# -~~~~ ~i ~2

Task Force

BY HAND 

# 6PPl-o2or3-ooi0

P.O . Box 331, Millwood, -'k 2'2t4B - (540)83?}1602



### July 26, 2010

Document Control Office Office ofPollution Prevention and Toxics Room6428 U.S. Environmental Protection Agency 1200 Pennsylvania Ave., N .W . Washington, DC 20460



### Re: Testina Consent Order for Ethylene Dichloride; Final Report (Docket No. OPPT-2003-0010) Dear Sirs: Enclosed in sextuplicate is a final report entitled "Route-to-Route Extrapolation of 1,2- Dichloroethane Studies fromthe Oral Route to Inhalation Using Physiologically Based Pharmacokinetic Models: Subchronic Toxicity in the Rat," as required under the Enforceable Consent Agreement for Ethylene Dichloride, 68 Fed. Reg. 33125 (June 3, 2003) (the "ECA") . Please do not hesitate to contact me if there is any question about this report . 

### Sincerely,

# ~--llt~i06~

~ Peter E. Voytek, Ph.D . Manager Enclosures cc: John E. Schaeffer W . Caffey Norman, Esq. 

## CONTAINS NOCBI 5110073p. 2



# : ~o1oooo'o o V13 Route-to-Route Extrapolation of 1,2-Dichloroethane Studies fromthe Oral Route to Inhalation Using Physiologically

Based Pharmacokinetic Models: Subchronic Toxicity in the Rat

Prepared for RAP Task Force, Millwood, Virginia

Prepared by Lisa M . Sweeney, Ph.D., DABT Ann Parker, B.S. Toxicology Excellence for Risk Assessment, Cincinnati, Ohio

July 22, 2010



# CO"'" INS NOCBI

### EDCSubchronic Route-to-Route July 22, 2010

Page 2 _ EXECUTIVE SUMMARY A need has been identified for a quantitative understanding of the hazards of 1,2-dichloroethane (ethylene dichloride, EDC, CAS No. 107-06-2) exposure by the inhalation route. Under Section 4 of the Toxic Substances Control Act (TSCA), the U.S. EPA issued a testing consent order (Enforceable Consent Agreement, ECA) to performtoxicity testing and mechanistic and pharmacokinetic studies to satisfy EPA's data needs for EDC (U.S. EPA, 2003, 2009) . As part ofTier I testing, pharmacokinetic studies were conducted (Saghir et al ., 2006) and a physiologically based pharmacokinetic (PBPK) model was developed that describes the disposition of EDCin rats by the oral and inhalation routes (Sweeney et al ., 2008) . This report serves to fulfill the identified data need for route-to-route extrapolation to the inhalation route ofresults of a subchronic toxicity study previously conducted by the oral route. The route-to-route extrapolation of results of the 90-day study of EDCusing the PBPK model was based on selection of critical endpoints of changes in hematocrit and liver and kidney weight changes, the most appropriate internal dose measures, and an appropriate point ofdeparture. The available data indicated that the most appropriate dose metric for route to route extrapolation of hepatic effects is the minimum post-exposure concentration of glutathione in the liver. For extrahepatic effects, a health-protective extrapolation of internal dose based on the amount of extrahepatic EDC metabolismwas used in route-to-route extrapolation. The specified points of' departure were the NOAEL and LOAEL of 37.5 and 75 mg/kg-day, respectively, which applied to both the hepatic and extrahepatic endpoints. Based on PBPK modeling results presented here, the rat NOAEL and LOAEL for extrahepatic effects in rats subchronically exposed to EDCby corn oil gavage are equivalent to continuous exposure of rats to 4.4 and 6.7 ppmEDC respectively, using extrahepatic metabolismas the dose metric that is equivalent in the gavage and inhalation scenarios . The hepatic effects, which are of uncertain biological significance, yielded higher rat NOAEL and LOAEL equivalents. Sensitivity analyses ofthe key internal dose metric at the oral and inhalation-equivalent NOAEL indicated that in both scenarios, the amount ofextrahepatic metabolismwas sensitive to the ventilation rate, but in opposite directions; the scenarios were otherwise generally sensitive to different parameters. For gavage dosing, the simulated amount of extrahepatic metabolism was sensitive to the ventilation rate, blood:air and slowly perfused tissues :air partition coefficients and the capacity for extrahepatic metabolism

. For inhalation exposure, the simulated amount ofextrahepatic metabolismmost sensitive to the ventilation rate and only moderately sensitive to any other physiological or biochemical parameters.

### EDC Subchronic Route-to-Route July 22, 2010

Page - INTRODUCTION 1,2-Dichloroethane (ethylene dichloride, EDC, CAS No. 107-06-2) is used as an intermediate in the production ofvinyl chloride, trichloroethylene, vinylidene chloride, and l,1,1- trichloroethane, which are chlorinated solvents used as ingredients in antiknock gasoline, paint solvents, coatings, adhesives, and a grain fumigant . A need has been identified for a quantitative understanding of the hazards of EDC exposure by the inhalation route. Under Section 4 of the Toxic Substances Control Act (TSCA), the U.S. EPA issued a testing consent order (Enforceable Consent Agreement, ECA) to performtoxicity testing and mechanistic and pharmacokinetic studies to satisfy EPA's data needs for EDC (U.S. EPA, 2003) ; this consent order was subsequently modified with respect to timing (U.S. EPA, 2009) . Summary of Physioloiz icallv Based Pharmacokinetic (PBPKMod_el A combination of experimental studies (D'Souza et al ., 1987, 1988; Gargas et al . 1986; Spreafico et al ., 1980

; Payan et al ., 1995; Reitz et al ., 1982; Withey and Karpinksi, 1985; Saghir et al ., 2006) and modeling (Sweeney et al ., 2008) was used to develop a physiologically based pharmacokinetic (PBPK) model that would allowroute-to-route extrapolation fromexisting and future data on hazards of oral EDCexposure to assess inhalation hazards . The Sweeney et al . (2008) model is an expansion and refinement of previous PBPK models (D'Souza et al ., 1987, 1988; Staats et al ., 1991 ; ENVIRON 2004) for disposition of EDC in male F344 rats based on EDC kinetics data following oral gavage exposure. Sprague-Dawley rats receiving intravenous (iv) doses of EDC (Spreafico et al ., 1980) rapidly cleared EDCfromthe blood. However, the D'Souza et al . (1987, 1988) model structure was not able to replicate the clearance (even when applying a large rate of metabolismin the liver), suggesting that EDCalso undergoes extrahepatic metabolism . EDCstudies (Spreafico et al ., 1980 ; Saghir et al ., 2006) indicate that pulmonary metabolismis not significant as evidenced by the lack of GSHdepletion in the lung; thus lung extrahepatic metabolismis not needed, although it was included in the D'Souza et al . (1987, 1988) model . Oral absorption of EDCwas initially described using a simple first-order description (D'Souza et al ., 1987, 1988) . However, when uptake fromthe GI tract was measured in rats dosed with radiolabeled EDC, it was found that approximately 50% of the administered radiolabeled EDC dose remained in the GI tract at 1 hr post dosing, but only an additional 15%

was absorbed in the following 3 hrs, indicating bi-phasic absorption (Payan et al ., 1995) . The expanded model (Sweeney et al ., 2008) included a two compartment GI tract where EDCwas rapidly absorbed fromthe first compartment then sent to either the portal blood or to a second GI compartment where additional absorption occurs, and the extrahepatic metabolism

was modeled as occurring in a venous blood "pool" fed by the slowly perfused tissues, kidney and other richly perfused tissues. Updated model parameters determined from previous models and literaturewere tested against the available data. An iterative approach was used to optimize the model parameters (hepatic metabolism, extrahepatic metabolism, exhalation rates, and absorption rates) ; the modified model was able to provide adequate estimates of GSHdependent metabolism . The revised model provided an adequate fit to all the rat data except

### EDCSubchronic Route-to-Route July 22, 2010

Page 4--- _ fetal tissue (a 3.3-fold difference was found between modeled and predicted fetal tissue concentrations) . The model can be used to calculate specified dose metrics of interest (blood concentrations, tissue concentrations, or amounts metabolized) after inhalation or gavage (corn oil or water) . Model code is provided in Appendix A . SUMMARY OF KEY STUDY Study Design A 90-day oral toxicity study of EDC administered by gavage in corn oil was conducted using male and female viral antibody-free Sprague-Dawley rats. Ten animals per sex served as vehicle controls. Sprague-Dawley rats (10/sex/dose) received 0 (vehicle only), 37.5, 75, or 150 mg/kgday, or vehicle only were administered to Each rat received a gavage volume of 0.1 ml per 100g body weight calculated fromweekly individual body weights (Daniel et al ., 1994) . Study Results No clinical signs of toxicity were seen during the 90-day study. Some changes were seen in hematology and chemistry analysis. Few gross and histological changes were found (single incidences) ; none of the changes were dose dependent . Male rats in the high-dose group (150 mg/kg-day) had a significant decrease in food consumption (data not shown in Daniel et al ., 1994) and body weight (17%) during the 90-day study compared to the controls. There were no significant differences in food consumption or weight gain patterns in the other treated rats compared to control rats. However, in a 10-day toxicity study by the same authors, 10/10 females and 8/10 males dosed at 300 mg/kg-day died before study end (Daniel et al, 1994) . Gross pathology examinations ofthe animals in the 10-day study revealed a diffuse reddening of the lungs. Changes in relative liver and kidney weights were seen in the mid- and high-dose group for both sexes. Female rats had increased liver and kidney weights at the high dose, but only increased kidney weights in the mid-dose (75 mg/kg-day) group. Males had significantly increased brain, liver and kidney weights at the mid- and high-doses; males also had decreased hemoglobin, hematocrit, and alkaline phosphatase levels at the same doses. At the high-dose level, red blood cells, lymphocytes, hemoglobin, hematocrit, potassium, and albumin levels were significantly decreased while platelets, white blood cells, neutrophils, and monocytes were increased in females. Fewgross and histological changes were found (single incidences) ; none of the changes were dose dependent. Effects for which statistically significant changes were observed at the mid-dose are summarized in Table 1 . Table 1 . Organ Weights and Hematology Parameters with Statistically Significant Changes at the Middle Dose in a Subchronic Stud of EDCin S ra e-Dawle Rats Daniel et al ., 1994 ) _ Control 37.5 mg/kg- 75 mg/kg-day 150 mg/kg-day

daya Females Kidney weight (%

of bodyweight) 0.67 t 0.09 0.70 f 0.06 0.77 t 0.07a 0.82 f 0.09a

### EDCSubchronic Route-to-Route July 22, 2010

Page 5 _ Males 

### Brain wt %

of bod y wei g ht) 0

.40+0 .03 0.40 ±0

.02 0 .43 f 0 .03a 0

.49t 0 .04a Kidne ywei ght %

ofbody wei g

ht) 0 .62f 0 .06 0.66t 0.06 0

.73 f 0 .05a 0

.84f 0 .07a Liver wei ght %

of bod ywei ght) 2.59t 0

.21 2.69t 0

.16 3.10t 0

.42a 3.40 ±0

.36a Hemoglobin H b /dL 16.2 f 0 .06 16.0+0.6 15.4 t 0 .5a 15.2 t 0

.7a Hematocrit (Hct) (%) 46.0 f 2.1 -- 45.4 t 1 .8 46.7 ± l .la 43.0 t 2.Oa aSignificantly different fromthe control group (p <_ 0.05) SELECTION OF CRITICAL ENDPOINTS ANDDOSE MEASURES Critical Endpoint The critical endpoint in Daniel et al . (1994) was the decrease in hemoglobin in male rats at 75 mg/kg-day compared to the controls in the 90 day study. Changes in relative liver and kidney weight will also be considered because, although these endpoints are considered to be of questionable biological significance (changes in relative weight without corresponding microscopic lesions), additional dose metrics may be considered relevant to route-to-route extrapolation, as discussed in the following paragraphs. Critical Dose Measures Consistentwith U.S. EPA's Guidelinesfor Carcinogen RiskAssessment and PBPK modeling guidance (U.S. EPA, 2005, 2006), the selection of an appropriate dose measure for toxicological endpoints of interest (both cancer and non-cancer endpoints) requires a careful consideration of the mode of action by which a chemical exerts an effect. Parent compound (peak, average, or area under the concentration vs. time curve [AUC]) and amount metabolized were suggested as dose metrics in the ECA (U.S. EPA, 2003) . In consideration of the toxicological endpoints of concern identified in the subchronic study, dose metrics potentially relevant to hepatic effects and extrahepatic effects have been identified. The dose metrics to be considered were expanded beyond those suggested in the ECA . For hepatotoxicity of EDC, the following dose metrics were considered: total amount of EDC metabolized in the liver (normalized to liver weight) (AMLVL), peak concentration of chloroacetaldehyde (metabolite) in the liver (CML), AUC of chloroacetaldehyde in the liver (AUCML), and the minimum concentration of glutathione in the liver (GSHL)

. For extrahepatic effects, the total amount of EDCmetabolized (normalized to body weight) (AMETBW) and the amount of EDC metabolized in extrahepatic tissues (normalized to body weight) (AMXBW) were considered to be the more logical metrics ; the peak concentration ofEDC in arterial blood (CA) and the AUC of EDCin arterial blood (AUCB) were also evaluated, in order to provide a comprehensive assessment . The data indicate that the most appropriate dose metric for route to route extrapolation of hepatic effects is the minimumpost exposure concentration of GSH in the liver (GSHLmin) . The reason for this choice and supporting data are presented in the following paragraphs. Less information

### EDCSub_chronic Route-to-Route July 22, 2010

Page 6 - is available for mode(s) of action for extrahepatic effects, so the route-to-route extrapolation for extrahepatic effects was based on the dose metric yielding the most conservative equivalent inhalation exposure, the amount of extrahepatic metabolism(normalized to body weight) . Supporting data are provided below . Igwe et al . (1986) evaluated the potential interaction of dietary disulfiram(Antabuse) and EDC exposure in male Sprague-Dawley rats treated with the compounds for 30 days. Disulfiramacts to block the metabolismof aldehydes by aldehyde dehydrogenase. One pathway for EDC metabolism, which competes with GSH conjugation, is oxidative metabolismto chloroacetaldehyde (Figure 1) ; co-exposure to disulfiramwould block the metabolismof chloroacetaldehyde by aldehyde dehydrogenase (ALDH), resulting in potentially greater accumulation of chloroacetaldehyde, generation of higher levels of the chloroacetaldehyde-GSH conjugate, and/or more extensive depletion of GSH . Igwe et al . (1986) found that the combined exposure to EDCand disulfiramincreased hepatotoxicity (mid-zonal necrosis), decreased spleen weight, and resulted in testicular atrophy. These findings support the use of dose metrics related to EDCmetabolismrather than parent compound as indicators of toxicity.

CI P45i0 CI

CI ALDFf GST S-G + GSH Cl

5-G CI C) '~~~ `Y` O

6H OH Figure 1 . Metabolic scheme for EDC Chloroacetaldehyde has been demonstrated to be hepatotoxic when administered directly to mice in drinking water (Daniel et al ., 1992) and chloroacetaldehyde is cytotoxic to isolated rat hepatocytes (Sood and O'Brien, 1993) . The studies by Sood and O'Brien (1993) included incubations with added antioxidants or GSH-depletion prior to the addition of chloroacetaldehyde. The greater susceptibility ofhepatocytes when GSHwas depleted indicates that the toxicity is not likely to be due to the generation of the GSH-chloroacetaldehyde conjugate. Incubations of hepatocytes with chloroacetaldehyde and added antioxidants produced delays in cytotoxicity, indicating that the overall antioxidant status is the best indicator of

### EDCSubchronic Route-to-Route July 22, 2010

Page 7 potential hepatotoxicity in chloroacetaldehyde-exposed liver cells. Thus, GSHLmin (lowest GSHconcentration after EDC exposure) is supported as the most appropriate dose metric for identifying an EDC inhalation concentration that would be expected to produce hepatotoxicity equivalent to that observed in gavage-exposed rats. In addition to its apparent hepatotoxicity, chloroacetaldehyde has also been implicated as a potential nephrotoxicant . The greater nephrotoxicity of ifosfamide vs. cyclophosphamide has been attributed to greater generation of chloroacetaldehyde fromifosfamide than from cyclosphosphamide. The nephrotoxic potential of chloroacetaldehyde has been demonstrated in ex vivo/in vitro systems (isolated perfused rat kidney, renal cortical slices, and cultured proximal tubules) (Zamlauski-Tucker et al ., 1994; Yaseen et al ., 2008a, 2008b; Knouzy et al ., 2010) . While these studies and Igwe et al . (1986) are generally supportive of chloroacetaldehyde (or its downstreammetabolites) as extrahepatic toxicants, the available data cannot provide sufficient support for one metabolism-related dose metric over another, so the lowest inhalation-equivalent NOAEL was selected for extrahepatic effects. ROUTE TO ROUTE EXTRAPOLATION METHODS Route-to-route extrapolation of the subchronic NOAEL and LOAEL for rats were performed using the PBPK model (Sweeney et al ., 2008) . Minor changes were made to the model code to convert it from

ACSL 11 .8.4 to acs1X (Version 2.5.0.6) and to facilitate computation ofthe dose metrics to be considered in the subchronic route to route extrapolation, interpretation of previously-conducted reproductive and developmental toxicology studies (Alumot et al ., 1976; Rao et al ., 1980), and design of the extended one-generation reproductive toxicity study (Appendix A) . Internal dose metrics for male and female rats dosed with 37.5 or 75 mg/kg-day EDCin corn oil for 90consecutive days (per Daniel et al ., 1994 study design) were determined fromPBPK model simulations (Appendix B, Table B-1) using end-of-study, group-specific body weights. Equivalent inhalation exposure concentrations were derived using default body weights for male and female rats (U.S. EPA, 1988) and assuming 24 hr/day exposure for 90consecutive days (continuous exposure) . Inhalation exposure concentrations producing NOAEL- and LOAEL-equivalent internal dose metrics were derived by iteratively simulating various trial concentrations until a trial concentration approximately matching the simulated internal dose fromthe gavage study was derived (Appendix B, Table B-3) . The level of precision of the equivalent exposure concentrations is two significant figures. ROUTE TO ROUTE EXTRAPOLATION RESULTS The consideration ofan array of dose metrics for both hepatic and extrahepatic effects yielded a range ofpotential NOAEL and LOAEL equivalents, reported in Appendix B and summarized here. For hepatic effects, the 24 hr/day NOAEL equivalent inhalation exposures ranged from20 to 80 ppm

; the most appropriate dose measure, the minimumliver GSHlevel, yielded a NOAEL, of 62 ppm

for continuous inhalation exposure of male rats. The hepatotoxicity LOAELequivalents ranged from32 to 100 ppm continuous inhalation exposure; minimumliver GSH

### EDC Subchronic Route-to-Route July 22, 201.0

Page 8

_ - yielded a LOAEL of 100 ppm for male rats. The extrahepatic toxicity 24 hr/day NOAELequivalents ranged from4.4 to 200 ppm and the LOAEL-equivalents ranged from6.7 to 340 ppm . The metabolism-related NOAEL- and LOAEL-equivalents for extrahepatic effects via inhalation exposure were lower than those related to parent compound. Of the dose measures considered in this analysis, the amount of extrahepatic metabolism (normalized to body weight) (AMXBW) yielded the most conservative NOAEL- and LOAELequivalents. Therefore this dose metric is farther considered in the sensitivity analyses and these corresponding inhalation equivalents of 4.4 ppm(NOAEL) and 6.7 ppm(LOAEL) (24 hrs/day) are recommended for quantitative evaluation ofsubehronic inhalation hazards of EDC in rats. SENSITIVITY ANALYSIS The route-to-route extrapolation of the subchronic oral study of EDCin rats involved the consideration of multiple endpoints (hepatic and extrahepatic) and internal dose metrics consistent with supportable modes of action, as computed using a PBPK model (Sweeney et al ., 2008) . The sensitivity of the critical dose metric, the simulated amount EDCmetabolized in extrahepatic tissues of female rats (AMXBW), to changes in model parameter values was evaluated for scenarios involving corn oil gavage or continuous inhalation. In the gavage scenario, a daily EDCdose of 37.5 mg/kg-day for 90 days, the NOAEL, was used as the basis of the analysis. The continuous inhalation equivalent for female rats, 4.4 ppm for 24 hrs/day for 90 days, was used as the basis of the inhalation sensitivity analysis. The sensitivity analysis was conducted using a relative change ("delta") of 0.0001 % for the input parameter and noting the change in the model prediction of interest (total extrahepatic metabolismnormalized to body weight, AMXBW), normalized to the baseline prediction of dose metric of interest. The fractional increase in the prediction divided by the fractional increase in the parameter was defined as the normalized sensitivity coefficient (NSC) . The results are summarized in Table 2. For the gavage scenario, AMXBW was very sensitive to the dose, blood:air and slowly perfused tissues :air partition coefficients (PB and PSA), ventilation rate (QPC), and the extrahepatic metabolismrate (expressed as a fraction of the rate of oxidative metabolismin the liver, XLRATIO) . Under the inhalation scenario, AMXBW was also very sensitive to QPC(but in the opposite direction) and to the exposure concentration. Table 2. Sensitivity Coefficients for Amount of EDC Metabolized in Extrahepatic Tissues (AMXB W) Oral dose (37.5 mg/kg- Inhalation exposure Parameter' 

### day) (4.4 pprn ) 

### Bod y wei g ht B -0.0087 -0.27 ~ Inhaled concentration (CONC) Not 0.96

### EDCSubchronic Route-to-Route _ July 22, 2010

Page 9 - applicable Gava e dose ( ODOSEQ 1 .3 Not applicable Alveolar ventilation rate PC -1 .00 0.88 

### Cardiac output CC 0 .27 -0.19 Fractional blood flowto liver LC -0.062 -0.35 Fractional volume ofadi pose fat tissue VFC 0.24 -0.000033 Blood:air partition coefficient PB 1 .7 0.084 Fat :air p artition coefficient PFA -0.90 -0.000038 Slowl y erfused tissues: air partition coefficient PSA 1 .6 -0.000029 Michaelis constant for oxidative metabolismof EDC KM -0.013 -0.27 Michaelis constant for EDC for GSHconjugation KMG 0.10 

### 0 .00071 Maximum

rate of oxidative metabolismof EDC in the liver VMAXLC 0.17 0.31 Maximal rate of extrahepatic EDC metabolism, as a fraction of maximumrate of oxidative metabolismof EDC in the liver XLRATIO 0.73 0.36 Maximum

rate of GSH conjugation of EDC in the liver VMAXLGC -0.39 -0.00071 aParameters not listed had INSCI<0.1 for both scenarios. In order to interpret the sensitivity analyses, it is helpful to consider the overall disposition of orally administered or inhaled dose (ODOSE or AINH, respectively) via elimination by exhalation (AEXH), liver metabolism(AML), or extrahepatic metabolism(AMX) . (Note: Even though AMXBW

is equivalent in these scenarios, the amounts [AMX in mg, rather than AMXBW

in mg/kg] of extrahepatic metabolismare not equal in these scenarios because the body weights differ; the gavage simulations used a study-specific body weight, while the inhalation-equivalent simulations used the default body weight specified in U.S. EPA (1988) . For the gavage scenario (37.5 mg/kg-day), the cumulative 90-day dose of 1049 mg, 339 mg are exhaled, 566 mg metabolized in the liver, and 143 metabolized extrahepatically. For the inhalation scenario (lowest NOAEL equivalent of 4.4 ppm, 24 hrs/day), 178 mg are inhaled, 16 mg exhaled, 68 mg metabolized in the liver, and 94 mg metabolized extrahepatically. Thus, while extrahepatic metabolismis the major route of EDC clearance in the inhalation scenario, it is the smallest contributor to gavage clearance. Viewed in this light, it is not so surprising that the key determinants ofAMXBW (i .e., sensitive parameters) differ between routes. Under the gavage scenario, a substantial fraction of dosed EDC is cleared by first pass metabolismin the liver; of the parent chemical that is not biotransformed by the liver, more is exhaled than is metabolized extrahepatically. Thus, an increase in the ventilation rate or decrease in PBwill increase the amount exhaled, so less EDCwill be cleared by extrahepatic metabolism

. The high sensitivity ofAMXBW to XLRATIO (see Table 2 for definition)

### EDCSubchronic Route-to-Route July 22, 2010

Pagel0 demonstrates that, under this scenario, extrahepatic metabolismis limited by the metabolic rate constants rather than tissue blood flow . The lack of sensitivity ofAMXBW to body weight (BW) for the gavage scenario indicates that the choice ofusing the end-of-study body weights reported by Daniel et al . (1994), rather than an estimate of initial weight or average weight did not have a significant effect on the point of departure for the route-to-route extrapolation. Under the inhalation scenario, the sensitivity ofAMXBW to ventilation rate is in the opposite direction. The total systemic dose of EDCis increased when ventilation rate is increased, so more EDCcan then be delivered to extrahepatic tissues for biotransformation to unspecified metabolites. Extrahepatic metabolismis decreased if blood flow to the liver increases, is almost equally sensitive to VMAXLC, XLRATIO, and KM and is insensitive to the rate of conjugation of EDCwith GSH in the liver (VMAXLGC and KMG) . These findings indicate that liver metabolismmay be flow limited, while extrahepatic metabolismis limited by the metabolic capacity (VMAXLC x XLRATIO/KM, at low concentration) . CONCLUSIONS The route-to-route extrapolation of results of the gavage subchronic EDC study using the PBP.K model was based on selection ofcritical endpoints, the most appropriate internal dose measures, and appropriate points of departure. For hepatotoxicity, a dose metric related to the apparent mode of action was chosen. For extrahepatic effects, a conservative dose measure was selected fromamong the options considered because of a lack of information to clearly support selection of another metric. The gavage rat NOAEL of 37.5 mg/kg-day was determined to be equivalent to continuous (24 hr/day) exposure of rats to 4.4 ppmEDC, when using the conservative dose metric of extrahepatic metabolism .

### EDC Subchronic Route-to-Route July 22, 2010

Page I 1 REFERENCES Alumot E, Nachtomi E, Mandel E, et al . (1976) . Tolerance and acceptable daily intake of chlorinated fumigants in the rat diet. Food Cosmet Toxicol . 14(2) :105-10 . Daniel FB, DeAngelo AB, Stober JA, Olson GR, Page NP . (1992) . Hepatocarcinogenicity of chloral hydrate, 2-chloroacetaldehyde, and dichloroacetic acid in the male B6C3F 1 mouse. Fundam Appl Toxicol . 19(2) :159-68. Daniel FB, Robinson M, Olson GR, et al . (1994) . Ten and ninety-day toxicity studies of 1,2- dichloroethane in Sprague-Dawley rats. Drug Chem Toxicol . 17(4) :463-77. D' Souza RW, Francis WR, Bruce RD, Andersen ME. (1987) . Physiologically based pharmacokinetic model for ethylene dichloride and its application in risk assessment. Drinking Water and Health, vot. 8. National Academy Press, Washington, DC. D' Souza RW, Francis WR, Andersen ME. (1988) . Physiological model for tissue glutathione depletion and increased resynthesis after ethylene dichloride exposure. J Pharmacol Exp Ther. 245(2) :563-8. ENVIRON. (2004) . Application of a PBPK Model for Cancer and Noncancer Risk Assessment of 1,2-Dichloroethane. Phase I : Evaluation of Issues Related to the Use of a PBPK Model for DCE. Requisition/Reference No. 2W2E59, QT-DC-030000387. Gargas ML, Andersen ME, Clewell HJ, 3rd. (1986) . Aphysiologically based simulation approach for determining metabolic constants fromgas uptake data. Toxicol Appl Pharmacol . 86(3) :341-52. Igwe OJ, Que Hee SS, Wagner WD . (1986) Interaction between 1,2-dichloroethane and disulfiram

. I . Toxicologic effects . FundamAppl Toxicol . 6(4) :733-46 Knouzy B, Dubourg L, Baverel G, Michoudet C . (2010) . Targets ofchloroacetaldehyde-induced nephrotoxicity. Toxicol In Vitro. 24(1) :99-107. Payan JP, Saillenfait AM, Bonnet P, Fabry JP, Langonne 1, Sabate JP. (1995) . Assessment ofthe developmental toxicity and placental transfer of 1,2-dichloroethane in rats. Fundam Appl Toxicol . 28(2) :187-98. Rao KS, Murray JS, Deacon MM, et al . (1980) . Teratogenicity and reproduction studies in animals inhaling ethylene dichloride. In: Banbury Report 5, Ethylene Dichloride: A Potential Health Risk (B. Ames, P. Infante, and R . Reitz, eds.) pp. 149-166. Cold Spring Harbor, NY. Reitz RH, Fox TR, Ramsey JC, Quast JF, Langvardt PW, Watanabe PG . (1982) .

### EDCSubchronic Route-to-Route July 22, 2010

Page 12 Pharmacokinetics and macromolecular interactions of ethylene dichloride in rats after inhalation or gavage. Toxicol Appl Pharmacol . 62(2) :190-204. Saghir SA, Clark AJ, Gilles MM, et al . (2006) . 1,2-Dichloroethane (EDC) : Limited Pharmacokinetics and MetabolismStudy in Fischer 344 Rats (February 28, 2006) . Toxicology and Environmental Research and Consulting, The Dow Chemical Company, Midland, Michigan. Sood C, O'Brien PJ . (1993) . Molecular mechanisms of chloroacetaldehyde-induced cytotoxicity in isolated rat hepatocytes. BiochemPharmacol . 46(9) :1621-6. Spreafico F, Zuccato E, Marcucci M, et al . (1980) . Pharmacokinetics of ethylene dichloride in rats treated by different routes and its long-terminhalatory toxicity. In: Ames, B., Infante, P., Reitz, R

. (Eds.), Ethylene Dichloride: A Potential Health Risk? Banbury Report 5. Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, pp. 107-133. Staats DA, Fisher JW, Connolly RB . ( 1991) . Gastrointestinal absorption of xenobiotics in physiologically based pharmacokinetic models. Atwo-compartment description. Drug Metab Dispos. 19(1) :144-8. Sweeney LM, Saghir SA, Gargas ML. (2008) . Physiologically based pharmacokinetic model development and simulations for ethylene dichloride (1,2-dichloroethane) in rats. Regul Toxicol Pharmacol . 51 :311-323. U.S. EPA (1988) . Recommendations for and Documentation ofBiological Values for Use in Risk Assessment . EPA/600/6-87/008. U.S. EPA (2003) . 1,2-Ethylene dichloride; Final Enforceable Consent Agreement and Testing Consent Order . Federal Register 68 No. 106, June 3, 2003, pp 33125-9 U.S. EPA

. (2005) . Guidelines for Carcinogen Risk Assessment U.S. Environmental Protection Agency, Washington, DC, EPA/630/P-03/OOlF, 2005. U.S. EPA

. (2006) Approaches for the Application of Physiologically Based Pharmacokinetic (PBPK) Models and Supporting Data in RiskAssessment (Final Report) . U.S. Environmental Protection Agency, Washington, D .C., EPA/600/R-05/043F. U.S. EPA (2009)

. 1,2-Ethylene Dichloride; Completion of EPA ProgramReview . Federal Register 74 No. 139, July 22, 2009, pp 36196-36198. http :l/www

.re~ulations .fzov/search%Re%!s/contentStrearner?object1d=09000064809t78d9&dispo si tion=attachment&contentTxpe=html Withey JR, Karpinski K . (1985) . The fetal distribution of some aliphatic chlorinated hydrocarbons in the rat aftervapor phase exposure. Biol Res Pregnancy Perinatol . 6(2) :79-88.

### EDC Subchronic Route-to-Route _ July 22, 2010

Page-13- - Yaseen Z, Michoudet C, Baverel G, Dubourg L. (2008a) . Mechanisms ofthe ifosfamide-induced inhibition of endocytosis in the rat proximal kidney tubule. Arch Toxicol . 82(9) :607-14. Yaseen Z, Michoudet C, Baverel G, Dubourg L. (2008b) . In vivo mesna and amifostine do not prevent chloroacetaldehyde nephrotoxicity in vitro. Pediatr Nephrol . 23(4) :611-8. Zamlauski-Tucker MJ, Morris ME, Springate JE. (1994) . Ifosfamide metabolite chloroacetaldehyde causes Fanconi syndrome in the perfused rat kidney. Toxicol Appl Pharmacol . 129(1) :170-5.p. 15



### EDCSubchronic Route-to-Route July 22, 2010 Page 14 APPENDIX A: PBPK MODEL CODE edc4.cs1 PROGRAM

: GLUTATHIONE DEPLETION MODEL FOR EDC (EDC4 .CSL) !Initial parameter values for the rat (DSouza et al . 1987, 1988) !Retyped, documentation modified by LMS 7/19/O1 !revised February 23, 2005 !Add kidney, update tissue volumes and flows per Brown et al ., 1997 !Adjust flow and volume calcs to ensure mass balance !Add chamber for closed chamber simulations, add iv administration !implement GSH delay per Environ report !revise GSH parameter calculations to ensure ss in unexposed !gsh turnover rates from Potter and Tran, tissue specific values !Input pcs as tissue :air and calculate tissue :blood !revised February 23, 2006 !add two compartment GI, repeat gavage dosing, GST conj of parent in liver !turn off lung metab for now !revised June 2006 extrahepatic metabolism, reformulate reactions !for oxidative metabolite! !2010-06-11 edited by Lisa M . Sweeney for acslX !2010-06-17 added feeding scenario to accommodate simulation of Alumot et al . 1976 '.and extended one gen ingestion scenario INITIAL !SPECIAL FLOW RATES! CONSTANT QPC=15 $!alveolar ventilation rate L/hr/kg^0 .74! CONSTANT QCC=15 $!Cardiac output L/hr/kg^0 .74! !FRACTIONAL BLOOD FLOWTO TISSUES! CONSTANT QLC = 0 .18 $!Fractional blood flow to liver! CONSTANT QFC = 0 .07 $!Fractional blood flow to fat! CONSTANT QSC = 0 .34 $!Fractional blood flow to slow! CONSTANT QKC = 0 .14 !Fractional blood flow to kidney QRC = 1 .0-(QLC + QFC + QSC + QKC) $!Fractional blood flow to rapid! !BODY WEIGHT! CONSTANT BW = 0 .22 $!Body weight (kg)! !FRACTIONAL TISSUE VOLUMES! CONSTANT VPC = 0 .005 $!Fraction lung tissue! CONSTANT VLC = 0 .037 $!Fraction liver tissue! CONSTANT VFC = 0 .07 $!Fraction fat tissue! CONSTANT VSC = 0 .59 $!Fraction slow tissue (skin and muscle)! CONSTANT VKC = 0 .0073 !Fraction kidney constant vvc = 0 .05 VRC = 0 .95- (vpc + vlc + vfc + vsc + vkc + vvc) $!Fraction rapid tissue! !PARTITION COEFFICIENTS! CONSTANT PPA = 33 $!Lung/air partition coefficient! CONSTANT PLA = 33 $!Liver/air partition coefficient! CONSTANT PFA = 340 $!Fat/air partition coefficient!p. 16



### EDCSubchronic Route-to-Route July 22, 2010 Page 15 CONSTANT PSA = 23 $!Slowly perfused tissue/air partition coefficient! CONSTANT PRA = 33 $!Richly perfused tissue/air partition coefficient! CONSTANT PKA = 33 $!Kidney/air partition coefficient! CONSTANT PB = 29 $!Blood/air partition coefficient!

pp=ppa/pb pl=pla/pb pf=pfa/pb ps=psa/pb pr=pra/pb pk=pka/pb CONSTANT MW = 98 .96 $!Molecular weight (g/mol)! !KINETIC CONSTANTS! CONSTANT VMAXIC = 3 .15 !!Maximum velocity of oxidative metabolism (mg/hrkg^0 .7)! CONSTANT KM = 0 .25 $!Michaelis-Menten constant (mg/L)! CONSTANT vmaxlgc=480 .0 $!enzy conj rate const gsh w parent(mg/(hr-kg^-0 .7))! constant kmg = 2000 !Km with respect to EDC ma/L (not rate limiting at relev conc?) constant kmgg = 125 !Km with respect to liver GSH in uM (rate limiting when gsh depleted) CONSTANT KGSM =2 .0 $!gsh conj rate const w metab (1/(uM-hr))! CONSTANT KFEE=4600 $!conj rate const w non gsh (1/hr)! CONSTANT Kdgsyn=0 .32 $!GSH synthase breakdown (1/hr)! CONSTANT Kdgsh1=0 .14 $!GSH turnover rate--liver! CONSTANT KDGSHP =0 .011 !Gsh turnover rate--lung CONSTANT KSL = 200 $!Maximum GSH production control (liver)! CONSTANT KSp = 200 $!Maximum GSH production control (lung)! CONSTANT Tau = 2 $!Time delay constant (hr)! CONSTANT GSO1 = 5500 $!Initial GSH concentration (uM)! constant gslmit = 1200 !mitochondrial GSH, does not conjugate or turnover CONSTANT GSOp = 1200 $!Initial GSH concentration (uM)! CONSTANT PLRATI0=0.0 $!MFO ratio lung/liver! constant racpgp=0 CONSTANT xLRATI0=0 .0 !MFO ratio extrahepatic/liver constant kdet = 0 .025 !P450 turnover constant (1/hr) constant kdi = 0 .0 !second order reaction rate for liver P450 inactivation by oxid metab ! 1/((mg-equiv/1)-hr) !DOSING INFO! CONSTANT CONC = 0 $!Inhaled concentration (ppm)! CONSTANT VCHC = 9 .1 !Total chamber volume (L) CONSTANT NRATS = 0. !number of rats in closed chamber Vch = vchc-nrats*bw !net chamber volume CONSTANT KLC = 0 .0 !loss rate to chamber AIO = conc*vch*mw/24450.0 !initial mass of chemical in chamber constant odosec = 0 !gavage dose at t=0 in mg/kg constant kas=1 !oral absorption rate from stomach constant kt = 1 !transport rate from stom to intestines constant kai = 1 ! oral absorption rate from intestines constant ivdosec = 0 . !iv dose at t=0 in mg/kg constant tinf=0 .01 !duration of iv injection (hr)

### EDCSubchronic Route-to-Route July 22, 2010

Page 1 6-- riv=ivdosec*bw/tinf constant FDOSEC =0 . ! daily dose in feed (Alumot study) in mg/kg constant CDOSEC = 0 . ! daily dose for continuous ingestion (water or feed) mg/kg/d constant TING = 12 . ! ingestion duration for continuous ingestion scenario (hrs) !TIMING PARAMETERS! CONSTANT TSTART =0 . $!Start of exposure (hrs)! CONSTANT TPER=24 CONSTANT TSTOP=120 CONSTANT POINTS=1200 $!Number of points in plot! CINT = TSTOP/POINTS $!Communication interval! constant TCHNG=6 !SCALED PARAMETERS! QC = QCC*BW**0.74 QP = QPC*BW**0.74 QL = QLC*QC QF = QFC*QC QS = QSC*QC QK = QKC*QC qr = qc-(ql+qf+qs+qk) VP = VPC*BW VL = VLC*BW VF = VFC*BW VS = VSC*BW VR = VRC*BW vk = vkc*bw vv = vvc*bw !Liver metabolism! VMAX10=VMAXIC*BW**0.7 vmaxlg = vmaxlgc*bw**0 .7 vmaxp= vmaxl0*plratio vmaxx=vmaxl0*xlratio AGS01=GSO1*VL !Lung metabolism! AGSOp=GSOp*VP P1=0 P1R=0 P2=0 P2R=0 P3--100 P3R=100 KgshprodLO=agsol*kdgshl !baseline liver gsh synthesis rate umol/hr r10=kgshprodl0 r20=kgshprodl0 kgshprodtdl0=kgshprodl0 kgshprodp0=agsop*kdgshp !baseline lung gsh synthesis rate umol/hr rpl0=kgshprodp0 rp20=kgshprodp0 kgshprodtdp0=kgshprodp0

### EDCSubchronic Route-to-Route July 22, 2010

Page 17 kgsynprodl0=kgshprodl0*,kdgsyn !baseline prod gsh synthetase umol/hr/hr kgsynprodp0=kgshprodp0*kdgsyn !base prdxn of gsh synthetase in lung END $!End of initial! DYNAMIC ALGORITHM IALG=2 $!Gear method for stiff systems! DERIVATIVE RAI = nrats*qp*(CA/pb - ci) -klc*ai AI = INTEG(RAI, AIO) cch= ai/vch cp = cch*24450/mw !CI=Concentration in inhaled air (mg/1)! CI=cch*pulse(tstart, tper, tchng) RAinh=qp*ci Ainh=INTEG(RAINH,0 .) !Algebraic solution for CA1 after gas exchange! !CA1 is arterial blood concentration after gas exchange! CA1= (QC*CV +QP*CI)/(QC + QP/PB) CX = CA1/PB raexh=qp*cx aexh=integ(raexh,0 .) !Mass balance for the lung tissue compartment! RAP = QC*(CA1-CA) - RAMpu AP = INTEG(RAP,0.0) Clung = AP/VP AUCP=INTEG(CP,0 .0) CA=C1ung/PP AUCB=INTEG(CA,0 .0) !UPTAKE BY ORAL ROUTE! RFEEDA = FDOSEC*BW*(0 .528*(PULSE(0 .0,24 .,1 .))+0.272*(PULSE(1 .,24 .,1 .))+0 .2*PULSE(16 .,24 .,1 .)) !Alumot study

RCDOSE= CDOSEC*BW/TING*(PULSE(0.0, 24 .,TING)) RING=RFEEDA+RCDOSE AING = INTEG(RING, 0.) RSTOM = -(KAs+kt)*STOM+RING $!dSTOM/dT! days=t/24 ODOSE =odosec*bw*(1 .0 + (int(days))) !repeat dosing STOM =INTEG(RSTOM,0 .0) +ODOSE $!amount in stomach (mg)! rintest = kt*stom - kai*intest intest = integ(rintest, 0 .) !AS = Amount in slowly perfused tissues (mg)! RAS = QS*(CA-CVS) AS = INTEG(RAS,0.0) CVS = AS/(VS*PS) CS = AS/VS !AR = Amount in richly perfused tissues (mg)!

### EDCSubchronic Route-to-Route July 22, 201.0

Pd&e-18 RAR = QR*(CA-CVR) AR = INTEG(RAR,0.0) CVR = AR/(VR*PR) CR = AR/VR !AK = Amount in kidney RAk = Qk*(CA-CVk) Ak = INTEG(RAk,0 .0) CVk = Ak/(Vk*Pk) Ck = Ak/Vk (mg) !

!AF = Amount in fat tissues (mg)' RAF = QF*(CA-CVF) . AF = INTEG(RAF,0.0) CVF = AF/(VF*PF) CF = AF/VF !CV = Mixed venous blood concentration (mg/1)! rinf=riv*pulse(0 ., 2000 ., tinf) ivdose--integ(rinf,0 .) RAVx = rinf + (QS*CVS + QR*CVR+ qk*CvK)-(qs+qr+qk)*CVx - ramx

AV = integ(ravx, 0 .) cvx=Av/vv

cv = QFc*CVF + QLc*CVL + cvx*(qsc + qrc + qkc) !AL = Amount in liver tissue (mg)! RAL = QL*(CA-CVL)-RAM1 + KAs*STOM+ kai*intest AL = INTEG(RAL,0 .0) CVL = AL/(VL*PL) CL = AL/VL AUCL = INTEG(CL,O .) !LIVER METABOLISM! !AM = Amount metabolized liver (mg)! RAM1= RAMox + RAMCon RAMox =(VMAXl*CVL)/(KM+CVL) ramcon = vmaxlg*(GS1/(gsl+kmgg))*(CVL/(cvl + kmg)) AM1=INTEG(RAM1,0 .) AMP1=AM1*1000/MW RAMP1=RAML*1000/MW !time-dependence of hepatic P950 oxidation due to inactivation by oxid metabolite rvmaxl = (vmaxl0-vmaxl)*kdet - vmaxl*kdi*CML vmaxl = INTEG(rvmaxl, vmaxl0) !CM1=0XIDATIVE METABOLITE LIVER mg/L)! RAMM1= ramox -RACMGl*MW/1000-RACMEE1*MW/1000 AMMI=INTEG(RAMM1,0 .) CML=AMM1/VL

### EDCSubchronic Route-to-Route July 22, 2010

Page 19 AUCML=INTEG(CML,O.) !ACPG1 = AMT PARENT CONJUGATED WITH GSH LIVER (uMOLES)! RACPG1=ramcon*1000/MW ACPG1=INTEG(RACPGI,O .) !ACMG1=AMT METABOLITE CONJUGATED WITH GSH LIVER (uMOLES)! RACMG1=KGSM*GS1*CM1*1000/MW*VL ACMG1=INTEG(RACMG1,0 .0) !ACMEE1=AMT METABOLITE CONJUGATED WITH EVERYTHING ELSE LIVER! !uMOLES! RACMEE1=KFEE*VL*CM1*1000/MW ACMEE1=INTEG(RACMEE1,0.) !LUNG METABOLISM! !AMp=Amount metabolized lung (mg)! RAMpu=RAMpox + rampcon rampox=(VMAXp*CA)/(KM+CA) rampcon=RACPGp*MW/1000 AMp=INTEG(rampu,0.) AMPp=AMp*1000 ./MW RAMPp=RAMpu*1000 ./MW !CMp=OXIDATIVE METABOLITE (mg/L)! RAMMp= rampox -RACMGp*MW/1000-RACMEEp*MW/1000 AMMp=INTEG(RAMMp,O.) CMp=AMMp/VP !ACMGp= AMT METABOLITE CONJUGATED WITH GSH LUNG (uMOLES)! RACMGp=KGSM*GSp*CMp*VP*1000/MW ACMGp=INTEG(RACMGp,O .) !ACMEEp=AMT METABOLITE CONJUGATED WITH EVERYTHING ELSE LUNG (uMOLES)' . RACMEEp=KFEE*VP*CMp*1000/MW ACMEEp=INTEG(RACMEEp,O .) !ACPGp=AMT PARENT CONJUGATED WITH GSH LUNG (uMOLES)! ! RACPGp=KGS*GSp*Ca*VP*1000/MW ACPGPp=INTEG(RACPGp,O.) !extrahepatic METABOLISM! !AMx = Amount metabolized extrahepatic (mg)! RAMx= RAMxox + RAMxCon amx=integ(ramx, 0 .) RAMxox =(VMAXx*CVx)/(KM+CVx) amxox = integ(ramxox, 0 .) ramxcon=0 amxcon=integ(ramxcon, 0 .)

'.gsh synthesis rate--time dependent kgshprodl=integ(kgsynprodl0*(ksl+gsol)/(ksl+gsl) & -kdgsyn*kgshprodl,kgshprodl0) kgshprodp=integ(kgsynprodp0*(ksp+gsop)/(ksp+gsp) & -kdgsyn*kgshprodp,kgshprodp0)

### EDCSubchronic Route-to-Route _ July 22, 2010

Page 20---- !time delay (Bishchoff et al . 1971) r0=kgshprodl rrl=(r0-rl)/tau rl=integ(rrl,rl0) rr2=(rl-r2)/tau r2=integ(rr2,r20) rr3=(r2-kgshprodtdl)/tau kgshprodtdl=integ(rr3, kgshprodtdl0) rp0=kgshprodp rrp1=(rp0-rpl)/tau rpl=integ(rrpl,rpl0) rrp2=(rpl-rp2)/tau rp2--integ(rrp2,rp20) rrp3=(rp2-kgshprodtdp)/tau kgshprodtdp=integ(rrp3, kgshprodtdp0) !GS1 = GIUTAHIONE LIVER (uM)!

RAMGS1=kgshprodtdl-Kdgshl*GS1*VL-RACMGI-RACPG1 AMGS1=INTEG(RAMGSl,AGS01) GS1=AMGS1/VL gshl = gsl + gslmit !GSp=GLUTAHIONE LUNG (uM)! RAMGSp=Kgshprodtdp-Kdgshp*GSp*VP-RACMGp-RACPGp AMGSp=INTEG(RAMGSp,AGSOp) GSp=AMGSp/VP !PCTGSH-PERCENT GSH COMPARED TO CONTROL! PCTGSHP=GSp/GSOp*100 !mass balance anet = AING+ odose + ivdose + ainh - aexh atissue=ap + as+ ar + al+ ak + af +av agi = stom + intest amet = aml + amp + amx AMETBW = AMET/BW !total amount metabolized, normalized to BW AMXBW= AMX/BW !extrahepatic metabolism normalized to BW AMLVL = AML/VL !liver metabolism normalized to BW termt(t .ge .tstop) END $!End of derivative! END $!End of dynamic! END $!End of program Rat .m % rat .m 0 2010-06-11 created from edc4 .cmd proced rat by Lisa M . Sweeney o physiol parameters from Brown et al . 1997 QPC=15; QCC=15; QLC=0 .18 ;QFC=0 .07 ; QSC=0 .34 ; QKC=0 .14 ; PB=29; PLA=33 ; PPA=10; PFA=340;PRA=33; PSA=23 ; PKA=33;p. 22



### EDCSubchronic Route-to-Route July 22, 2010 Page-21 VMAXLC=4 .0; KM=0 .25; PLRATI0=0 .0; XLRATI0=0 .3; %PLRATIO WA0 .026 VMAXLGC=4 .80; KMGG=530; KMG=20 .0; KGSM=2 .O;KFEE=4600.0; KDGSYN=0 .324 ;KDGSHL=0 .14 ; KDGSHP=0 .011 ; GSOL=5500;GSOP=1200; TAU=0 .89 ; KSL=1200; KSP=240; NRATS=O; KLC=O ; CONC=O ; IVDOSEC=O ; ODOSEC=O ;FDOSEC=O. ;CDOSEC=O; VCHC=9.1 ; KAS=8 ; KT=2; KAI=0 .15; o Default absorption parameters are for corn oil gavage TSTART=O; TPER=24; TSTOP=24 ; TCHNG=24 ; TINF=0 .01 ; Sdrat .m % sdrat .m a updated 5/19/2006 by Lisa M . Sweeney % updated 6/9/2006 LMS % 2010-06-10 sdrat m file created from edc4 .cmd files by Lisa M . Sweeney %proced sdrat %fat from schoeffner et al . 1999 opcs from Dsouza et al ., 1987 use rat VFC=0 .065; PB=28 ; PLA=30; PSA=22 ; BW=0.267 ; %default weight for a male SD rat in a subchronic study (EPA, 1988) Waterabsparam

.m %waterabsparam .m absorption parameters for administration in water KAS=5. ; KT=2 . ; KAI=1 .5; Alumot metrics.m oalumot_metrics .m %simulate dose metrics for Alumot et al . (1976) assuming absorption from diet is similar to absorption from water vehicle % body weight estimated as 0.2 kg per BW after 5 weeks of treatment o assume 500 ppm diet is -50 mg/kg/day, since authors state that 250 ppm diet is equivalent to 25 mg/kg/day % simulate one week and compute daily metrics by dividing by 7 days . use sdrat BW= .2 FDOSEC=50 TSTOP=168 disp("Alumot dose metrics 50 mg/kg/day)") disp("absorption parameters from corn oil") start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max( cml),

### EDCSubchronic Route-to-Route July 22, 2010

Page 22 disp("CA max") max( ca) use waterabsparam disp("absorption parameters from water") start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max^) max(_cml), disp("CA max") max ( ca) Rao repro 150.m orao_terat_300 % 150 ppm group, reproductive study of Rao et al . use sdrat BW=.250; o per paper TSTOP=168. ; TCHNG=6. ; CONC=150 .t start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max(_cml) disp("CA max") max( ca) Rao terat 300.m %rao_terat_300 0 300 ppm group, teratogencity study of Rao et al . use sdrat BW=.250 ; o per paper TSTOP=240. ; TCHNG=7 . ; CONC=300

. ; start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max(_cml), disp("CA max") max ( ca) Extonegen.m %extonegen .m eextended one generation reproduction study scenario use sdrat BW=.25; TSTOP=24 ; CDOSEC=50;

### EDCSubchronic Route-to-Route

Page 23 start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max(_cml) disp("CA max") max( ca) CDOSEC=100; start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max (_cm1) disp("CA max") max( ca) CDOSEC=200; start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max(_cml) disp("CA max") max( ca) CDOSEC=300; start @nocallback AMETBW, AMLVL, AUCML, AUCB disp("CML max") max(_cml) disp("CA max") max( ca)

### EDCSubchronic Route-to-Route _ July 22, 2010

Page 24 -- - -- APPENDIX B PBPK-Derived Internal Dosimetry and Route-to-Route Extrapolations for EDC-Exposed Rats Values ofthe dose metrics of arterial blood EDC, liver GSHor liver chloroacetaldehyde (metabolite) concentration and daily metabolismoccurring the liver (normalized to liverweight) or extrahepatic metabolismor total metabolism (normalized to body weight) were predicted using the PBPK models. Simulations wereconducted at the NOAEL (37.5 mg/kg-day) and LOAEL (75 mg/kg-day) for both sexes, and the outputs are provided in Table B-1 . Table B-1 . Internal dose metrics corresponding to the NOAEL and LOAEL in Daniel et al . 1994 rat subchronic study, as com puted using a PBPK model Sweene et al ., 2008

37.5 37.5 75 mg/kg, 75 mg/kg, mg/kg, mg/kg, female male female male (284 g) (562 g) 311 590 Total amount of EDCmetabolized, normalized by body weight (AMETBW) ( m g/kg BW 2283 2246 3779 3686 Total amount of EDCmetabolized in extrahepatic tissues, normalized by body wei ght AMXB (m

g/kg B 463 458 691 682 Maximum

concentration of EDCin arterial blood CAmax m/L 10.4 12.0 24.2 27.2 

### AUCfor EDCin arterial blood (AUCB) m EDCx hrs/L blood 1504 1836 3997 4922 Amount of EDC metabolized in liver, normalized by liver wt (AMLVL) (mg/kg liver 4.92 x 104 4.83 x 104 8.34 x 104 8.12 x 104 Maximum

concentration of EDC metabolite in the liver (CMLmax) (mg EDC-e uivalent/L liver 0 .0117 0.00953 0.0159 0 .0126 Area under the concentration vs. time curve (AUC) for EDCmetabolite in the liver (AUCML) (mg EDC-equivalent x hrs/L liver 3.29 3.20 6.17 5.85 Minimum

concentration of glutathione in the liver GSHLmin M 4415 4508 3297 3484

### EDCSubchronic Route-to-Route _ July 22, 2010

Page 25 -- Table B-2. Internal dose metrics corresponding to 24-hr exposure to a range of inhalation concentrations m as com puted using a PBPK model Sweene et al ., 2008



### Males Concentration 0 1 10 100 1000 AMETBWa 0 169 1675 14,543 25,882 AMXBW 0 101 927 3476 3842 CAmax 0 0.00965 0.106 2.420 97.531 AUCB 0 20.8 230 5216 21,0310 AMLVL 0 1850 20,225 299,110 595,680 CMLmax 0 5.43 x 10-5 6.15 x 10 0.0141 0.0284 AUCML 0 0.117 1 .32 26.7 46.7 ~ GSHLmin 6700 6673 6403 3491 1721 Females Concentration 0 1 10 100 1000 AMETBWa 0 181 1797 15,657 27,851 AMXBW 0 108 998 3763 4165 CAmax 0 0.00960 0.106 2.39 97.5 AUCB 0 20.7 228 5142 210,210 AMLVL 0 1978 21,608 32,1470 640,160 CMLmax 0 5.81 x 10" 6.59 x 10 0.0158 0.0315 AUCML 0 0 .126 1 .41 29.4 52.0 LGSHLmin 6700 6671 6383 3339 1660 aFor definitions and units, see Table B-1 . Table B-3. Inhaled concentrations (ppm) for 24-hr/day exposures to EDCfor 90consecutive days that yield simulated internal doses (Sweeney et al ., 2008) equivalent to subchronic NOAEL and LOAEL doses Subchronic Oral Dosing Scenario Dose Metric' 37.5mg/kgday, female 37.5

mg/kgday, male __

75 mg/kgday, female 75 mg/kgday, male Extrahe atic Effects AMETBW 12 13 21 22 AMXBW 4.4 4.7 6 .7 7.2 

### CAmax 200 220 340 360 AUCB 46 53 88 97 Hepatic Effects AMLVL 21 21 32 33 CMLmax 80 74 100 90 AUCML 20 21 12 33

### EDCSubchronic Route-to-Route July 22, 2010

Page 26 _ GSHLmin 61 62 100 10 'For definitions and units, see Table B-1 . The value ofthe "equivalent" inhaled concentration was highly dependent on the choice of internal dose metric. For example, the inhalation "equivalent" of 37.5 mg/kg-day by corn oil gavage to a female mouse ranged from 4.4ppm, based on the amount metabolized inextrahepatic tissues to 200 ppm, based on peakconcentration ofEDC in arterial blood. In general, the predicted concentration ofa compound inawell-perfused, non-metabolizing tissue that is not a portal ofentrywill track the concentration in the blood (i .e., tissue concentration ;:%- blood concentration x tissue :blood partition coefficient) . The choice ofAUCvs. peak for a given tissue also affects the results of the route-toroute extrapolation, as shown for both parent compound (EDC in blood) and metabolite (chloroacetaldehyde in liver) . Because the inhalation exposures rapidly come to steady-state, averageconcentration =AUC/duration,&peak concentration. In the cornoil gavage studies, average concentration < peakconcentration. Thus, starting from the gavage study, the choice ofAUCrather than peak sets a lower target blood or tissue concentration for determining the equivalent inhaled concentration. Mechanistic evidence indicate that minimumhepatic GSHis the most appropriate dose metric for route-to-route extrapolation ofliver effects (rationale provided in the main report), but route-to-route extrapolation results for other liver-related dose metrics are provided. For extrahepatic effects, the dose metricwhichyields to the lowest inhalationequivalent exposure is recommended, a NOAEL of 4.4 ppm and LOAEL of 6.7 ppmfor AMXBW .