May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 1 APPENDIX 1

2

CASE STUDIES TO ACCOMPANY DATA DERIVED EXTRAPOLATION FACTOR 3

DOCUMENT 4

5

This document is an Appendix to the d raft d ocument on Data Derived Extrapolation 6

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

derivation of non

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

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

, al tho ugh 9

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

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

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

values found in IRIS or Program Office risk assessments. 13

14

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

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

chemicals for others. Differences are due to chemical

- specific data sets, which may be more 17

informative for some areas than others. 18

19

1. Summary 20

This section communicates the current assessment(s) (e.g

. , IRIS, PPRTV, RED, 21

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

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

24

2. H azard Identification and Dose Response 25

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

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

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

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

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

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

32

3. Basis for DDEF 33

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

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

of DDEF method and highlights the connection between the measure of dose and ad verse 36

effect

. 37

38

4. DDEF Derivation 39

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

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

the UF component should be presente d. 42

43

Each of the case studies illustrates different principles described in the Document

. Table 44

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

have experience with deriving a DD E F for intra

- species extrapo lation with regard to TD. As 46

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

48May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 2 Table 1. DDEF Case Study Chemicals and Issues 1

2

Data Derived

Extrapolation

Factor Chemical Other Principles or I ssues

Animal to Human,

Toxicokinetics

( EF AK ) * 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, i nternal dose

of reactive metabolite in liver chosen as basis for

toxicokinetic equivalency between species

Animal to Human,

Toxicodynamics

( EF AD ) 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, u se of in vitro data, u se of

genomics data

N

- methyl

carbamate

pesticides Application of a DDEF to a common mechanism

group of chemicals, u se of DDEF approach to

identify data gaps

Within H uman

V ariability

, Toxicokinetics

( EF HK ) 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

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

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

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

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

Concentration do not make that calculation explicit. 8

9May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 3 

## INTERSPECIES ADJUSTMENT FOR TOXICO KINETICS 1

2



### Ethylene Glycol Monobutyl Ether (EGBE)

— EF AK 3



### Case Study 4

5

Summary 6

7

Ethylene glycol monobutyl ether (EGBE; 2

- butoxy ethanol) has an established RfD of 8

0. 1 mg/kg

- d on the U

. S

. EPA’s Integrated Risk information System (IRIS) data base (U.S. EPA, 9

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

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

extrapolated via PBPK modeling to identify the hu man equivalent dose. 12

13

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

a n HED of 1.4 mg/kg

- d . To this value, a combined uncertainty factor of 10 was applied, which 15

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

(UF H ). The UF AK was reduced to 1 on the basis of the dosimetry adjustments for TK, and the 17

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

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

20

Hazard Identification and Dose Response 21

22

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

subchronic 91

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

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

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

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

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

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

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

in humans (in US EPA, 2010). 31

32

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

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

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

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

acid/liter

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

hemosiderin deposition in male rat liver (NTP, 2000). In the IRIS assessment, t he dose

- response 38

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

Figure 1. 40

41May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 4 1

2

Figure 1

. Analysis Approach for Developing the Human Equivalent Dose with 3

Values Shown 4

5

6

Basis for DDEF 7

8

AUC values for the EGBE metabolite 2

- butoxyacetic acid ( BAA ) in arterial blood of 9

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

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

, were deemed 11

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

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

, hemolysis 13

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

. PBPK 14

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

AUC. 16

17

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

results of this analysis indicated that an AUC value of 133 μmol/L

- hr BAA in arterial blood is 19

the BMDL 10 for increased hemosiderin de position in liver in male rats. 20

21

The AUC value for BAA of 133 μmol/L

- hr in arterial blood was chosen as the POD for 22

inter species extrapolation. Next, a human PBPK model was employed to translate thi s level of 23

the dose metric to an HED of 1.4 mg/kg

- d. 24

25

DDEF Derivation 26

27

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

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

identify that an external dose of 5.83 mg/kg

- d in the r at would produce this BMDL 10 30

concentration (133 μmol/L

- hr) of the BAA metabolite ( Dr Richard Corley, personal 31

communication, 20 10 ). The human PBPK model was run to identify the external dose that 32

produced the same level of the dose metric (133 μmol/L

- hr); this value of the dose metric was 33

produced by an external dose of 1.4 mg/kg

- d in the human. The AUC dose metric was used as 34

the basis for human equivalence. 35

36

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

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

External

Conc. Rat

PBPK

Model Dose

Metric

Values BMD

Modeling POD as

Dose

Metric Human

PBPK

Model Human

Equivalent

Dose

350

– 3500

μ mol/L

- hr

BAA 133 μ mol/L

- hr

BAA 1.4 mg/kg

- d

5.83 mg/kg

- d POD as

Rat

External

Dose 150

– 600

mg/m 3 EGBEMay 11, 2011 DRAFT: DO NOT CITE OR QUOTE 5 Eq. 1, Section 3.2.2.2). Using the data described above, a comparison of the external doses 1

would yield a EF AK value of 5.83 mg/kg

- d ÷ 1.4 mg/kg

- d = 4.2. The 4.2

- fold DDEF would 2

replace the default UF AK 3

- fold factor. 3

4

Applying the EF A

- TK 4.2

- fold* to the rat external dose (5.83 mg/kg

- d) yields an HED of 5

1.4 mg/kg

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

7

The above methods c an also be compared to the default methodology that is b ased on 8

body weight scaling (U

. S

. EPA, 2006) . Using a study

- specific female rat body weight of 0.188 9

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

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

dose (5.83 mg/kg

- d) to yield an HED o f 1.3 mg/kg

- d . The reciprocal of the 0.23 DAF is 12

analogous to EF AK and would be 4.3. The 4. 3

- fold factor would replace the default 3

- fold UF AK

. 13

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

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

TK data for EGBE. 16

______________ 17

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

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

focused on TK ; please see the EGBE DDE F A D case study in this appendix

. 20

21

References 22

23

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

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

- 131. 25

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

- based 26

pharmacokinetics of 2

- butoxyethanol and its major metabolite, 2

- butoxyacetic acid, in rats 27

and humans. Toxicol. Appl. Pharmacol. 129:61

- 79. 28

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

Physiologically

- based pharmacokinetics and the dermal absorption of 2

- butoxyethanol vapors by 30

humans. Toxicol. Appl. Pharmacol. 39(2):120

- 130. 31

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

butoxyethanol (CA S No. 111

- 76

- 2) in F344/N rats and B6C3F1 mice (inhalation studies). 33

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

http://ntp.niehs.nih.gov/?objecti d=070AC403

- B110

- CA79

- 3A23AF79DE7B752A

. 35

36

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

Glycol Monobutyl Ether (EGBE) CAS No. 111

- 76

- 2 . Available at 38

http://www.epa.gov/ncea/iris/toxreviews/0500

- tr.pdf (accessed 9/10/2010). 39

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

Extrapolation: Use of BW 3/4 as Default Method in Derivation of the Oral RfD (External Review 41

Draft). Risk Assessment Forum Technical Panel, Washington, DC. EPA/630/R

- 06/001. 42

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

. 43May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 6 

### Vinyl Chloride

— EF AK 1



### Case S tudy 2

3

Summary 4

5

Vinyl chloride (VC) has an established oral Reference Dose of 3 E

- 3 (0.003) mg/kg

- d in 6

the current Integrated Risk Information System file (U

. S

. EPA, 2000) . The point of departure for 7

liver toxicity is a NOAEL value of 0.13 mg/kg

- d from a chronic feeding study in male Wistar 8

rats. PBPK modeling was used to develop a human equivalent dose of 0.09 mg/kg

- d, obviating 9

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

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

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

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

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

toxicokinetic extrapolation ( EF AK ). 15

16

Hazard Identification and Dose

- R esponse 17

18

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

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

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

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

there may be limited evidence suggestive of a risk for other non

- liver tumors (e.g., leukemia, 23

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

cancers other than liver in humans” (U

. S

. EPA, 2000). Other noncancer effects noted in 25

epidemiologic investigations include impaired liver function and biochemical and histological 26

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

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

29

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

12

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

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

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

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

characterized only as liver weight changes. 35

36

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

critical targe t organ. Til et al. (1983, 1991) reported the results of two

- year rodent bioassays 38

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

0.13, or 1.3 mg/kg

- d in feed for only 4 hours/day to minimize volatilization. T he VC content of 40

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

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

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

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

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

cancer effects in the chronic bioassay. These same changes were observed in a second study, but 46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 7 the doses employed in that study (Feron et al., 1981) were higher than those employed by Til and 1

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

approach based on external dose, a traditional (NOAEL) approach to dose

- response evaluation 3

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

extrapolation was the NOAEL of 0.13 mg/kg

- d for liver cell polym orphisms and bile duct cysts. 5

6

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

short

- lived metabolites that achieve only low steady

- state concentrations. These are thought to 8

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

longevity of CYP

- derived metabolites demonstrated an i nverse relationship between metabolite 10

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

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

of the short

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

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

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

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

17

Basis for DDEF 18

19

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

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

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

for liver effects, 0.13 mg/kg

- d. Consistent with guidance for RfC derivation, PBPK modeling of 23

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

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

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

and deemed sufficient for quantitative re liance. The NOAEL dose (0.13 mg/kg

- d) was converted 27

into the dose metric for VC

— the amount of metabolite in the liver (AML), with units of 28

oncentration mg/liter of liver. 29

30

DDEF Derivation 31

32

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

between applied dose and the dose metric (AML) up to doses approximating 25 mg/kg

- d . This 34

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

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

NOAEL dose of 0.13 mg/kg

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

internal exposure in the 70

- kg human was determined to result from a drinking water exposure of 38

0.09 mg/kg

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

- d and 0.09 mg/kg

- d in 39

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

41

42

43

44

45

46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 8 1

2

3

4

5

6

7

8

9

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

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

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

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

in the human i dentified the human equivalent dose, the dose producing the 14

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

16

17

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

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

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

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

22

Using the data descri bed above ( see S ection 3.2.2.2), these data indicate a DDEF value 23

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

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

4.32, in place of the default value of 10. By applying the DDEF calculated above (4.32

- fold) and 26

the 10

- fold intraspecies UF to the animal NOAEL (0.13 mg/kg

- d), the RfD is 0.13 mg/kg

- d ÷ 27

43.2 = 0.003 mg/kg

- d. This is the same value that was calculated fo r the IRIS assessment, which 28

was expressed as the HED/UF, or 0.09 mg/kg

- d/30 (U.S. EPA, 2000). 29

30

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

body weight scaling (U

. S

. EPA, 2006). Using a default value of 0.462 kg for adult Wistar rats 32

(U

. S

. EPA, 1988) and applying the body weight scaling approach (U

. S

. EPA, 2006) to the 33

NOAEL of 0.13 mg/kg

- d, a HED can be calculated as: 34

35

0.13 mg/kg

- d * 0.462 kg = 0.060 mg 36

0.06 mg * (70kg ÷ 0.462kg) 3/4

= 37

0.06 mg * 43.19 = 2.59 mg 38

2.59 mg ÷ 70 kg = 0.037 mg/kg

- d 39

40

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

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

of quantitative data on VC. 43

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 0.09 mg/kg

- d 0.13 mg/kg

- d 3 mg metabolite

per L liver 0.09 mg/kg

- dMay 11, 2011 DRAFT: DO NOT CITE OR QUOTE 9 References 1

2

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

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

Toxicol. Appl. Pharmacol. 87(2):185

- 205. 5

Bi, W.F., Y.S. Wang, M.Y. Huang and D

. S. Meng. 1985. Effect of vinyl chloride on tests in 6

rats. Ecotoxicol. Environ. Saf. 10(3):281

- 289. 7

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

- 95. 8

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

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

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

OSHA/DHSP. 12

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

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

report prepared for EPA/NCEA under co ntract number 68

- D2

- 0129. 15

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

study of vinyl

- chloride in rats. Food Cosmetol. Toxicol. 19(3):317

- 333. 17

Guengerich, F.P., P.S. Mason, W.T. Stott et al. 1981. Roles of 2

- haloethylene oxides and 18

2

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

protein and DNA. Cancer Res. 41:4391

- 4398. 20

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

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

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

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

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

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

V 83.285/291099, TSCATS Document FYI

- AX

- 0184

- 0353, Fiche No. 0353. 27

Til, H.P., V.J. Feron and H.R. Immel. 1991. Lifetime (149

- week) oral carcinogenicity study of 28

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

- 718. 29

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

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

Assessment Office, Cincinnati, Ohio. EPA/600/6

- 87/008, February, 1988. Available at 32

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

. 33

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

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

DC. Available at http://www.epa.gov/ncea/iris/subst/1001.htm (accessed 9/10/2008). 36May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 10 U.S. EPA (U.S. Environmental Protection Agency). 2006. Harmonization in Interspecies 1

Extrapolation: Use of BW 3/4 as Default Method in Deri vation of the Oral RfD (External Review 2

Draft). Risk Assessment Forum Technical Panel, Washington, DC. EPA/630/R

- 06/001. 3

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

. 4

5



## INTERSPECIES ADJUSTMENT FOR TOXICODYNAMICS 6

7



### Ethylene Glycol Monobutyl Ether (EGBE)

— E F AD 

### Case Study 8

9

Summary 10

Ethylene glycol monobutyl ether (EGBE; 2

- butoxy ethanol) has an established RfD of 11

0. 1 mg/kg

- d on the U

. S

. EPA’s Integrated Risk information System (IRIS) database (U.S. EPA, 12

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

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

be the critical effect. Derivation of the HED of 1.4 mg/kg

- d is detailed in the EGBE TK case 15

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

17

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

a n HED of 1.4 mg/kg

- d

. Uncertainty factors were applied to this POD value to derive the RfD. 19

20

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

account for variation in sensitivity within the human population (UF H )

. UF A was reduced to 1 on 22

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

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

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

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

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

28

Hazard Identification and Dos e Response 29

30

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

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

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

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

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

36

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

hemoglobin accumulation in Ku pffer cells include: 38

39

**•** Oxidative metabolism to butoxyacetic acid (BAA) 40

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

loss of deformability) 42May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 11 **•** Decreased erythrocyte count, hemoglobin, and hematocrit, and in response, increased 1

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

3

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

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

time without hemolysis were 35

- 40, 40

- 45, 60

- 90, 103

- 120, 147

- 268 and 360 minutes, 6

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

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

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

led Carpenter et al

. (1956) to speculate that the BAA metabolite of Cellosolve was responsible 10

for hemolysis. 11

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

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

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

- 11 14

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

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

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

incubation wi th 0.2 mM BAA for 6 hours or longer. The 4% measure was “mild

, ” and the data 18

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

increase in hemolysis over the back ground (control) level of 1%. Histologic evaluations of ra t, 20

but not human RBC preparations post

- exposure demonstrated erythrocyte “ghosts

, ” which are 21

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

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

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

which leads to fragility. 25

26

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

through a narrow

- diameter filter and monitorin g an increase in inflow pressure. The results were 28

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

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

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

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

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

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

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

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

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

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

follow

- on study, Udden (2002) demonstrated again th at human erythrocytes were less 39

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

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

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

mM

– a difference of 200

- fold. 43

44

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

- induced 45

RBC effects in vitro . An advantage of this study is the application of pairwise statistical design 46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 12 to determine the effect of treatment over control. Male Fischer 344 rats 15 weeks of age were 1

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

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

parameters: hematocrit was increased 2

- 4% and MCV was increased less than 4% above vehicle 4

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

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

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

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

9

Udden (2002) compared the sub

- hemolytic and hemolytic effects of BAA in rat and 10

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

were measured following a four

- hour exposure

. Alterations were noted in loss of deformability, 12

but at concentrations that were 150

- fold higher in rat erythrocytes than in human erythrocytes 13

(0.05 mM versus 7.5 mM). A larger species

- difference in response was noted in comparing 14

effect levels for increases in MCV

– these differences approximated 200

- fold, with rat 15

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

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

18

19

Basis for DDEF 20

21

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

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

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

25

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

l ow as 0. 0 5 mM. In contrast, similar hemolytic effects were observed in human blood exposed 27

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

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

component of the interspecies uncertainty factor. 30

31

DDEF Derivation 32

33

One potential approach would be to derive an adjustment factor of 0.005 for UF A

- TD 34

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

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

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

UF A

- TD was established at 1: 38

39

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

, 40

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

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

43

References 44

45

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

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

- 131. 47May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 13 Ghanayem, B.I. and C.A. Sullivan. 1993. Assessment of the hemolytic activity of 1

2

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

humans. Hum. Exp. Toxicol. 12(4):305

- 311. 3

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

butoxyacetic acid, a metabolite of 2

- butoxyethanol: II. Resistance in red blood cells from 5

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

- 102. 6

Udden M.M. 2002. In vitro sub

- hemolytic effects of butox yacetic acid on human and rat 7

erythrocytes. Toxicol Sci, 69: 258

- 264. 8

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

Glycol Monobutyl Ether (EGBE) CAS No. 111

- 76

- 2. In support of Summary Information on the 10

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

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

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

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

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

16

17



### Dimethyl A rsenic A cid (DMA)

— EF AD 

### Case Study 18

19

1

. Summary 20

21

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

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

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

collaboration with NHEERL scientists, developed a non

- linear mode of action assessment for 25

DMA for the development of rat bladder tumors (U

. S

. EPA, 2006). The MOA and dose

26

response assessments were developed using the MOA and Human Relevance Frameworks. The 27

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

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

of the default 10

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

component of UF A (EF AD ) to 1X. This case study describes the determ ination of the 3X factor 31

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

. The 32

default UF H of 10X factor was also applied leading to a composite factor of 30X

. 33

34

2. Hazard Identification and Dose

- Response 35

36

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

overall weight of the evidence prov ides convincing support for a non

- linear mode of action for 38

DMA V

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

40

**•** Reductive m etabolism of DMA V to DMA III

. 41May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 14 **•** DMA III causes urothelial cytotoxicity. Regenerative cell proliferation then ensues in 1

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

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

amount of DMA III is dependent on the conversion of DMA V to DMA III

. 4

**•** Sustained cytotoxicity leads to r egenerative cell proliferation which, in turn, ultimately 5

leads to hyperplasia and bladder tumors. 6

7

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

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

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

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

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

response to cell killing. As the severity of cytotoxicit y increases with increasing levels of DMA V 13

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

product is chromosome mutations. Thus, a tumor dose

- response curve would be influenced by 15

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

DMA V

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

in significant cell killing and regenerative cell proliferation in the urothelium of the blad der

. 18

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

levels. The levels of DMA III in the urine of rats treated with 100 ppm DMA V range from 20

0 .5

- 5.0uM. The LC 50 values for DMA III in rat and human urinary epithelial cells in vitro are 21

0.5

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

vitro at about 1.3 5 μ M DMA III . At 100 ppm, there is significant cell killing and regenerative 23

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

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

f emale rats via the feed. 26

27

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

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

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

well as for hyperplasia. A BMDL 10 value (0.43 mg/kg bw/day) is the basis for the point of 31

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

health protective bec ause a BMDL 1 0 of 0.43 mg/kg bw/day is approximately an order of 33

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

- fold 34

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

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

feeding studies. 37

38

3. Basis for DDEF 39

40

In the 2006 DMA risk assessment, instead of the default 10

- fold factor to extrapolate 41

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

account for interspecies differences in toxicokinetics

. UF A

- TD was reduced to 1X given that at a 43

similar dose at the target site (i.e.

, bladder urothelial), that humans and rats are expected to 44

respond pharmacodynamica lly similar. This case is built on a combination of information: 45May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 15 1

**•** C hemical

- specific in vitro data from Cohen et al

. (2002) which show that human and rats 2

cell respond similarly to exposure to DMA III

— the LC 50 s for cytotoxicity in human and 3

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

**•** There are m icroarray support (Sen et al

. , 2005)

. Qualitatively the genes up

- regulated in 5

human urinary bladder epithelial (UROtsa) are similar to those up

- regulated in rat urinary 6

bladder epithelial cells (MYP3) exposed to DMA V in vitro

. In this study, the r at cell line 7

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

**•** G eneral information on the development and function of the bladder along with incidence 9

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

in humans. 11

12

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

pharmacokinetic differences include: sequestration of DMA III by rat hemoglobin which results i n 14

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

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

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

of the risk assessment , an inter

- species extrapolation factor of 3 X was applied. Pharmacokinetic 18

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

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

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

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

half

- life in the rat for DMA V appears to correlate with erythrocyte half

- life, indicating that the 23

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

quantitative differences between rat and human which preve nts further reduction of the inter

25

species factor. 26

27

4. DDEF Derivation 28

29

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

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

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

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

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

35

References 36

37

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

dimethylarsinic acid

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

15(9): 1150

- 1157. 40

Sen, B., R. Grindstaff

, Y. Turpaz, J. Retief and D. Wolf. 2005. Gene expression to identify 41

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

Society of Toxicology Annual Meeting. New Orleans, Louisiana. March 2005. 43May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 16 U.S. EPA (U.S. Environmental Prote ction Agency)

. 2006. Revised Science Issue Paper: Mode 1

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

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

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

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

015262b

. 6

7

8



### N

- me thyl Carbamate Pesticides (NMCs)

— EF AD 

### Case Study 9

10

Summary 11

12

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

N

- methyl carbamates (NMCs) in 2007 (U

. S

. EPA, 2007). As required under the Food Quality 14

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

multiple pathways (i.e., food, drinking water, and residential/non

- occupational exposure to 16

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

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

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

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

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

ending cholinergic transmission in the nervous system. 22

23

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

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

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

available. 27

28

Hazard Identification and Dose Response 29

30

The NMCs were established as a CMG by U.S. EPA in 2001 (U

. S

. EPA, 2001) based on 31

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

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

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

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

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

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

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

hours). 39

40

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

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

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

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

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

widely used as a point of departure for risk assessment. 46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 17 U.S. EPA used the relative potency factor (RPF) method to determine the combined risk 1

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

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

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

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

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

time

- to

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

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

9

Basis for a DDEF 10

11

In the single chemical assessments for most NMCs, a default 10X factor for an imal

- to

12

human extrapolation was used. For three NMCs (aldicarb, methomy and oxamyl), however, 13

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

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

in risk assessment. These studies were used to derive the chemical

- specific inter

- species 16

extrapolation factor for these three chemicals. Table 2 summarizes the dose

- response and time

17

course modeling data for critical rat and h uman studies for these three NMCs. 18

19

Table 2 . NMC CRA: Inter

- species Extrapolation Factors and Corresponding Rat and Human 20

BMD 10 s and BMDL 10 s 21

22

Chemical Rat Human

Inter

species

UF Brain RBC RBC

BMD 10 (mg/kg) BMDL 10 (mg/kg) 1⁄2

life

(hrs) BMD 10 (mg/kg) BMDL 10 (mg/kg) 1⁄2

life

(hrs) BMD 10 (mg/kg) BMDL 10 (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

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

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

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

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

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

weight to the 3⁄4 power and are also consistent with a 3X factor to account fo r inter

- species 30

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

32May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 18 The mechanism of toxic action of NMCs is reproducible across a range of species, 1

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

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

- li f e to 3

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

and demonstrate the similarity of the half

- lives of the two species

. Based on this information, 5

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

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

8

DDEF Derivation 9

10

For the CRA, toxic potencies for the NMC s were determined using b rain AChE 11

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

exponential dose

- time

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

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

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

effect may then be derived. Using the data in Table 2 , and dividing the BMD 10

- rat by the 16

BMD 10

- human for RBD cholinesterase inhibition: 17

18

Aldicarb: 0.031 ÷ 0.016 = 1.9 ≈ 2 19

Methomyl: 0.204 ÷ 0.040 = 5.1 ≈ 5 20

Oxamyl: 0.278 ÷ 0.083 = 3.3 ≈ 3 21

22

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

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

standard 10X inter

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

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

regeneration) and indicated that rats and humans were very simi lar in this area. T he remaining 27

three

- fold (default) value for UFA address es species differences in toxicokinetics. 28

29

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

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

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

and they showed toxicodynamic equivalence, the Agency could reduce the inter

- species factor 33

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

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

factor for inter

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

sensitivity analysis in its risk characterization. 37

38

In this sensitivity analysis, the 10X inter

- species factor was reduced to 3X based on the 39

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

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

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 expresse d 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 DRAFT: DO NOT CITE OR QUOTE 19 the estimated human exposure to the cumulative risk to this group. The results of this sensitivity 1

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

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

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

shown here. The target MOE is 10 or higher f or intra

- species extrapolation. The table compared 5

the MOEs when using the standard UF to those obtained with the modified UF A

. 6

7

8

Table 3 . Sensitivity Analyses NMC Cumulative Food Assessment: DDE F Approach for Inter

9

species UF 10

11

Age Group Estimated Exposu re

at the 99.9 th

Percentile (mg/kg

oxamyl equivalents) MOE at the

99.9 th

Percentile Percentile at

Which Target of

10 is Reached

Baseline CRA Children 1

- 2 0.0229 7.9 99.848 th

Children 3

- 5 0.0209 8.6 99.870 th

DDEF Approach

for Inter

- species UF Children 1

- 2 0.0183 9.8 99.896 th

Children 3

- 5 0.0171 10.5 N/A

12

13

Review of this table shows that: 14

15

**•** U sing the standard 10X inter

- species factor for all NMCs without human data, the 16

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

- 2 and 17

3

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

percentiles of exposures

. 19

**•** W hen considering an alternative approach to the inter

- species factor which assum es a 3X 20

inter

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

percentile of exposure increase to 9.8 and 10.5 for children 1

- 2 and 3

- 5 years

— a 20% 22

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

10 at the 99.896 th percentile of ex posures. 24

25

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

substantial improvement in the refinement of the CRA. 27

28

References 29

30

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

Public Law 104

– 170

— AUG. 3, 1996. Available at 32

http://www.epa.gov/pesticides/regulating/laws/fqpa/gpogate.pdf (accessed 9/12/2008). 33May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 20 Radić, Z. and P. Taylor. 2006. Structure and function of cholinesterases. In: Toxicology of 1

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

Burlington, MA. p 161

- 186 3

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

cholinesterases. In: Toxicology of Organophosphate and Carbamate Compounds

, R.C. Gupta, 5

Ed. Elsevier Academic Press: Burlington, MA. p. 209

- 218. 6

U.S. EPA (U.S. Environmental Protection Agency

. 2001. Memorandum from Marcia Mulkey 7

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

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

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

9/12/2008). 11

U.S. EPA (U.S. Environmental Protection Agency

. 2006. DRAFT Harmonization in 12

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

Risk Assessment Forum Technical Panel , Washington, DC. 14

U.S. EPA ( U.S. Environmental Protection Agency). 2007. N

- Methyl Carbamate Revised 15

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

Programs, Washington, DC. Ava ilable online at 17

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

19

20



## INTRASPECIES ADJUSTMENT FOR TOXICOKINETICS

— 21



## ( EF HK 

## ) 22

23

B oron and Compounds 24

25

Summary 26

27

In the U

. S

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

10 - 1 mg/kg

- d has been developed based on the critical developmental effect of decreased fetal 29

weights (U

. S

. EPA, 200 4 ). The point of departure for the derivation of this value is the BMD L 05 30

value of 10.3 mg/kg

- d . The BMD L 05 is based on the combined results of two studies chosen for 31

the derivation of the RfD (Heindel et al

. , 1992; Price et al., 1994, 1996). Using data from rats 32

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

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

interspecies toxicokinetic adjustment factor was 3.3. An intra

- human kinetic adjustment factor 35

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

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

uncertainty in the RfD derivation was from toxicodynamics. Inter

- speci es and intra

- human 38

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

adjustment and sub

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

dividing the BMDL 05 of 10.3 mg/kg

- d by the adjustm ent factor and rounding to one digit. This 41

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

. Specifically, it demonstrates how a n intra

- human kinetic adjustment factor of 2.0 was 1

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

glomerular filtration rate as a surrogate for boron clearance

. 3

4

Hazard Identification and Dose

- Response 5

6

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

sensitive targets of boron toxicity in multiple species ( U

. S

. EPA, 200 4 ). Testicular effects 8

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

spermatogenic epithelium, impaired spermatogenesis, reduced fe rtility, and sterility. The 10

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

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

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

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

. 14

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

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

17

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

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

critical developmental studies because they were well

- conducted studies of a sensitive endpoint 20

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

which were also studied for developmental toxicity. 22

23

The P OD was determined by BMD modeling. BMD evaluation of multiple 24

developmental endpoints identified d ecreased fetal body weight as the most suitable endpoint

. 25

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

and the results were combined for BMD evaluation. T he benchmark response (BMR) level f or 27

mean fetal weight was chosen to be the BMD L 05 value of 10.3 mg/kg

- d

. 28

29

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

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

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

33

Basis for DDEF 34

35

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

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

and fat tissues represent outliers

— boron seems to accumulate in bone and the low water content 38

of adipose tissue reduces boron distribution to fat. 39

40

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

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

minimal

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

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

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

compartments. As the boron RfD is based on dev elopmental effects observed in rats, the most 46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 22 relevant kinetic data are those pertaining to pregnant rats and pregnant humans. There are 1

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

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

4

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

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

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

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

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

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

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

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

internal exposure. 13

14

DDEF Derivation 15

16

For the assessment of int raspecies toxicokinetic variability, glomerular filration rate 17

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

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

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

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

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

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

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

variability in GFR

. 25

26

Table 4 . Measures of GFR V ariability Among Pregnant Women 27

28

Study Mean GFR(m L /min) Standard Deviation

Dunlop 150.5 a 17.6

Krutzen 195 b 32

Sturgiss 138.9 c 26.1

29

a Serially

- averaged observations across three time periods (16, 26, and 36 weeks) for 25 pregnant women

. 30

b Third trimester values for 13 pregnant women

. 31

c Serially

- averaged observations across two time periods (early and late pregnancy) for 21 pregnant wo men (basal 32

index plus basal control individuals)

. 33

34

35

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

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

below the general population mean (mean/[mean

- 2 SD]) as the metric for the int raspecies 38

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

common term used for statistical methods using multiple standard deviations to establish 40May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 23 “acceptable” lower bounds. For the derivation of E F HK , the sigma method is modified by using 3 1

SD as the reduction factor for establishing the lowe r bound (i.e., mean GFR

- 3 SD). The basic 2

formula modified from Dourson et al. (1998) for E F HK is: 3

4

GFR AVG AFHK = GFR AVG − 3SD GFR 5

6

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

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

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

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

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

below the mean does not provide adequate coverage of the susceptible sub

- population (those 12

pregnant women experiencing or predisposed to preeclampsia)

. While no conclusive 13

information exists from controlled

- dose studies in humans, it may be possible that the variability 14

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

any re sidual uncertainty in using GFR as a surrogate. 16

17

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

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

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

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

standard deviation was 150.5 and 17.6 mL/min, respectively

. Sturgiss et al. (1996) performed a 22

s imilar assessment of GFR ( also using inulin clearance) for 21 women in early (12

- 19 weeks) 23

and late (30

- 35 weeks) pregnancy and again at 15

- 25 weeks post partum and found a mean GFR 24

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

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

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

iohexol clearance in the second and third trimester and again 6

- 1 2 months post partum . In this 28

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

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

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

. 31

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

sigma method value calculations for E F H K are shown in Table 5

. 33

34

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

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

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

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

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

preeclamptic GFR. 40

41

42

43

44

45

46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 24 Table 5. Sigma

- method value calculation for E F HK a 1

2

Study Mean GFR (SD)

(m L /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 Mean GFR ÷ (Mean GFR

- 3 SD). 4

b Serially

- averaged observations across three time periods (16, 26, and 36 weeks) for 25 pregnant women. 5

c Third trimester values for 13 pregnant women. 6

d Serially

- averaged observations across two time periods (early and late pregnancy) for 21 pregnant wo men (basal 7

index plus basal control individuals). 8

9

10

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

variability, EF HK is determined from the average of the individual sigma

- method values for each 12

of the three studies (T able 4 )

. The mean GFR and standard deviation values in Table 5 are based 13

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

estimate, which was for the third trimester only. The average sigma

- method value from the t hree 15

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

boron clearance, the average sigma

- method value of 1.93 is rounded upward to 2.0 and 17

established as the value for EF HK

. 18

19

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

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

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

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

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

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

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

perinatal death. 27

28

T he ~2

- fold int raspecies variability factor derived from three standard deviations below 29

the mean of three studies for pregnancy GFR (mean = 161.5 mL/min; mean

- 3 SD = 85.8) is 30

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

outcomes d ue to renal complications. Th erefore, the default value of 3.16 for UF H

- TK was 32

replaced with a data

- derived adjustment factor of 2.0. 33

34

References 35

36

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

intake re

- ev aluation of toxicokinetics for data derived uncertainty factors. Biol. Trace Elem. 38

Res. 66(1

- 3):453

- 263. 39May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 25 Dunlop, W. 1981. Serial changes in renal haemodynamics during normal human pregnancy. 1

Br. J. Obstet. Gynecol. 88:1

- 9. 2

Heindel, J

. J

. , C.J. Price; E.A. Field et al. 1992

. Developmental toxicity of boric acid in mice 3

and rats. Fund

. Appl

. Toxicol

. 18 (2) :266

- 277. 4

Krutzen E., P. Olofsson, S.E. Back and P. Nilsson

- Ehle. 1992. Glomerular filtration rate in 5

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

diabetes. Scand. J. Clin. Lab. Invest. 52:387

- 392. 7

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

10043

- 35

- 3) in Sprague Dawley rats. National Toxicology Program, P ublic Health Service, U.S. 9

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

90

- 105 (and Report Supplement No. 90

- 105A) , NTIS# PB91

- 137588. 11

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

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

boron. Toxicol. Sci. 60: 252

- 256. 14

Price, C

. J

., M.C. Marr, C.B. Myers. 1994

. Determination of the no

- observable

- adverse

- effect 15

level (NOAEL) for developmental toxicity in Sprague

- Dawley (CD) rats exposed to boric acid in 16

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

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

RTI Identification No. 65C

- 5657

- 200. 19

Price, C

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

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

Fund

. Appl

. Toxicol

. 32 (2) :179

- 193. 22

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

Am. J. Physiol. 271:F16

- F20. 24

U.S. EPA ( U.S. Environmental Proection Agency)

. 2 00 4 . IRIS Summary for Boron and 25

Compounds (CASRN 7440

- 42

- 8)

. Available at http://w ww.epa.gov/ncea/iris/subst/0410.htm 26

Last revised August 5, 2004

. 27

Vaziri, N

. D

., F. Oveisi, B.D., Culver et al

. 2001

. The effect of pregnancy on renal clearance of 28

boron in rats given boric acid orally. Toxicol

. Sci

. 60(2):257

- 263. 29

30

31



### Methylmercury (MeHg) 32

33

Summary 34

35

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

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

Information System (IRIS) entry for Methylmercury (U.S. EPA, 2001b). Methylmercury 38May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 26 (MeHg) has a reference dose (RfD) of 1 × 10 - 4 mg/kg

- d on U.S. EPA’s IRIS database in 2001 1

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

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

Health: Methylmercury (U

. S

. EPA, 2001a). 4

5

Multiple RfDs were calculated from BM DL 05 values for various endpoints reported in 6

three epidemiological studies measuring neurobehavioral deficits in children exposed in utero

. 7

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

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

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

human toxicokinetic data. 11

12

Hazard Identification and Dose Response 13

14

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

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

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

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

19

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

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

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

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

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

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

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

The Faroe Islands study was a longitudinal study of about 900 mother

- infant pairs (Grandjean et 27

al., 1997). The main independent variable was cord

- blood mercury; maternal

- hair mercury was 28

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

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

(Kjellstrom et al

., 1996 a,b ), increased maternal hair mercury was associated wi th decreased 31

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

in the Seychelles Islands, but these data were also included in the modeling (NRC

, 2000). 33

34

No mode of action for methylmercury has been established. 35

36

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

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

dose

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

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

Test, California Verbal Learning Test. Data were modeled using a K

- power model with K > 1; 41

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

abnormal response was defined as one falling into the lowest 5% of test responses (P 0 = 0.05). 43

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

advice that the combina tion of BMR and P 0 were within the observed range of responses and 45May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 27 were, in fact, typical for these types of measurements. BMDL 05 values of 46 to 79 ppb MeHg in 1

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

3

There is a correlation between maternal

- blood mercury concentrations and fetal

- blood 4

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

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

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

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

chose not to make a numerical adjustment betwe en cord

- blood and maternal

- blood mercury in 9

calculating the RfD. The relationship between cord

- blood and maternal

- blood mercury was 10

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

blood measurements to estima ted ingested maternal dose used a one

- compartment model with 12

fixed parameters, as advised by the scientific reviews. 13

Twenty

- four RfDs were calculated using various BMDL 05 s but with the same dose 14

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

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

10 - 4 mg/kg

- d ). 17

18

Basis for DDEF 19

20

A PBPK model and a one

- compartment model for pregnant women were used to examine 21

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

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

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

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

ppm varied up to three

- fold. This value (3) served as a non

- default value for EF HK ; the TD 26

component ( U F HD was left at a default value of 3 an d the overall intraspecies UF value was 10. 27

28

DDEF derivation 29

30

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

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

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

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

maternal blood circulation. Both a PBPK model and a one

- compartment model were use d to 35

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

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

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

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

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

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

dose metric. 42

43

The U

. S

. EPA characterized human toxicokinetic variability as differences in external 44

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

The concentration selected for analysis was one that was relevant to the BMD L 05 for the 46May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 28 neurobehavioral effects

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

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

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

and variability in model parameters was conducted in three studies (Stern, 1997 ; Swartout and 4

Rice, 2000; Clewell et al., 1999) to i dentify the extent to which the external (ingested) dose 5

might vary when compared to a fixed maternal hair or blood concentration. 6

7

Results from the Stern (1997) analysis were available in the original publication, whereas 8

specific predictions of values at given percentiles for the Swartout and Rice (2000) and Clewell 9

et al. (1999) studies required additional model exercises by the original authors; these analyses 10

were published by NRC (2000). All data used in the models were from human studies. The 11

an alysis demonstrated the ratio of external (ingested) doses (in μ g/kg/day) that resulted in the 12

same blood concentration; the ratio was selected as that resulting from the comparison of the 13

dose at the 50 th percentile of the distribution to the dose at the 1 st percentile of the distribution. 14

These percentiles of the distribution represented the “general” human and the ‘sensitive” human, 15

respectively. Because the dose at the 1 st percentile of the distribution will be lower than the dose 16

at the 50 th percenti le of the distribution, the ratio will have a value greater than 1.0. 17

18

Table 6 presents the ratios developed (external dose at the 50 th percentile / external dose 19

at the 1 st percentile) for each of the three studies. Considering TK variability as descr ibed by the 20

ratio of external doses at the specified percentiles of the distribution, values for blood and hair 21

ranged from 1.7 to 3.3. Maximum values were 3.3 and 3.0 for hair and blood, respectively. The 22

U

. S

. EPA’s IRIS entry for MeHg states, “Using ma ternal blood as the starting point, the 23

consolidated range from the three analyses is 1.7 to 3.0

. ” , this is consistent with the U.S. EPA’s 24

Water Quality Criterion document (U.S. EPA, 2001a) On this basis, a value of 3 was chosen to 25

serve as the numerical replacement for the default value of the portion of the UF related to 26

intraspecies TK variability. As no data were available to address intraspecies differences in 27

susceptibility (TD), this portion of the UF was left at the default value of 3. Together t hese 28

values for the components of UF H combine to equal a value of 10, which was characterized as a 29

“hybrid” value, comprising values based on default methodology and on data. 30

31

32

33May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 29 Table 6

. Comparison of Results from Three Analyses of the Interindividual Variability in the 1

Ingested Dose of MeHg Corresponding to a Given Maternal

- Hair or Blood Hg Concentration. 2

This is Table 3

- 1 from NRC (2000). 3

4

Study Maternal

M edium 50 th P ercentile a

(μg/kg

- d) 50 th P ercentile/

5 th P ercentile b 50 th P ercentile/

1 st P ercentile c

Stern (1997) Hair 0.03

– 0.05 d

(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

Blood e 0.02 2.1 2.8

Clewell et al.

(1999) Hair 0.08 1.5 1.8

Blood f 0.07 1.4 1.7

5

a Predicted 50 th percentile of the ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in 6

blood. 7

b Ratio of 50 th percentile of ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in blood 8

to the 5 th percentile. 9

c Ratio of 50 th percentile of ingested dose of methylmercury that corresponds to 1 ppm Hg in hair or 1 ppb in blood to 10

the 1 st percentile. 11

d Range reflects minimum and maximum values among eight alternative analyses. 12

e Data from J. Swartout, U.S. Environmental Protection Agency, personal commun.; June 9, 2000. 13

f Data from H.J. Clewell, ICF Consulting, personal commun.; April 19, 2000. 14

15

16

Acknowledgment : Some passages in this document were taken from the U.S. EPA’s IRIS entry 17

for Methylmercury (U.S. EPA, 2001b) ; some were taken from the U.S. EPA’s Water Quality 18

Criterion document for Methylmercury (U.S. EPA, 2001a) 19

20

References 21

22

Clewell, H.J., J.M. Gearhart, P.R. Gentry et al. 1999. Evaluation of the uncertainty in an oral 23

reference dose for methylmercury due to interindividual variability in pharmacokinetics. Risk 24

Anal. 19(4):547

- 558. 25

Grandjean, P., P. Weihe, R. White et al. 1997. Cognitive deficit in 7

- year

- old children with 26

prenatal exposure to methylmercury. Neurotoxicol. Teratol. 19(6):417

- 128. 27

Kjellstrom, T., P. Kennedy, S. Wallis and C. Mantell. 1986a. Physical and mental development 28

of children with prenatal expo sure to mercury from fish. Stage 1: preliminary tests at age 4. 29

Report 3080. Solna, Sweden: National Swedish Environmental Protection Board. 30May 11, 2011 DRAFT: DO NOT CITE OR QUOTE 30 Kjellstrom, T., P. Kennedy, S. Wallis et al. 1986b. Physical and mental development of children 1

with prenatal exp osure to mercury from fish. Stage 2: interviews and psychological tests at age 6. 2

Solna, Sweden: National Swedish Environmental Protection Board, Report 3642. 3

NRC (National Research Council). 2000. Toxicological effects of methylmer cury. Committee 4

on the Toxicological Effects of Methylmercury, Board on Environmental Studies and 5

Toxicology, Commission on Life Sciences, National Research Council

, Washington, DC: 6

National Academy Press. 7

Stern, A.H. 1997. Estimation of the interindividual variability in the one

- compartment 8

pharmacokinetic model for methylmercury: Implications for the derivation of a reference dose. 9

Regul. Toxicol. Pharmacol. 25(3):277

- 288 (As cited in Clewell et al., 1999). 10

Swartout, J. and G. Rice. 2000. Uncertainty analysis of the estimated ingestion rates used to 11

derive the methylmercury reference dose. Drug Clin. Toxicol. 23(1):293

- 306. 12

U.S

. EPA (U.S. Environmental Protection Agency). 200 1 a . Water Quality Criterion for the 13

Protection of Human Health: Methylmercury. Office of Science and Technology, Office of 14

Water. Washington, DC. EPA / 823 / R

- 01 / 001. Available at 15

http://www.epa.gov/waterscience/criteria/methylmercury/merctitl.pdf

. 16

U.S

. EPA (U.S. Environmental Protection Agency)

. 200 1b . Integrated Risk Information System 17

(IRIS) F ile for M ethylmercury. Available at http://www.epa.gov/iris/subst/0073.htm (accessed 18

9/10/2008)

. 19