interspecies toxicodynamic data exist, and have been used in the IRIS 

19 assessment to replace the default factor of 3.2 for UFAD with a value of 1. This case study only 

20 focused on TK; please see the EGBE DDEFAD case study in this appendix. 

21

22 References

23

Carpenter, C.P., G.A. Keck, J.H. Nair 3rd 24 , U.C. Pozzani, H. F. Smyth Jr. and C. S. Wiel. 1956. 

25 The toxicity of butyl cellosolve solvent. AMA Arch. Ind. Health. 14(2):114-131. 

26 Corley, R.A., G.A. Bormett and B.I. Ghanayem. 1994. Physiologically-based 

27 pharmacokinetics of 2-butoxyethanol and its major metabolite, 2-butoxyacetic acid, in rats 

28 and humans. Toxicol. Appl. Pharmacol. 129:61-79. 

29 Corley, R.A., D.A. Markham, C. Banks, P. Delorme, A. Masterman and J.M. Houle. 1997. 

30 Physiologically-based pharmacokinetics and the dermal absorption of 2-butoxyethanol vapors by 

31 humans. Toxicol. Appl. Pharmacol. 39(2):120-130. 

32 NTP (2000). NTP technical report on the toxicology and carcinogenesis studies of 2 

33 butoxyethanol (CAS No. 111-76-2) in F344/N rats and B6C3F1 mice (inhalation studies). 

34 National Toxicology Program. Research Triangle Park, NC. NTP TR 484. 

35 http://ntp.niehs.nih.gov/?objectid=070AC403-B110-CA79-3A23AF79DE7B752A.

36

37 U.S. EPA (U.S. Environmental Protection Agency). 2010 Toxicological Review of Ethylene 

38 Glycol Monobutyl Ether (EGBE) CAS No. 111-76-2. Available at 

39 http://www.epa.gov/ncea/iris/toxreviews/0500-tr.pdf (accessed 9/10/2010).

40 U.S. EPA (U.S. Environmental Protection Agency). 2006. Harmonization in Interspecies 

Extrapolation: Use of BW3/4 41 as Default Method in Derivation of the Oral RfD (External Review 

42 Draft). Risk Assessment Forum Technical Panel, Washington, DC. EPA/630/R-06/001. 

43 Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=148525.
May 11, 2011 6 DRAFT: DO NOT CITE OR QUOTE

1 Vinyl Chloride—EFAK

2 Case Study

3

4 Summary

5

6 Vinyl chloride (VC) has an established oral Reference Dose of 3 E-3 (0.003) mg/kg-d in 

7 the current Integrated Risk Information System file (U.S. EPA, 2000). The point of departure for 

8 liver toxicity is a NOAEL value of 0.13 mg/kg-d from a chronic feeding study in male Wistar 

9 rats. PBPK modeling was used to develop a human equivalent dose of 0.09 mg/kg-d, obviating 

10 the uncertainty factor for interspecies toxicokinetics. The total UF of 30 comprises an 

11 uncertainty factor of 3 to cover toxicodynamic differences between species and a default value of 

12 10 for intraspecies variability. Species differences in dosimetry were determined on the basis of 

13 external doses required to produce the same level of the toxicologically active metabolite in the 

14 critical organ (liver). This case study demonstrates the application of data to inform interspecies 

15 toxicokinetic extrapolation (EFAK).

16

17 Hazard Identification and Dose-Response

18

19 Liver was selected as the critical target organ of vinyl chloride in humans and 

20 experimental animals. There is a strong epidemiological basis for liver effects in humans. 

21 Studies involving workers in the polyvinyl chloride plastics industry from several countries have 

22 demonstrated a significant relationship between VC inhalation exposure and liver cancer. While 

23 there may be limited evidence suggestive of a risk for other non-liver tumors (e.g., leukemia, 

24 brain, lung, pancreas, mammary) “vinylchloride is not likely to be associated strongly with 

25 cancers other than liver in humans” (U.S. EPA, 2000). Other noncancer effects noted in 

26 epidemiologic investigations include impaired liver function and biochemical and histological 

27 evidence of liver damage and focal hepatocellular hyperplasia. Pulmonary function appeared 

28 unimpaired, and no solid evidence of teratogenicity in humans has been identified. 

29

30 Limited data are available for inhalation studies in animals. Data are available from a 

31 12-month inhalation study that support liver as the critical organ. Bi et al. (1985) exposed Wistar 

32 rats to 0, 10, 100, or 3,000 ppm VC for 6 hours/day, 6 days/week. Cellular alterations, 

33 degeneration and necrosis were observed in the seminiferous tubules of the testes, with a 

34 NOAEL in the 10 ppm exposure group. This same exposure was the LOAEL for liver effects, 

35 characterized only as liver weight changes. 

36

37 Like the inhalation results, studies conducted via the oral route identify the liver as the 

38 critical target organ. Til et al. (1983, 1991) reported the results of two-year rodent bioassays 

39 with VC in feed. Groups of 100 or 50 male and female Wistar rats were exposed to 0, 0.014, 

40 0.13, or 1.3 mg/kg-d in feed for only 4 hours/day to minimize volatilization. The VC content of 

41 feed was measured before and after feeding to control for volatilization. Multiple hepatic effects 

42 were noted including several that were deemed neoplastic or preneoplastic. The pathologists 

43 were able to delineate and determine incidences for two effects not thought to represent 

44 neoplastic or preneoplastic changes. Liver cell polymorphisms and proliferative bile duct 

45 epithelium cysts served as the basis for identifying the liver as the critical target tissue for non 

46 cancer effects in the chronic bioassay. These same changes were observed in a second study, but 
May 11, 2011 7 DRAFT: DO NOT CITE OR QUOTE

1 the doses employed in that study (Feron et al., 1981) were higher than those employed by Til and 

2 coworkers. Because of a lack of confidence in the outcome from a benchmark dose modeling 

3 approach based on external dose, a traditional (NOAEL) approach to dose-response evaluation 

4 for events not associated with carcinogenicity was used. The point of departure for species 

5 extrapolation was the NOAEL of 0.13 mg/kg-d for liver cell polymorphisms and bile duct cysts. 

6

7 The initial process in the mode of action appears to be the formation of reactive and 

8 short-lived metabolites that achieve only low steady-state concentrations. These are thought to 

9 be responsible for the toxic effects of VC (Bolt, 1978). Experiments that manipulated the 

10 longevity of CYP-derived metabolites demonstrated an inverse relationship between metabolite 

11 longevity and protein and nucleotide binding (Guengerich et al., 1981). Thus, the metabolism of 

12 VC to reactive intermediates was demonstrated to be a critical determinant of toxicity. Because 

13 of the short-lived nature of the metabolite(s), a measure of their concentration in the target tissue 

14 (liver, the site of their formation) was deemed the appropriate dose metric for quantitative 

15 application. This concept and approach has also been applied to methylene chloride (Andersen 

16 et al., 1987), and chloroform (ILSI, 1997). 

17

18 Basis for DDEF

19

20 The liver was determined to be the target organ, and evidence indicated that formation of 

21 a reactive metabolite was likely responsible for toxicity. Benchmark dose modeling of external 

22 doses failed. Because of this, the POD for extrapolation was determined as the study NOAEL 

23 for liver effects, 0.13 mg/kg-d. Consistent with guidance for RfC derivation, PBPK modeling of 

24 the formation of the active metabolite in liver was used as the basis for determining an equivalent 

25 human dose. PBPK models were developed for rats and humans and used to extrapolate 

26 dosimetry between species (Clewell et al., 1995a,b), were subjected to an external peer review 

27 and deemed sufficient for quantitative reliance. The NOAEL dose (0.13 mg/kg-d) was converted 

28 into the dose metric for VC—the amount of metabolite in the liver (AML), with units of 

29 oncentration mg/liter of liver. 

30

31 DDEF Derivation

32

33 Importantly for dose extrapolation, these models demonstrated a linear relationship 

34 between applied dose and the dose metric (AML) up to doses approximating 25 mg/kg-d. This 

35 allowed linear interpolation to be used to identify levels of external doses associated with 

36 specific amounts of the internal dose, rather than specific iterations via PBPK modeling. The rat 

37 NOAEL dose of 0.13 mg/kg-d produced AML at a value of 3.0 mg/L (Figure 2). This level of 

38 internal exposure in the 70-kg human was determined to result from a drinking water exposure of 

39 0.09 mg/kg-d (the human equivalent dose). Thus, doses of 0.13 mg/kg-d and 0.09 mg/kg-d in 

40 the rat and human, respectively, are toxicokinetically equivalent. 

41

42

43

44

45

46
May 11, 2011 8 DRAFT: DO NOT CITE OR QUOTE

1

2

3

4

5

6

7

8

9

10 Figure 2. Schematic for dose extrapolation for vinyl chloride. The POD 

11 was defined as the external dose in the rat, with PBPK Modeling of the rat. 

12 PBPK modeling of the dose metric translated dose from units of applied dose 

13 to units of tissue concentration, representing the dose metric. PBPK modeling 

14 in the human identified the human equivalent dose, the dose producing the 

15 same level of the dose metric in the rat study at the POD. 

16

17

18 The IRIS file for VC used the human equivalent dose as the POD, to which UFs are 

19 applied. An alternative approach illustrated in this case study to deriving the data derived 

20 extrapolation factor for interspecies toxicokinetic differences would be to use the ratio of rat and 

21 human external doses resulting in the same level of target tissue exposure at the POD. 

22

23 Using the data described above (see Section 3.2.2.2), these data indicate a DDEF value 

24 for interspecies toxicokinetic extrapolation of 0.13 ÷ 0.09 = 1.44. Combined with the default 

25 value of 3 for toxicodynamics, a DDEF for interspecies extrapolation (UFA) would be 1.44 * 3 = 

26 4.32, in place of the default value of 10. By applying the DDEF calculated above (4.32-fold) and 

27 the 10-fold intraspecies UF to the animal NOAEL (0.13 mg/kg-d), the RfD is 0.13 mg/kg-d ÷ 

28 43.2 = 0.003 mg/kg-d. This is the same value that was calculated for the IRIS assessment, which 

29 was expressed as the HED/UF, or 0.09 mg/kg-d/30 (U.S. EPA, 2000).

30

31 The above methods can also be compared to the default methodology that is based on 

32 body weight scaling (U.S. EPA, 2006). Using a default value of 0.462 kg for adult Wistar rats 

33 (U.S. EPA, 1988) and applying the body weight scaling approach (U.S. EPA, 2006) to the 

34 NOAEL of 0.13 mg/kg-d, a HED can be calculated as:

35

36 0.13 mg/kg-d * 0.462 kg = 0.060 mg

0.06 mg * (70kg ÷ 0.462kg)3/4 37 = 

38 0.06 mg * 43.19 = 2.59 mg

39 2.59 mg ÷ 70 kg = 0.037 mg/kg-d

40

41 In this case study, the body weight scaling default approach yields a slightly lower POD 

42 value than the data derived approaches described above. Furthermore, this approach makes use 

43 of quantitative data on VC.

44

45

Rat

External

Dose

Rat

PBPK

Model

Identify 

NOAEL

as POD

Express 

POD as 

Dose Metric

Human

PBPK

Model

Human

Equivalent

Dose

0.13 mg/kg-d 3 mg metabolite

per L liver 0.09 mg/kg-d

Rat

External

Dose

Rat

PBPK

Model

Identify 

NOAEL

as POD

Express 

POD as 

Dose Metric

Human

PBPK

Model

Human

Equivalent

Dose

0.13 mg/kg-d 3 mg metabolite

per L liver 0.09 mg/kg-d

Rat

External

Dose

Rat

PBPK

Model

Identify 

NOAEL

as POD

Express 

POD as 

Dose Metric

Human

PBPK

Model

Human

Equivalent

Dose

Rat

External

Dose

Rat

PBPK

Model

Identify 

NOAEL

as POD

Express 

POD as 

Dose Metric

Human

PBPK

Model

Human

Equivalent

Dose

0.13 mg/kg-d 3 mg metabolite

per L liver 0.13 mg/kg-d 0.09 mg/kg-d 3 mg metabolite

per L liver 0.09 mg/kg-d
May 11, 2011 9 DRAFT: DO NOT CITE OR QUOTE

1 References

2

Andersen, M.E., H.J. Clewell 3rd 3 , M.L. Gargas, F.A. Smith and R.H. Reitz. 1987. 

4 Physiologically based pharmacokinetics and the risk assessment process for methylene chloride. 

5 Toxicol. Appl. Pharmacol. 87(2):185-205.

6 Bi, W.F., Y.S. Wang, M.Y. Huang and D.S. Meng. 1985. Effect of vinyl chloride on tests in 

7 rats. Ecotoxicol. Environ. Saf. 10(3):281-289. 

8 Bolt, H.M. 1978. Pharmacokinetics of vinyl chloride. Gen. Pharmacol. 9:91-95. 

9 Clewell, H.J., P.R. Gentry, J.M. Gearhart et al. 1995a. The development and validation of a 

10 physiologically based pharmacokinetic model for vinyl chloride and its application in a 

11 carcinogenic risk assessment for vinyl chloride. ICF Kaiser report prepared for EPA/OHEA and 

12 OSHA/DHSP. 

13 Clewell, H.J., T.R. Covington, K.S. Crump et al. 1995b. The application of a physiologically 

14 based pharmacokinetic model for vinyl chloride in a noncancer risk assessment. ICF/Clement 

15 report prepared for EPA/NCEA under contract number 68-D2-0129. 

16 Feron, V.J., C.F.M. Hendriksen, A.J. Speek, H.P. Til and B.J. Spit. 1981. Lifespan oral toxicity 

17 study of vinyl-chloride in rats. Food Cosmetol. Toxicol. 19(3):317-333.

18 Guengerich, F.P., P.S. Mason, W.T. Stott et al. 1981. Roles of 2-haloethylene oxides and 

19 2-haloacetaldehydes derived from vinyl bromide and vinyl chloride in irreversible binding to 

20 protein and DNA. Cancer Res. 41:4391-4398. 

21 ILSI (International Life Sciences Institute). 1997. An evaluation of epa’s proposed guidelines 

22 for carcinogen risk assessment using chloroform and dichloroacetate as case studies. Report of 

23 ILSI HESI Expert Panel. International Life Sciences Institute, Washington, DC. 

24 Til, H.P., H.R. Immel and V.J. Feron. 1983. Lifespan oral carcinogenicity study of vinyl 

25 chloride in rats. Final report. CIVO Institutes, Division for Nutrition and Food Research, TNO. 

26 The Netherlands: Netherlands Organization for Applied Scientific Research. TNO Report No. 

27 V 83.285/291099, TSCATS Document FYI-AX-0184-0353, Fiche No. 0353. 

28 Til, H.P., V.J. Feron and H.R. Immel. 1991. Lifetime (149-week) oral carcinogenicity study of 

29 vinyl chloride in rats. Food Chem. Toxicol. 29:713-718. 

30 U.S. EPA (U.S. Environmental Protection Agency). 1988. Recommendations for and 

31 documentation of biological values for use in risk assessment. Environmental Criteria and 

32 Assessment Office, Cincinnati, Ohio. EPA/600/6-87/008, February, 1988. Available at 

33 http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=34855. 

34 U.S. EPA (U.S. Environmental Protection Agency). 2000. IRIS Summary file and 

35 Toxicological Review for Vinyl Chloride. Integrated Risk Information System, Washington, 

36 DC. Available at http://www.epa.gov/ncea/iris/subst/1001.htm (accessed 9/10/2008).
May 11, 2011 10 DRAFT: DO NOT CITE OR QUOTE

1 U.S. EPA (U.S. Environmental Protection Agency). 2006. Harmonization in Interspecies 

Extrapolation: Use of BW3/4 2 as Default Method in Derivation of the Oral RfD (External Review 

3 Draft). Risk Assessment Forum Technical Panel, Washington, DC. EPA/630/R-06/001. 

4 Available at http://cfpub.epa.gov/ncea/cfm/recordisplay.cfm?deid=148525.

5

6 INTERSPECIES ADJUSTMENT FOR TOXICODYNAMICS

7

8 Ethylene Glycol Monobutyl Ether (EGBE)—EFAD Case Study

9

10 Summary

11 Ethylene glycol monobutyl ether (EGBE; 2-butoxy ethanol) has an established RfD of 

12 0.1 mg/kg-d on the U.S. EPA’s Integrated Risk information System (IRIS) database (U.S. EPA, 

13 2010). This value is based on the results of a subchronic drinking water study in mice and rats 

14 where increases in Kupffer cell hemosiderin content secondary to hemolysis were determined to 

15 be the critical effect. Derivation of the HED of 1.4 mg/kg-d is detailed in the EGBE TK case 

16 study earlier in this appendix and in the IRIS file for EGBE (U.S. EPA, 2010a,b).

17

18 As described below, the IRIS RfD is based on a PBPK modeling approach that identified 

19 an HED of 1.4 mg/kg-d. Uncertainty factors were applied to this POD value to derive the RfD. 

20

21 A total UF of 10 was applied to this HED to derive the RfD. A default value of 10 was used to 

22 account for variation in sensitivity within the human population (UFH). UFA was reduced to 1 on 

23 the basis of dosimetry adjustments to account for TK (discussed in EGBE case study earlier in 

24 this appendix). EFAD was also reduced to a value of 1, because studies indicate that humans may 

25 be significantly less sensitive than rats to the hematological effects of EGBE. In this case study, 

26 issues associated with EGBE TD are described and an alternative approach to DDEF derivation 

27 based on the use of in vitro data are described.

28

29 Hazard Identification and Dose Response 

30

31 Based on extensive review of the literature, hematologic effects appear to be the most 

32 sensitive of the adverse effects observed in laboratory animals exposed to EGBE. Hematologic 

33 effects (e.g., hemoglobinuria) have also been documented in worker populations exposed to 

34 technical grade EGBE (Cellosolve) and following ingestion of cleaning products containing 

35 EGBE (U.S. EPA, 2010). 

36

37 Key events in the proposed mode of action in erythrocytes leading to increases in 

38 hemoglobin accumulation in Kupffer cells include:

39

40 • Oxidative metabolism to butoxyacetic acid (BAA)

41 • Erythrocyte swelling and lysis (probably preceded by an increase in osmotic fragility and 

42 loss of deformability)
May 11, 2011 11 DRAFT: DO NOT CITE OR QUOTE

1 • Decreased erythrocyte count, hemoglobin, and hematocrit, and in response, increased 

2 production of immature erythrocytes (reticulocytes) by the bone marrow

3

4 Carpenter et al. (1956) incubated erythrocytes from rats, mice, rabbits, monkeys, dogs, 

5 humans and guinea pigs with 0.1% butoxyacetic acid (BAA). Results demonstrating maximum 

6 time without hemolysis were 35-40, 40-45, 60-90, 103-120, 147-268 and 360 minutes, 

7 respectively. These data indicate that guinea pigs and humans are more resistant and that rats 

8 and mice may be more sensitive to the hemolytic effects of BAA. Studies with Cellosolve and 

9 BAA demonstrated that RBC were much more sensitive to BAA than Cellosolve. These results 

10 led Carpenter et al. (1956) to speculate that the BAA metabolite of Cellosolve was responsible 

11 for hemolysis. 

12 In a direct comparison of the effects of BAA on rat and human erythrocytes, Udden and 

13 Patton (1994) devised a study using filtration, phase contrast light microscopy and routine 

14 hematologic methods. RBC were obtained from healthy adults via venipuncture and from 9-11 

15 week old male Fischer 344 rats via cardiac puncture. Rat RBCs were incubated with 0.2 and 2.0 

16 mM BAA; human erythrocytes were incubated with 2.0 mM BAA only. Rat RBC demonstrated 

17 30% hemolysis after incubation with 2.0 mM BAA for 4 hours, and 4% hemolysis after 

18 incubation with 0.2 mM BAA for 6 hours or longer. The 4% measure was “mild,” and the data 

19 were not shown. Incubation of human RBC with 2.0 mM BAA for 4 hours resulted in no 

20 increase in hemolysis over the background (control) level of 1%. Histologic evaluations of rat, 

21 but not human RBC preparations post-exposure demonstrated erythrocyte “ghosts,” which are 

22 cell membranes from lysed cells. These incubation conditions resulted in increases in mean 

23 corpuscular volume (MCV) in rat RBC incubated with 0.2 mM BAA, but not human RBC 

24 incubated with 2.0 mM BAA. The increase in MCV is indicative of swelling of RBCs, an event 

25 which leads to fragility. 

26

27 Finally, these investigators examined the deformability of RBC by pumping them 

28 through a narrow-diameter filter and monitoring an increase in inflow pressure. The results were 

29 presented graphically, as pressure versus time plots. The logic behind this study was that while 

30 RBC normally can deform to pass through tight spaces (like in capillaries), RBC in which 

31 swelling has been induced and in which other mechanisms may lead to increased membrane 

32 rigidity, the passage through the membrane pores will be limited, resulting in an increase in 

33 inflow pressure. Rat erythrocytes demonstrated a roughly tripled pressure when incubated with 

34 2.0 mM BAA for 4 hours compared to controls, and pressure was nearly doubled in rat RBC

35 incubated with 0.2 mM BAA for 4 hours. In contrast, pressure differences between human RBC 

36 incubated in the absence of BAA and in the presence of 2.0 mM BAA for 4 hours were not 

37 distinguishable. These authors indicated that their findings that human RBCs were less sensitive 

38 in vitro to the hemolytic effects of BAA were consistent with multiple other findings. In a 

39 follow-on study, Udden (2002) demonstrated again that human erythrocytes were less 

40 susceptible to the effects of BAA than erythrocytes from rats. Whereas rat erythrocytes 

41 demonstrated alterations of RBC including deformability and changes in MCV at 0.05 mM, 

42 human erythrocytes did not demonstrate changes in MCV at concentrations reached below 10 

43 mM – a difference of 200-fold. 

44

45 Ghanayem and Sullivan (1993) also performed a species comparison of BAA-induced 

46 RBC effects in vitro. An advantage of this study is the application of pairwise statistical design 
May 11, 2011 12 DRAFT: DO NOT CITE OR QUOTE

1 to determine the effect of treatment over control. Male Fischer 344 rats 15 weeks of age were 

2 used, and human blood was drawn from adult male donors. BAA (2.0 mM incubated up to 

3 4 hours) produced only slight, but not statistically significant alterations of hematological 

4 parameters: hematocrit was increased 2-4% and MCV was increased less than 4% above vehicle 

5 controls. The authors concluded that their results demonstrated that humans were “minimally 

6 sensitive” to the in vitro effects of BAA. In comparison, RBC from rats were deemed “relatively 

7 susceptible” to the effects of BAA. A graphic presentation of data demonstrated that in rats, 

8 MCV and hematocrit were increased nearly 60% when exposed to 2.0 mM BAA.

9

10 Udden (2002) compared the sub-hemolytic and hemolytic effects of BAA in rat and 

11 human RBCs. Erythrocyte deformability, density, MCV, count, osmotic fragility, and hemolysis

12 were measured following a four-hour exposure. Alterations were noted in loss of deformability, 

13 but at concentrations that were 150-fold higher in rat erythrocytes than in human erythrocytes 

14 (0.05 mM versus 7.5 mM). A larger species-difference in response was noted in comparing 

15 effect levels for increases in MCV – these differences approximated 200-fold, with rat 

16 erythrocytes responding at 0.05 mM and human erythrocytes demonstrating alterations of MCV 

17 at 10 mM. Changes in osmotic fragility were similar. 

18

19

20 Basis for DDEF 

21

22 Several data sets are available in which the responsiveness of rat and human blood at 2 

23 mM can be compared. However, comparison of effect data for TD is most appropriately 

24 accomplished by comparing the different concentrations resulting in the same response.

25

26 Hemolytic effects were observed in rat erythrocytes exposed to BAA at concentrations as 

27 low as 0.05 mM. In contrast, similar hemolytic effects were observed in human blood exposed 

28 to 10 mM BAA. The IRIS file indicates that humans may be much less sensitive than rats to the 

29 hematologic effects EGBE, and for this reason a value of 1 was selected for the toxicodynamic 

30 component of the interspecies uncertainty factor. 

31

32 DDEF Derivation

33

34 One potential approach would be to derive an adjustment factor of 0.005 for UFA-TD

35 (0.05 mM/10 mM = 0.005). This approach requires the assumption that the TD differences 

36 observed in vitro would be approximated in vivo. Uncertainty regarding this issue prompted 

37 EPA to take a different approach. In the IRIS assessment (U.S.EPA, 2000b), the UF value for 

38 UFA-TD was established at 1: 

39

40 Regarding toxicodynamics, in vivo (Carpenter et al., 1956) and in vitro (Ghanayem and Sullivan, 1993; Udden, 

41 2002; Udden and Patton, 1994) studies indicate that humans may be significantly less sensitive than rats to the 

42 hematological effects of EGBE. For this reason, a value of 1 was selected for the toxicodynamic portion of the UFA. 

43

44 References

45

Carpenter, C.P., G.A. Keck, J.H. Nair 3rd 46 , U.C. Pozzani, H.F. Smyth Jr. and C.S. Wiel. 1956. 

47 The toxicity of butyl cellosolve solvent. AMA Arch. Ind. Health. 14(2):114-131. 
May 11, 2011 13 DRAFT: DO NOT CITE OR QUOTE

1 Ghanayem, B.I. and C.A. Sullivan. 1993. Assessment of the hemolytic activity of 

2 2-butoxyethanol and its major metabolite, butoxyacetic acid, in various mammals including 

3 humans. Hum. Exp. Toxicol. 12(4):305-311.

4 Udden, M.M. 1994. Hemolysis and decreased deformability of erythrocytes exposed to 

5 butoxyacetic acid, a metabolite of 2-butoxyethanol: II. Resistance in red blood cells from 

6 humans with potential susceptibility. J. Appl. Toxicol. 14(2):97-102. 

7 Udden M.M. 2002. In vitro sub-hemolytic effects of butoxyacetic acid on human and rat 

8 erythrocytes. Toxicol Sci, 69: 258-264.

9 U.S. EPA (U.S. Environmental Protection Agency). 2010a. Toxicological Review of Ethylene 

10 Glycol Monobutyl Ether (EGBE) CAS No. 111-76-2. In support of Summary Information on the 

11 IRIS System. IRIS (Integrated Risk Information System), Washington, DC. Available at 

12 http://www.epa.gov/ncea/iris/toxreviews/0500tr.pdf (accessed 8/18/2010).

13 U.S. EPA (U.S. Environmental Protection Agency). 2010b. IRIS Summary Sheets for Ethylene 

14 Glycol Monobutyl Ether (EGBE). Reference Concentration for Chronic Inhalation Exposure. 

15 Available online at http://www.epa.gov/ncea/iris/subst/0500.htm (accessed 8/18/2010). 

16

17

18 Dimethyl Arsenic Acid (DMA)—EFAD Case Study

19

20 1. Summary

21

22 Dimethyl arsenic acid (DMA), also known as cacodylic acid, is an herbicide used on 

23 primarily cotton and turf. DMA is also a urinary metabolite in most mammals, including 

24 humans, following direct exposure to inorganic arsenic. The Office of Pesticide Programs, in 

25 collaboration with NHEERL scientists, developed a non-linear mode of action assessment for 

26 DMA for the development of rat bladder tumors (U.S. EPA, 2006). The MOA and dose27 response assessments were developed using the MOA and Human Relevance Frameworks. The 

28 information provided by the mode of action analysis also provides the basis for the chronic RfD 

29 and the respective UFs in the Registration Eligibility Decision (RED) for cacodylic acid. Instead 

30 of the default 10-fold factor to extrapolation from animal to human, OPP has reduced the TD 

31 component of UFA (EFAD)to 1X. This case study describes the determination of the 3X factor 

which was used to account for toxicodynamic differences between animals and humans. 32 The 

33 default UFH of 10X factor was also applied leading to a composite factor of 30X.

34

35 2. Hazard Identification and Dose-Response

36

In rat carcinogenicity studies, oral exposure to DMAV 37 leads to bladder tumors. The 

38 overall weight of the evidence provides convincing support for a non-linear mode of action for 

DMAV 39 -induced carcinogenesis in rodents. The key events include:

40

• Reductive metabolism of DMAV to DMAIII 41 . 
May 11, 2011 14 DRAFT: DO NOT CITE OR QUOTE

• DMAIII 1 causes urothelial cytotoxicity. Regenerative cell proliferation then ensues in 

2 order to replace dead urothelial cells. The amount of cell killing is a function of the 

severity of the cytotoxicity which is related to the amount of DMAIII 3 present. The 

amount of DMAIII is dependent on the conversion of DMAV to DMAIII 4 .

5 • Sustained cytotoxicity leads to regenerative cell proliferation which, in turn, ultimately 

6 leads to hyperplasia and bladder tumors.

7

8 To obtain a tumor via the proliferation/replication genetic error process, induced cell 

9 proliferation needs to be persistent. There is convincing experimental evidence to indicate that 

this is the case for the rat bladder. There is a clear association of DMAV 10 treatment and cell 

11 killing/regenerative proliferation and bladder tumors. The amount of proliferation would be a 

12 function of the amount of cell killing since the tissue will undergo regenerative proliferation in 

response to cell killing. As the severity of cytotoxicity increases with increasing levels of DMAV 13

(DMAIII 14 ), regenerative proliferation is the rate limiting step for tumor formation, even though the 

15 product is chromosome mutations. Thus, a tumor dose-response curve would be influenced by 

16 the induced cell proliferation curve, even though chromosomal mutations may be an output. 

DMAV 17 -induced tumors would only be produced at treatment durations and dose levels that result 

18 in significant cell killing and regenerative cell proliferation in the urothelium of the bladder. 

19 Experimental data are available to support the coincidence of key events at similar concentration 

levels. The levels of DMAIII in the urine of rats treated with 100 ppm DMAV 20 range from 

0.5-5.0uM. The LC50 values for DMAIII 21 in rat and human urinary epithelial cells in vitro are 

22 0.5-0.8uM. There is a significant increase in chromosome aberrations in human lymphocytes in 

vitro at about 1.35 μM DMAIII 23 . At 100 ppm, there is significant cell killing and regenerative 

24 proliferation in female rat bladders. It appears that chromosomal mutations, cytotoxicity and cell 

proliferation can potentially occur concurrently at 100 ppm DMAV 25 , the tumorgenic dose in 

26 female rats via the feed.

27

28 Among the several key events, all of which are necessary for tumor formation, cell 

29 proliferation has been used for deriving a point of departure because it is needed for increasing 

30 the likelihood of chromosome mutation formation and for the perpetuation of genetic errors, as 

31 well as for hyperplasia. A BMDL10 value (0.43 mg/kg bw/day) is the basis for the point of 

32 departure in deriving reference dose or a margin of exposure. This approach is considered public 

33 health protective because a BMDL10 of 0.43 mg/kg bw/day is approximately an order of 

34 magnitude lower than the dose (~0.7 mg/kg bw/day or 10 ppm) that resulted in a 1.5-fold 

nonstatistical increase in cell proliferation after 10 weeks of exposure to DMAV 35 and about two 

36 orders of magnitude lower than the dose (~9.4 mg/kg bw/day) resulting in neoplasia in the 

37 feeding studies. 

38

39 3. Basis for DDEF

40

41 In the 2006 DMA risk assessment, instead of the default 10-fold factor to extrapolate 

42 from animal to human, OPP has reduced the TD component to 1X. A 3X factor was used to 

43 account for interspecies differences in toxicokinetics. UFA-TD was reduced to 1X given that at a 

44 similar dose at the target site (i.e., bladder urothelial), that humans and rats are expected to 

45 respond pharmacodynamically similar. This case is built on a combination of information: 
May 11, 2011 15 DRAFT: DO NOT CITE OR QUOTE

1

2 • Chemical-specific in vitro data from Cohen et al. (2002) which show that human and rats 

cell respond similarly to exposure to DMA 3 III—the LC50s for cytotoxicity in human and 

4 rat epithelial cells were very similar (0.8 μM and 0.5 μM, respectively).

5 • There are microarray support (Sen et al., 2005). Qualitatively the genes up-regulated in 

6 human urinary bladder epithelial (UROtsa) are similar to those up-regulated in rat urinary 

bladder epithelial cells (MYP3) exposed to DMAV 7 in vitro. In this study, the rat cell line 

8 was quantitatively more sensitive compared to the human cell line. 

9 • General information on the development and function of the bladder along with incidence 

10 of bladder tumors in human populations qualitatively supports the animal mode of action 

11 in humans. 

12

13 There are known pharmacokinetic differences between rats and humans. These 

pharmacokinetic differences include: sequestration of DMAIII 14 by rat hemoglobin which results in 

15 a long retention time in the rat compared to humans or mice, and the increased urinary output of 

16 TMAO in rats compared to humans. Because of uncertainties regarding quantifying the tissue 

17 dose in humans using rat data, and in the absence of a fully developed PBPK model at the time 

18 of the risk assessment, an inter-species extrapolation factor of 3X was applied. Pharmacokinetic 

19 analyses indicate that for similar chronic low level exposures, rats would take longer to achieve 

steady state concentrations of DMAV 20 and metabolites in target tissue compared to humans and 

21 that for a given exposure target tissue concentrations would be elevated for a longer time after 

22 exposure ceased in the rat because rat hemoglobin acts as a slow release storage depot. Note that

half-life in the rat for DMAV 23 appears to correlate with erythrocyte half-life, indicating that the 

24 binding to hemoglobin is not readily reversible. There are, however, uncertainties regarding the 

25 quantitative differences between rat and human which prevents further reduction of the inter26 species factor. 

27

28 4. DDEF Derivation

29

30 A value of 1X was developed for EFAD based on the bullets above in combination with 

31 the animal MOA and implementation of the Human Relevance Framework. Together, the 

32 weight of the evidence provides a strong case for TD equivalence between rats and humans. A 

33 3X factor was used to account for interspecies differences in toxicokinetics. The default UFH of 

34 10X factor was also applied leading to a composite factor of 30X

35

36 References

37

38 Cohen, S.M., L.L. Arnold, E. Uzvolgyi et al. 2002. Possible role of dimethylarsinous acid in 

39 dimethylarsinic acid-induced urothelial toxicity and regeneration in the rat. Chem. Res. Toxicol. 

40 15(9):1150-1157. 

41 Sen, B., R. Grindstaff, Y. Turpaz, J. Retief and D. Wolf. 2005. Gene expression to identify 

42 interspecies concordance of the mechanisms of arsenic induced bladder cancer. Presented at the 

43 Society of Toxicology Annual Meeting. New Orleans, Louisiana. March 2005.
May 11, 2011 16 DRAFT: DO NOT CITE OR QUOTE

1 U.S. EPA (U.S. Environmental Protection Agency). 2006. Revised Science Issue Paper: Mode 

2 of Carcinogenic Action for Cacodylic Acid (Dimethylarsinic Acid, DMAV) and 

3 Recommendations for Dose Response Extrapolation. January 30, 2006. Health Effects Division, 

4 Office of Pesticide Programs, US Environmental Protection Agency. Available at 

5 http://www.regulations.gov/fdmspublic/component/main?main=DocumentDetail&o=090000648

6 015262b. 

7

8

9 N-methyl Carbamate Pesticides (NMCs)—EFAD Case Study

10

11 Summary

12

13 The Office of Pesticide Programs released its revised cumulative risk assessment for the 

14 N-methyl carbamates (NMCs) in 2007 (U.S. EPA, 2007). As required under the Food Quality 

15 Protection Act (FQPA, 1996), a cumulative risk assessment incorporates exposures from 

16 multiple pathways (i.e., food, drinking water, and residential/non-occupational exposure to 

17 pesticides in air, or on soil, grass, and indoor surfaces) for those chemicals with a common 

18 mechanism of toxicity. A cumulative risk assessment begins with the identification of a group of 

19 chemicals, called a Common Mechanism Group (CMG), which induces a common toxic effect 

20 by a common mechanism of toxicity. The NMCs were considered to be a CMG due to their 

21 common inhibitory actions on acetylcholinesterase, an enzyme that is normally required for 

22 ending cholinergic transmission in the nervous system. 

23

24 This case study describes a sensitivity analysis conducted in the risk characterization 

25 phase of the revised CRA using a DDEF approach. TD equivalence for animal to human 

26 extrapolation (EFAD = 1X) was assumed for several chemicals for which human data were not 

27 available.

28

29 Hazard Identification and Dose Response

30

31 The NMCs were established as a CMG by U.S. EPA in 2001 (U.S. EPA, 2001) based on 

32 their similar structural characteristics and shared ability to inhibit acetylcholinesterase (AChE) 

33 by carbamylation of the serine hydroxyl group located in the active site of the enzyme. When 

34 AChE is inhibited, acetylcholine accumulates and results in cholinergic toxicity, due to 

35 continuous stimulation of cholinergic receptors throughout the central and peripheral nervous 

36 systems that innervate virtually every organ in the body. An important aspect of NMC toxicity is 

37 the rapid nature of the onset and recovery of effects; following maximal inhibition of 

38 cholinesterase (typically between 15 and 45 minutes), recovery occurs rapidly (minutes to 

39 hours). 

40

41 Inhibition of AChE is considered the first and critical step in the toxicity of NMCs. 

42 Human health monitoring has capitalized on the availability of blood cholinesterase 

43 measurements, and these have been widely accepted as a marker of exposure. However, since 

44 the brain AChE may be considered more as the critical target site, data on inhibition of brain 

45 AChE are obviously only available using laboratory animals. Brain AChE data have been 

46 widely used as a point of departure for risk assessment.
May 11, 2011 17 DRAFT: DO NOT CITE OR QUOTE

1 U.S. EPA used the relative potency factor (RPF) method to determine the combined risk 

2 associated with exposure to NMCs. Briefly, the RPF approach uses an index chemical as the 

3 point of reference for comparing the toxicity of the NMC pesticides. RPFs are calculated as the 

4 ratio of the toxic potency of a given chemical to that of the index chemical and are used to 

5 convert exposures of all chemicals in the group into exposure equivalents of the index chemical. 

6 Because of its high quality dose response data for all routes of exposure, as well as high quality 

7 time-to-recovery data, U.S. EPA selected oxamyl as the index chemical for standardizing the 

8 toxic potencies and calculating relative potency factors for each NMC pesticide. 

9

10 Basis for a DDEF

11

12 In the single chemical assessments for most NMCs, a default 10X factor for animal-to13 human extrapolation was used. For three NMCs (aldicarb, methomy and oxamyl), however, 

14 there are studies in human subjects that were determined by U.S. EPA, after considering the 

15 advice of the Human Studies Review Board, to be ethically and scientifically acceptable for use 

16 in risk assessment. These studies were used to derive the chemical-specific inter-species 

17 extrapolation factor for these three chemicals. Table 2 summarizes the dose-response and time18 course modeling data for critical rat and human studies for these three NMCs.

19

20 Table 2. NMC CRA: Inter-species Extrapolation Factors and Corresponding Rat and Human 

21 BMD10s and BMDL10s 

22

Chemical

Rat Human

Interspecies 

UF

Brain RBC RBC

BMD10

(mg/kg)

BMDL10

(mg/kg)

1⁄2 

life 

(hrs)

BMD10

(mg/kg)

BMDL10

(mg/kg)

1⁄2 

life 

(hrs)

BMD10

(mg/kg)

BMDL10

(mg/kg)

1⁄2 

life 

(hrs)

Aldicarb F = 0.048

M = 0.056

F = 0.035

M = 0.035 1.5 0.031 0.020 1.1 0.016 0.013 1.7 2X

Methomyl 0.486 0.331 1.0 0.204 0.112 0.8 0.040 0.028 1.6 5X

Oxamyl F = 0.145

M = 0.185

F = 0.111

M = 0.143 0.9 0.278 0.158 0.8 0.083 0.068 2.4 3X

23

24

25 With regards to the EFAK, NMCs have similar metabolic profiles across species. NMCs 

26 do not require activation; the parent compound is an active AChE inhibitor. Although some 

27 metabolites of NMCs have been shown to be active as well, none have been shown to be more 

28 potent than the parent chemical. Thus, metabolism is considered to be a detoxification process. 

29 As such, species differences in tissue dosimetry are likely correlated with differences in body 

30 weight to the 3⁄4 power and are also consistent with a 3X factor to account for inter-species 

31 differences in toxicokinetics (U.S. EPA, 2006). 

32
May 11, 2011 18 DRAFT: DO NOT CITE OR QUOTE

1 The mechanism of toxic action of NMCs is reproducible across a range of species, 

2 including rodents and humans. In addition, the AChE enzyme in humans and rats has similar 

3 function and structure (see reviews by Radic and Taylor, 2006; Sultatos, 2006). The half-life to 

recovery values1 4 for rats and humans provided in Table 2 range from approximately 1 to 2 hours

5 and demonstrate the similarity of the half-lives of the two species. Based on this information, 

6 given a similar dose or concentration at the target site, it is likely that human and rat AChE 

7 would respond similarly. This understanding can inform the interspecies DDEF (EFAD).

8

9 DDEF Derivation

10

11 For the CRA, toxic potencies for the NMCs were determined using brain AChE

12 inhibition measured at peak inhibition following gavage exposures in rats. The Agency used an 

13 exponential dose-time-response model to develop benchmark dose estimates at a level estimated 

14 to result in 10% brain cholinesterase inhibition (i.e., a benchmark dose or BMD10) to estimate 

15 relative potency. Ratios comparing doses (administered) that produce the same magnitude of 

16 effect may then be derived. Using the data in Table 2, and dividing the BMD10-rat by the 

17 BMD10-human for RBD cholinesterase inhibition:

18

19 Aldicarb: 0.031 ÷ 0.016 = 1.9 ≈ 2

20 Methomyl: 0.204 ÷ 0.040 = 5.1 ≈ 5

21 Oxamyl: 0.278 ÷ 0.083 = 3.3 ≈ 3

22

23 This analysis showed that the ratio of the BMDs for rat/human ranges from 2 to 5 for 

24 these NMCs. This range would tend to support the DDEF approach described here to reduce the

25 standard 10X inter-species factor to 3X. The concentration of toxicant at the active site in vivo is 

26 controlled by toxicokinetic processes. The available data described TD processes (enzyme 

27 regeneration) and indicated that rats and humans were very similar in this area. The remaining 

28 three-fold (default) value for UFA addresses species differences in toxicokinetics. 

29

30 It may be possible to use in vitro studies using human and rat tissues and human and rat 

31 AChE to test this hypothesis. In other words, it may be possible to use in vitro studies to 

32 demonstrate toxicodynamic equivalence between rats and humans. If these data were available 

33 and they showed toxicodynamic equivalence, the Agency could reduce the inter-species factor 

34 for those NMCs without human toxicity studies to 3X. Because of the lack of these in vitro

35 studies, the Agency does not believe it appropriate at this time to further refine the standard 10X 

36 factor for inter-species extrapolation. Instead, the Agency has used the DDEF approach as a 

37 sensitivity analysis in its risk characterization. 

38

39 In this sensitivity analysis, the 10X inter-species factor was reduced to 3X based on the 

40 assumption of toxicodynamic equivalence for carbaryl, carbofuran, and formetanate HCl. These 

41 three NMCs were identified since they were shown in the CRA to contribute a large portion of 

 1 Recovery half-life differs from elimination half-life. While elimination half-life is not an acceptable basis for 

calculation of a DDEF for toxicokinetic components, enzyme regeneration measurements (the subject of the present 

analysis) are also expressed in half-life values. This usage refers to regeneration of enzymatic activity or de novo 

synthesis of additional enzyme (protein). In this instance, “half-life” measures are an adequate basis for derivation 

of DDEF values for toxicodynamic events.
May 11, 2011 19 DRAFT: DO NOT CITE OR QUOTE

1 the estimated human exposure to the cumulative risk to this group. The results of this sensitivity 

2 analysis for the food exposure assessment are shown below in Table 3. The Agency has used a 

3 probabilistic approach to the food exposure assessment. The estimated exposures of the NMC as 

a group (i.e., oxamyl equivalents) and the margins of exposure (MOE) at the 99.9th 4 percentile are 

5 shown here. The target MOE is 10 or higher for intra-species extrapolation. The table compared 

6 the MOEs when using the standard UF to those obtained with the modified UFA.

7

8

9 Table 3. Sensitivity Analyses NMC Cumulative Food Assessment: DDEF Approach for Inter10 species UF

11

Age Group

Estimated Exposure 

at the 99.9th

Percentile (mg/kg 

oxamyl equivalents)

MOE at the 

99.9th

Percentile

Percentile at 

Which Target of 

10 is Reached

Baseline CRA Children 1-2 0.0229 7.9 99.848th

Children 3-5 0.0209 8.6 99.870th

DDEF Approach 

for Inter-species UF

Children 1-2 0.0183 9.8 99.896th

Children 3-5 0.0171 10.5 N/A

12

13

14 Review of this table shows that:

15

16 • Using the standard 10X inter-species factor for all NMCs without human data, the 

(baseline) MOEs at the 99.9th 17 percentile of exposure are less than 10 for children 1-2 and 

3-5 years. Furthermore, they reach the target of 10 at the 99.848th and 99.870th 18

19 percentiles of exposures. 

20 • When considering an alternative approach to the inter-species factor which assumes a 3X 

inter-species factor for carbaryl, carbofuran, and formetanate HCl, the MOEs at 99.9th 21

22 percentile of exposure increase to 9.8 and 10.5 for children 1-2 and 3-5 years—a 20% 

23 increase in MOEs. The exposure for the younger age group reaches the target MOE of 

10 at the 99.896th 24 percentile of exposures. 

25

26 This sensitivity analysis suggests an opportunity where additional data would provide a 

27 substantial improvement in the refinement of the CRA. 

28

29 References

30

31 FQPA (Food Quality Protection Act). 1996. Food Quality Protection Act of 1996 (FQPA) 

32 Public Law 104–170—AUG. 3, 1996. Available at 

33 http://www.epa.gov/pesticides/regulating/laws/fqpa/gpogate.pdf (accessed 9/12/2008).
May 11, 2011 20 DRAFT: DO NOT CITE OR QUOTE

1 Radić, Z. and P. Taylor. 2006. Structure and function of cholinesterases. In: Toxicology of 

2 Organophosphate and Carbamate Compounds, R.C. Gupta, Ed. Elsevier Academic Press, 

3 Burlington, MA. p 161-186

4 Sultatos, L. 2006. Interactions of organophosphorus and carbamate compounds with 

5 cholinesterases. In: Toxicology of Organophosphate and Carbamate Compounds, R.C. Gupta, 

6 Ed. Elsevier Academic Press: Burlington, MA. p. 209-218.

7 U.S. EPA (U.S. Environmental Protection Agency. 2001. Memorandum from Marcia Mulkey 

8 to Lois Rossi. “Implementation of the Determinations of a Common Mechanism of Toxicity for 

9 N_Methyl Carbamate Pesticides and for Certain Chloroacetanilide Pesticides.” July 12, 2001. 

10 Available at http://www.epa.gov/oppfead1/cb/csb_page/updates/carbamate.pdf (accessed 

11 9/12/2008).

12 U.S. EPA (U.S. Environmental Protection Agency. 2006. DRAFT Harmonization in 

13 Interspecies Extrapolation: Use of BW3/4 as Default Method in Derivation of the Oral RfD. 

14 Risk Assessment Forum Technical Panel, Washington, DC.

15 U.S. EPA (U.S. Environmental Protection Agency). 2007. N-Methyl Carbamate Revised 

16 Cumulative Risk Assessment. U.S. Environmental Protection Agency, Office of Pesticide 

17 Programs, Washington, DC. Available online at 

18 http://www.epa.gov/pesticides/cumulative/carbamate_fs.htm. Last updated September 24, 2007.

19

20

21 INTRASPECIES ADJUSTMENT FOR TOXICOKINETICS—

22 (EFHK)

23

24 Boron and Compounds

25

26 Summary

27

28 In the U.S. EPA IRIS file for Boron and Compounds (posted 2004), an RfD value of 2X

10-1 29 mg/kg-d has been developed based on the critical developmental effect of decreased fetal 

30 weights (U.S. EPA, 2004). The point of departure for the derivation of this value is the BMD L05

31 value of 10.3 mg/kg-d. The BMD L05 is based on the combined results of two studies chosen for 

32 the derivation of the RfD (Heindel et al., 1992; Price et al., 1994, 1996). Using data from rats 

33 (Vaziri et al., 2001) and humans (Pahl et al., 2001), a mathematical model was applied to the TK 

34 component of the interspecies extrapolation factor to address interspecies toxicokinetics. The 

35 interspecies toxicokinetic adjustment factor was 3.3. An intra-human kinetic adjustment factor 

36 of 2.0 was estimated from three studies (Dunlop, 1981; Krutzén et al., 1992; Sturgiss et al., 

37 1996), using glomerular filtration rate as a surrogate for boron clearance. The remaining 

38 uncertainty in the RfD derivation was from toxicodynamics. Inter-species and intra-human 

39 toxicodynamic uncertainty were assigned the default value of 3.16. The product of all the 

40 adjustment and sub-factors served as the total adjustment factor of 66. The RfD was derived by 

41 dividing the BMDL05 of 10.3 mg/kg-d by the adjustment factor and rounding to one digit. This 

42 case study demonstrates the use of data to develop an intraspecies toxicokinetics extrapolation 
May 11, 2011 21 DRAFT: DO NOT CITE OR QUOTE

1 (EFHK). Specifically, it demonstrates how an intra-human kinetic adjustment factor of 2.0 was 

2 estimated from three studies (Dunlop, 1981; Krutzén et al., 1992; Sturgiss et al., 1996), using 

3 glomerular filtration rate as a surrogate for boron clearance.

4

5 Hazard Identification and Dose-Response

6

7 Oral animal studies have identified the testes and the developing fetus as the two most 

8 sensitive targets of boron toxicity in multiple species (U.S. EPA, 2004). Testicular effects 

9 include reduced organ weight and organ:body weight ratio, atrophy, degeneration of the 

10 spermatogenic epithelium, impaired spermatogenesis, reduced fertility, and sterility. The 

11 mechanism of action for boron’s effect on the testes is not known, but the available data suggest 

12 an effect on the Sertoli cell. Developmental effects following oral exposure to boron have been 

13 reported in mice, rabbits, and rats and include high prenatal mortality; reduced fetal body weight; 

14 and malformations and variations of the eyes, CNS, cardiovascular system, and axial skeleton. 

15 Similarities in the NOAEL values for the reproductive toxicity studies and quality control issues 

16 complicated the choosing of testicular effects as the critical effect. 

17

18 Developmental effects (decreased fetal weights) are considered the critical effect. The 

19 studies by Price et al. (1994, 1996), NTP (1990) and Heindel et al. (1992) in rats were chosen as 

20 critical developmental studies because they were well-conducted studies of a sensitive endpoint 

21 that identified both a NOAEL and LOAEL. Rats were more sensitive than mice and rabbits, 

22 which were also studied for developmental toxicity. 

23

24 The POD was determined by BMD modeling. BMD evaluation of multiple 

25 developmental endpoints identified decreased fetal body weight as the most suitable endpoint. 

26 Two studies (Heindel et al, 1992; Price et al., 1994, 1996) provided data on fetal body weight 

27 and the results were combined for BMD evaluation. The benchmark response (BMR) level for 

28 mean fetal weight was chosen to be the BMD L05 value of 10.3 mg/kg-d. 

29

30 No data are available to identify a mode of action, but boron is absorbed, distributed and 

31 eliminated unchanged in urine. It is not metabolized, so some measure of exposure to parent 

32 compound should serve as the basis for dose (exposure) expression. 

33

34 Basis for DDEF

35

36 Following administration, boron is rapidly absorbed and distributed throughout the body. 

37 It distributes with total body water; concentrations in all tissues examined were similar. Bone 

38 and fat tissues represent outliers—boron seems to accumulate in bone and the low water content 

39 of adipose tissue reduces boron distribution to fat. 

40

41 Given the relatively uniform distribution of boron to the tissues and that the majority of 

42 the compound is excreted quickly, the likelihood for sequestration of boron by a given tissue is 

43 minimal. Although there are no direct measurements of fetal boron concentrations, boron 

44 concentrations in the fetus should be the same as in the mother because boron is freely diffusible 

45 across biological membranes and will rapidly and evenly equilibrate in all body water 

46 compartments. As the boron RfD is based on developmental effects observed in rats, the most 
May 11, 2011 22 DRAFT: DO NOT CITE OR QUOTE

1 relevant kinetic data are those pertaining to pregnant rats and pregnant humans. There are 

2 insufficient data to compare plasma boron in rats and humans at the same exposure levels. 

3 Therefore, boron clearance is used as an estimator of internal dose.

4

5 Since boron is not metabolized, clearance from blood and tissues is via urinary 

6 elimination. Data demonstrate that boron is a small, uncharged molecule, with no protein 

7 binding. Evidence from human dialysis studies indicates clearance is via passive diffusion. 

8 These (and other) data identify passive renal mechanisms as those most governing boron 

9 clearance. For that reason, the most appropriate renal measurement for boron clearance is the 

10 glomerular filtration rate (GFR). Several studies have characterized the variability of GFR 

11 among pregnant humans (Table 4). The application of these data describing variance of GFR 

12 among pregnant humans serves as the basis for estimating human interindividual differences in 

13 internal exposure. 

14

15 DDEF Derivation

16

17 For the assessment of intraspecies toxicokinetic variability, glomerular filration rate 

18 (GFR) is used as a surrogate for boron clearance. Although the study of Pahl et al. (2001) 

19 provides an estimate of boron clearance variability in pregnant women, the data are judged to be 

20 inadequate for this purpose. As boron clearance is largely a function of GFR, the larger more 

21 certain data base on GFR and its variability among humans is used to estimate boron clearance 

22 variability. Because the measured boron clearances in the rat and human kinetic studies were 

23 less than GFR, tubular reabsorption could be contributing to the variability of boron clearance in 

24 the population. Variability in these factors, however, is judged to be minor in comparison to the 

25 variability in GFR.

26

27 Table 4. Measures of GFR Variability Among Pregnant Women

28

Study Mean GFR(mL/min) Standard Deviation

Dunlop 150.5a 17.6

Krutzen 195b 32

Sturgiss 138.9c 26.1

29 a 30 Serially-averaged observations across three time periods (16, 26, and 36 weeks) for 25 pregnant women. b 31 Third trimester values for 13 pregnant women. c 32 Serially-averaged observations across two time periods (early and late pregnancy) for 21 pregnant women (basal 

33 index plus basal control individuals).

34

35

36 GFR data have been used previously in the context of the boron RfD by Dourson et al. 

37 (1998), who proposed the ratio of the mean GFR to the GFR value 2 standard deviations (SD) 

38 below the general population mean (mean/[mean - 2 SD]) as the metric for the intraspecies

39 toxicokinetic adjustment factor. This approach is referred to as the sigma method, which is a 

40 common term used for statistical methods using multiple standard deviations to establish 
May 11, 2011 23 DRAFT: DO NOT CITE OR QUOTE

1 “acceptable” lower bounds. For the derivation of EFHK, the sigma method is modified by using 3 

2 SD as the reduction factor for establishing the lower bound (i.e., mean GFR - 3 SD). The basic 

3 formula modified from Dourson et al. (1998) for EFHK is: 

4

GFRAVG

AFHK = 5 GFRAVG − 3SDGFR 

6

7 where GFRAVG and SDGFR are the mean and standard deviation of the GFR (mL/min) for the 

8 general healthy population of pregnant women. The use of three standard deviations rather than 

9 two (as in Dourson et al., 1998) is based on a statistical analysis of the published GFR data, with 

10 more consideration being given to the full range of GFR values likely to be found in the 

11 population of pregnant women. In the aggregate, the data suggest that a lower bound GFR 2 SD 

12 below the mean does not provide adequate coverage of the susceptible sub-population (those 

13 pregnant women experiencing or predisposed to preeclampsia). While no conclusive 

14 information exists from controlled-dose studies in humans, it may be possible that the variability 

15 in boron clearance might be greater than GFR variability. Therefore, EFHK must also account for 

16 any residual uncertainty in using GFR as a surrogate. 

17

18 Three studies (Dunlop, 1981; Krutzén et al., 1992; Sturgiss et al., 1996) were found to 

19 address GFR variability in pregnant women. Dunlop (1981) assessed GFR for 25 women at 

20 three different time points during pregnancy (16, 26, and 36 weeks) and again after delivery. In 

21 this study (Dunlop, 1981) GFR was measured as inulin clearance and the overall average and 

22 standard deviation was 150.5 and 17.6 mL/min, respectively. Sturgiss et al. (1996) performed a 

23 similar assessment of GFR (also using inulin clearance) for 21 women in early (12-19 weeks) 

24 and late (30-35 weeks) pregnancy and again at 15-25 weeks post partum and found a mean GFR 

25 of 138.9 mL/min with a standard deviation of 26.1 mL/min. Krutzén et al. (1992) evaluated 

26 GFR during pregnancy for four different groups of women (13 normal healthy women, 16 

27 diabetic women, 8 hypertensive women, and 12 women diagnosed with preeclampsia) by using

28 iohexol clearance in the second and third trimester and again 6-12 months post partum. In this 

29 study (Krutzen et al, 1992) the third trimester mean GFR and standard deviation for the healthy 

30 women was reported as 195 and 32 mL/min, respectively. In general, the GFR values reported 

31 in this study are much higher than those reported by Dunlop (1981) and Sturgiss et al. (1996).

32 The reason for this discrepancy is not known. The GFRs from these studies and the results of the 

33 sigma method value calculations for EFHK are shown in Table 5.

34

35 Considering the Krutzén et al. (1992) results in the context of the sigma method, a 

36 reduction of 2 SD from the healthy population mean to establish the lower bound (which results 

37 in a GFR slightly higher than the mean of the preeclamptic GFR), would appear to be 

38 insufficient for adequate coverage of the susceptible population. Thus the use of 3 SD below the 

39 healthy GFR mean gives coverage in the sensitive subpopulation to about 1 SD below the mean 

40 preeclamptic GFR. 

41

42

43

44

45

46
May 11, 2011 24 DRAFT: DO NOT CITE OR QUOTE

Table 5. Sigma-method value calculation for EFHKa 1

2

Study Mean GFR (SD)

(mL/min) Mean GFR – (3SD) Sigma-Method Value

Dunlop 150.5 (17.6)b 97.7 1.54

Krutzen 195 (32)c 99 1.97

Sturgiss 138.9 (26.1)d 60.6 2.29

Averages 161.5 85.8 1.93

3 a 4 Mean GFR ÷ (Mean GFR - 3 SD).

b 5 Serially-averaged observations across three time periods (16, 26, and 36 weeks) for 25 pregnant women. c 6 Third trimester values for 13 pregnant women. 

d 7 Serially-averaged observations across two time periods (early and late pregnancy) for 21 pregnant women (basal 

8 index plus basal control individuals). 

9

10

11 As no single study is considered to be definitive for assessment of population GFR 

12 variability, EFHK is determined from the average of the individual sigma-method values for each 

13 of the three studies (Table 4). The mean GFR and standard deviation values in Table 5 are based 

14 on average GFR across the entire gestational period, except for the Krutzén et al. (1992) 

15 estimate, which was for the third trimester only. The average sigma-method value from the three 

16 studies is 1.93. Considering a small residual uncertainty in the use of GFR as a surrogate for 

17 boron clearance, the average sigma-method value of 1.93 is rounded upward to 2.0 and 

18 established as the value for EFHK.

19

20 By virtue of their lower GFR, pregnant women diagnosed with preeclampsia could be 

21 considered to be a sensitive subpopulation, at least toxicokinetically. Toxicodynamic sensitivity 

22 is presumably independent of toxicokinetic sensitivity. The onset of preeclampsia generally 

23 occurs after the week 20 of pregnancy and is characterized by acute hypertension, often 

24 accompanied by edema and proteinuria. Women with preeclampsia are at increased risk for 

25 premature separation of the placenta from the uterus and acute renal failure, among other adverse 

26 health effects. The fetus may become hypoxic and is at increased risk of low birth weight or 

27 perinatal death. 

28

29 The ~2-fold intraspecies variability factor derived from three standard deviations below 

30 the mean of three studies for pregnancy GFR (mean = 161.5 mL/min; mean - 3 SD = 85.8) is 

31 considered preferable for providing adequate coverage to women predisposed to adverse birth 

32 outcomes due to renal complications. Therefore, the default value of 3.16 for UFH-TK was 

33 replaced with a data-derived adjustment factor of 2.0. 

34

35 References

36

37 Dourson M., A. Maier, B. Meek, A. Renwick, E. Ohanian and K. Poirier. 1998. Boron tolerable 

38 intake re-evaluation of toxicokinetics for data derived uncertainty factors. Biol. Trace Elem. 

39 Res. 66(1-3):453-263.
May 11, 2011 25 DRAFT: DO NOT CITE OR QUOTE

1 Dunlop, W. 1981. Serial changes in renal haemodynamics during normal human pregnancy. 

2 Br. J. Obstet. Gynecol. 88:1-9.

3 Heindel, J.J., C.J. Price; E.A. Field et al. 1992. Developmental toxicity of boric acid in mice 

4 and rats. Fund. Appl. Toxicol. 18(2):266-277. 

5 Krutzen E., P. Olofsson, S.E. Back and P. Nilsson-Ehle. 1992. Glomerular filtration rate in 

6 pregnancy: a study in normal subjects and in patients with hypertension, preeclampsia and 

7 diabetes. Scand. J. Clin. Lab. Invest. 52:387-392.

8 NTP (National Toxicology Program). 1990. Developmental toxicity of boric acid (CAS No. 

9 10043-35-3) in Sprague Dawley rats. National Toxicology Program, Public Health Service, U.S. 

10 Department of Health and Human Services, Research Triangle Park, NC; NTP Report No. 

11 90-105 (and Report Supplement No. 90-105A) , NTIS# PB91-137588.

12 Pahl, M.V., B.D. Culver, P.L. Strong, F.J. Murray and N.D. Vaziri. 2001. The effect of 

13 pregnancy on renal clearance of boron in humans: a study based on normal dietary intake of 

14 boron. Toxicol. Sci. 60:252-256.

15 Price, C.J., M.C. Marr, C.B. Myers. 1994. Determination of the no-observable-adverse-effect 

16 level (NOAEL) for developmental toxicity in Sprague-Dawley (CD) rats exposed to boric acid in 

17 feed on gestational days 0 to 20, and evaluation of postnatal recovery through postnatal day 21 

18 [final report]. Research Triangle Institute, Center for Life Science, Research Triangle Park, NC; 

19 RTI Identification No. 65C-5657-200. 

20 Price, C.J., P.L. Strong, M.C. Marr, J.C. Seely, J.J. Heindel, B.A. Schwetz. 1996. 

21 Developmental toxicity NOAEL and postnatal recovery in rats fed boric acid during gestation. 

22 Fund. Appl. Toxicol. 32(2):179-193. 

23 Sturgiss, S.N., R. Wilkinson and J.M. Davison. 1996. Renal reserve during human pregnancy. 

24 Am. J. Physiol. 271:F16-F20.

25 U.S. EPA (U.S. Environmental Proection Agency). 2004. IRIS Summary for Boron and 

26 Compounds (CASRN 7440-42-8). Available at http://www.epa.gov/ncea/iris/subst/0410.htm

27 Last revised August 5, 2004.

28 Vaziri, N.D., F. Oveisi, B.D., Culver et al. 2001. The effect of pregnancy on renal clearance of 

29 boron in rats given boric acid orally. Toxicol. Sci. 60(2):257-263. 

30

31

32 Methylmercury (MeHg)

33

34 Summary

35

36 This case study presents information derived from the Water Quality Criterion for the 

37 Protection of Human Health: Methylmercury (U.S. EPA, 2001a) and the Integrated Risk 

38 Information System (IRIS) entry for Methylmercury (U.S. EPA, 2001b). Methylmercury 
May 11, 2011 26 DRAFT: DO NOT CITE OR QUOTE

(MeHg) has a reference dose (RfD) of 1 × 10-4 1 mg/kg-d on U.S. EPA’s IRIS database in 2001

2 (U.S. EPA, 2001b). No Toxicological Review is available for MeHg, but the underlying data 

3 and interpretations are published in the Water Quality Criterion for the Protection of Human 

4 Health: Methylmercury (U.S. EPA, 2001a). 

5

6 Multiple RfDs were calculated from BMDL05 values for various endpoints reported in 

7 three epidemiological studies measuring neurobehavioral deficits in children exposed in utero. 

8 Composite uncertainty factors of 10 were used in all calculations. This included a default 3 fold 

9 factor for human toxicodynamic variability and uncertainty and a three fold factor for human 

10 toxicokinetic variability and uncertainty. This latter EFHK was based on published analyses of 

11 human toxicokinetic data. 

12

13 Hazard Identification and Dose Response

14

15 MeHg can produce a variety of toxicities depending on the dose. These range from 

16 seizures and death to subtle neurobehavioral changes humans exposed in utero. The choice of 

17 studies, critical effects, model, and point of departure choices were informed by an NRC 

18 advisory report and a subsequent review by an independent scientific panel.

19

20 Mercury is methylated in soils and sediments by microorganisms and is bioaccumulated 

21 through aquatic food webs. It can reach relatively high concentrations (1 ppm or more) in 

22 predatory fish and sea mammals consumed by humans and wildlife. MeHg is absorbed readily 

23 from the human gut and is transported through the body, crossing both the blood/brain and 

24 placental barriers. Human studies from environmental exposures (fish consumption) were 

25 available and served to define the POD. Neurobehavioral effects were observed in two studies of 

26 children exposed in utero from maternal consumption of seafood (Faroes and New Zealand).

27 The Faroe Islands study was a longitudinal study of about 900 mother-infant pairs (Grandjean et 

28 al., 1997). The main independent variable was cord-blood mercury; maternal-hair mercury was 

29 also measured as was child hair mercury. At 7 years of age, children were tested on a variety of 

30 tasks designed to assess function in specific behavioral domains. In the New Zealand study 

31 (Kjellstrom et al., 1996a,b), increased maternal hair mercury was associated with decreased 

32 scores on standard IQ tests in 6 year old children. No effects were reported in a third such study 

33 in the Seychelles Islands, but these data were also included in the modeling (NRC, 2000). 

34

35 No mode of action for methylmercury has been established. 

36

37 Test responses of children in three large studies (Faroe Islands, Seychelles and New 

38 Zealand) were coupled with measured or calculated MeHg cord blood concentrations for the 

39 dose-response analysis. Benchmark dose (BMD) analysis was applied to the results from 

40 multiple individual neurobehavioral tests (e.g., Boston Naming Test, Continuous Performance 

41 Test, California Verbal Learning Test. Data were modeled using a K-power model with K > 1; 

42 K = 1 generally gave the best fit. These data were continuous in exposure and effect. An 

43 abnormal response was defined as one falling into the lowest 5% of test responses (P0 = 0.05). 

44 The benchmark response (BMR) was set at 0.05, based on the external review committee’s 

45 advice that the combination of BMR and P0 were within the observed range of responses and 
May 11, 2011 27 DRAFT: DO NOT CITE OR QUOTE

1 were, in fact, typical for these types of measurements. BMDL05 values of 46 to 79 ppb MeHg in 

2 fetal cord blood were chosen as the points of departure for RfD calculation. 

3

4 There is a correlation between maternal-blood mercury concentrations and fetal-blood 

5 mercury concentrations. A review of results from 21 studies demonstrated that the ratio of 

6 concentrations (fetal:maternal) is typically higher than 1, with overall mean values supporting a 

ratio close to 1.7. Ratios for the 5th and 95th 7 percentiles of cord:maternal Hg approximate 0.85 

8 and 3.5, respectively. Based on the advice of an NRC panel U.S. EPA (IRIS, U.S. EPA, 2001b) 

9 chose not to make a numerical adjustment between cord-blood and maternal-blood mercury in 

10 calculating the RfD. The relationship between cord-blood and maternal-blood mercury was 

11 discussed as an area of variability and uncertainty, during UF derivation. Conversion of cord 

12 blood measurements to estimated ingested maternal dose used a one-compartment model with 

13 fixed parameters, as advised by the scientific reviews. 

14 Twenty-four RfDs were calculated using various BMDL05s but with the same dose 

15 conversion and a composite uncertainty factor of 10. These calculations resulted in one RfD = 

16 0.2 μg/kg bw /day, three RfD = 0.05 μg/kg bw /day, and twenty RfD = 0.1 μg/kg bw /day (or 1x 

10-4 17 mg/kg-d). 

18

19 Basis for DDEF

20

21 A PBPK model and a one-compartment model for pregnant women were used to examine 

22 the relationship between ingested doses of MeHg and maternal blood levels. To estimate human 

23 interindividual variability (of MeHg concentrations in maternal blood to ingested MeHg dose), 

24 the most deterministic (sensitive) parameters of the TK model were identified and varied. Model 

25 results demonstrated that external doses required to produce maternal blood concentrations of 1 

26 ppm varied up to three-fold. This value (3) served as a non-default value for EFHK; the TD 

27 component (UFHD was left at a default value of 3 and the overall intraspecies UF value was 10. 

28

29 DDEF derivation 

30

31 Multiple measures of MeHg exposure are available from several human studies. For 

32 MeHg hair and blood are considered more appropriate than urine, particularly for longer term 

33 exposure. The toxicity evaluated was induced during gestation, at a time when MeHg exposure 

34 to the fetus’ developing brain via the placental blood supply. Thus MeHg originated from the 

35 maternal blood circulation. Both a PBPK model and a one-compartment model were used to 

36 assess variables in fetal MeHg exposure. Independent of model type, ability to estimate maternal 

37 hair concentrations required at least two more parameters (blood to hair transfer and hair growth 

38 rate) than required to estimate maternal blood concentrations. In addition, because the U.S. EPA 

39 set cord blood concentrations to equal maternal blood concentrations, the model was able to 

40 predict fetal cord blood concentrations with less uncertainty than maternal hair concentrations. 

41 Largely for these reasons, blood MeHg concentrations were selected as the most appropriate 

42 dose metric. 

43

44 The U.S. EPA characterized human toxicokinetic variability as differences in external 

45 (ingested) doses of MeHg that resulted in the same concentration of MeHg in maternal blood. 

46 The concentration selected for analysis was one that was relevant to the BMDL05 for the 
May 11, 2011 28 DRAFT: DO NOT CITE OR QUOTE

1 neurobehavioral effects—namely 1 ppm. This concentration is about 12 to 20 times higher than 

2 the concentrations serving as the POD, but the choice may be based in part on increasing model 

3 uncertainty when predicting concentrations lower than 1 ppm. An evaluation of the uncertainty 

4 and variability in model parameters was conducted in three studies (Stern, 1997; Swartout and 

5 Rice, 2000; Clewell et al., 1999) to identify the extent to which the external (ingested) dose 

6 might vary when compared to a fixed maternal hair or blood concentration. 

7

8 Results from the Stern (1997) analysis were available in the original publication, whereas 

9 specific predictions of values at given percentiles for the Swartout and Rice (2000) and Clewell 

10 et al. (1999) studies required additional model exercises by the original authors; these analyses 

11 were published by NRC (2000). All data used in the models were from human studies. The 

12 analysis demonstrated the ratio of external (ingested) doses (in μg/kg/day) that resulted in the 

13 same blood concentration; the ratio was selected as that resulting from the comparison of the 

dose at the 50th percentile of the distribution to the dose at the 1st 14 percentile of the distribution. 

15 These percentiles of the distribution represented the “general” human and the ‘sensitive” human, 

respectively. Because the dose at the 1st 16 percentile of the distribution will be lower than the dose 

at the 50th 17 percentile of the distribution, the ratio will have a value greater than 1.0. 

18

Table 6 presents the ratios developed (external dose at the 50th 19 percentile / external dose 

at the 1st 20 percentile) for each of the three studies. Considering TK variability as described by the 

21 ratio of external doses at the specified percentiles of the distribution, values for blood and hair 

22 ranged from 1.7 to 3.3. Maximum values were 3.3 and 3.0 for hair and blood, respectively. The 

23 U.S. EPA’s IRIS entry for MeHg states, “Using maternal blood as the starting point, the 

24 consolidated range from the three analyses is 1.7 to 3.0.”, this is consistent with the U.S. EPA’s 

25 Water Quality Criterion document (U.S. EPA, 2001a) On this basis, a value of 3 was chosen to 

26 serve as the numerical replacement for the default value of the portion of the UF related to 

27 intraspecies TK variability. As no data were available to address intraspecies differences in 

28 susceptibility (TD), this portion of the UF was left at the default value of 3. Together these 

29 values for the components of UFH combine to equal a value of 10, which was characterized as a 

30 “hybrid” value, comprising values based on default methodology and on data. 

31

32

33
May 11, 2011 29 DRAFT: DO NOT CITE OR QUOTE

1 Table 6. Comparison of Results from Three Analyses of the Interindividual Variability in the 

2 Ingested Dose of MeHg Corresponding to a Given Maternal-Hair or Blood Hg Concentration. 

3 This is Table 3-1 from NRC (2000).

4

Study Maternal 

Medium

50th Percentilea

(μg/kg-d)

50th Percentile/

5th Percentileb

50th Percentile/

1st Percentilec

Stern (1997) Hair 0.03 – 0.05d

(mean = 0.04)

1.8-2.4

(mean = 2.1)

2.3-3.3

(mean = 2.7)

Blood 0.01 1.5-2.2

(mean = 1.8)

1.7-3.0

(mean = 2.4)

Swartout and 

Rice (2000)

Hair 0.08 2.2 Data not reported

Bloode 0.02 2.1 2.8

Clewell et al. 

(1999)

Hair 0.08 1.5 1.8

Bloodf 0.07 1.4 1.7

5 a

Predicted 50th 6 percentile of the ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in 

7 blood.

b

Ratio of 50th 8 percentile of ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in blood 

to the 5th 9 percentile. c

Ratio of 50th 10 percentile of ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in blood to 

the 1st 11 percentile.

d 12 Range reflects minimum and maximum values among eight alternative analyses. e 13 Data from J. Swartout, U.S. Environmental Protection Agency, personal commun.; June 9, 2000.

f 14 Data from H.J. Clewell, ICF Consulting, personal commun.; April 19, 2000.

15

16

17 Acknowledgment: Some passages in this document were taken from the U.S. EPA’s IRIS entry 

18 for Methylmercury (U.S. EPA, 2001b); some were taken from the U.S. EPA’s Water Quality 

19 Criterion document for Methylmercury (U.S. EPA, 2001a)

20

21 References

22

23 Clewell, H.J., J.M. Gearhart, P.R. Gentry et al. 1999. Evaluation of the uncertainty in an oral 

24 reference dose for methylmercury due to interindividual variability in pharmacokinetics. Risk 

25 Anal. 19(4):547-558.

26 Grandjean, P., P. Weihe, R. White et al. 1997. Cognitive deficit in 7-year-old children with 

27 prenatal exposure to methylmercury. Neurotoxicol. Teratol. 19(6):417-128. 

28 Kjellstrom, T., P. Kennedy, S. Wallis and C. Mantell. 1986a. Physical and mental development 

29 of children with prenatal exposure to mercury from fish. Stage 1: preliminary tests at age 4. 

30 Report 3080. Solna, Sweden: National Swedish Environmental Protection Board.
May 11, 2011 30 DRAFT: DO NOT CITE OR QUOTE

1 Kjellstrom, T., P. Kennedy, S. Wallis et al. 1986b. Physical and mental development of children 

2 with prenatal exposure to mercury from fish. Stage 2: interviews and psychological tests at age 6. 

3 Solna, Sweden: National Swedish Environmental Protection Board, Report 3642.

4 NRC (National Research Council). 2000. Toxicological effects of methylmercury. Committee 

5 on the Toxicological Effects of Methylmercury, Board on Environmental Studies and 

6 Toxicology, Commission on Life Sciences, National Research Council, Washington, DC: 

7 National Academy Press.

8 Stern, A.H. 1997. Estimation of the interindividual variability in the one-compartment 

9 pharmacokinetic model for methylmercury: Implications for the derivation of a reference dose. 

10 Regul. Toxicol. Pharmacol. 25(3):277-288 (As cited in Clewell et al., 1999).

11 Swartout, J. and G. Rice. 2000. Uncertainty analysis of the estimated ingestion rates used to 

12 derive the methylmercury reference dose. Drug Clin. Toxicol. 23(1):293-306.

13 U.S. EPA (U.S. Environmental Protection Agency). 2001a. Water Quality Criterion for the 

14 Protection of Human Health: Methylmercury. Office of Science and Technology, Office of 

15 Water. Washington, DC. EPA/823/R-01/001. Available at 

16 http://www.epa.gov/waterscience/criteria/methylmercury/merctitl.pdf. 

17 U.S. EPA (U.S. Environmental Protection Agency). 2001b. Integrated Risk Information System 

18 (IRIS) File for Methylmercury. Available at http://www.epa.gov/iris/subst/0073.htm (accessed

19 9/10/2008).