EPA/635/R-16/079b Public Comment Draft www.epa.gov/iris

Toxicological Review of tert-Butyl (tert-)

(CASRN 75-65-0)

Supplemental Information – tert-Butyl Alcohol

April 2016

NOTICE

This document is a Public Comment Draft. This information is distributed solely for the purpose of pre-dissemination peer review under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. It is being circulated for review of its technical accuracy and science policy implications.

Integrated Risk Information System National Center for Environmental Assessment Office of Research and Development U.S. Environmental Protection Agency Washington, DC Supplemental Information―tert-Butyl Alcohol

DISCLAIMER

This document is a preliminary draft for review purposes only. This information is distributed solely for the purpose of pre-dissemination peer review under applicable information quality guidelines. It has not been formally disseminated by EPA. It does not represent and should not be construed to represent any Agency determination or policy. Mention of trade names or commercial products does not constitute endorsement or recommendation for use.

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CONTENTS

APPENDIX A. ASSESSMENTS BY OTHER NATIONAL AND INTERNATIONAL HEALTH AGENCIES ...... A-1 APPENDIX B. INFORMATION IN SUPPORT OF HAZARD IDENTIFICATION AND DOSE-RESPONSE ANALYSIS ...... B-1 B.1. TOXICOKINETICS ...... B-1 Absorption...... B-1 Distribution ...... B-2 Metabolism ...... B-2 ...... B-5 Physiologically Based Pharmacokinetic Models ...... B-6 B.2. PBPK MODEL EVALUATION SUMMARY ...... B-9 Evaluation of Existing tert-Butanol Submodels ...... B-9 Modification of Existing tert-Butanol Submodels ...... B-11 Summary of the PBPK Model for tert-Butanol ...... B-16 tert-Butanol Model Application ...... B-16 PBPK Model Code ...... B-16 B.3. OTHER PERTINENT TOXICITY INFORMATION ...... B-17 Other Toxicological Effects ...... B-17 Genotoxicity ...... B-31 Summary ...... B-35 APPENDIX C. DOSE-RESPONSE MODELING FOR THE DERIVATION OF REFERENCE VALUES FOR EFFECTS OTHER THAN CANCER AND THE DERIVATION OF CANCER RISK ESTIMATES ...... C-1 Noncancer Endpoints ...... C-1 Cancer Endpoints ...... C-23 REFERENCES ...... R-1

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TABLES

Table A-1. Health assessments and regulatory limits by other national and international health agencies ...... A-1 Table B-1. PBPK model physiologic parameters and partition coefficients ...... B-12 Table B-2. Rate constants for tert-butanol determined by optimization of the model with experimental data ...... B-15 Table B-3. Changes in weight in animals following exposure to tert-butanol ...... B-20 Table B-4. Changes in weight in animals following exposure to tert-butanol ...... B-23 Table B-5. Changes in liver histopathology in animals following exposure to tert-butanol ...... B-25 Table B-6. Changes in urinary bladder histopathology in animals following oral exposure to tert-butanol ...... B-27 Table B-7. Summary of genotoxicity (both in vitro and in vivo) studies of tert-butanol ...... B-34 Table C-1. Noncancer endpoints selected for dose-response modeling for tert-butanol ...... C-2 Table C-2. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in male F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk ...... C-3 Table C-3. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in female F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk ...... C-6 Table C-4. Summary of BMD modeling results for absolute kidney weight in male F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control mean ...... C-9 Table C-5. Summary of BMD modeling results for absolute kidney weight in female F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control mean ...... C-12 Table C-6. Summary of BMD modeling results for kidney inflammation in female rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk ...... C-15 Table C-7. Summary of BMD modeling results for absolute kidney weight in male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean ...... C-18 Table C-8. Summary of BMD modeling results for absolute kidney weight in female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean ...... C-21 Table C-9. Cancer endpoints selected for dose-response modeling for tert-butanol ...... C-24 Table C-10. Summary of the oral slope factor derivations ...... C-25 Table C-11. Summary of BMD modeling results for thyroid follicular cell adenomas in female B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk ...... C-26 Table C-12. Summary of BMD modeling results for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 5% extra risk ...... C-29 Table C-13. Summary of BMD modeling results for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in drinking water for 2 years, high dose omitted (NTP, 1995); BMR = 5% extra risk ...... C-32

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Table C-14. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk...... C-35 Table C-15. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk...... C-37 Table C-16. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk...... C-39 Table C-17. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk...... C-41 Table C-18. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk...... C-43 Table C-19. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk...... C-45 Table C-20. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-47 Table C-21. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and excluding high-dose group; re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-47 Table C-22. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-50 Table C-23. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-50 Table C-24. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-52 Table C-25. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk...... C-52

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Table C-26. Summary of the inhalation unit risk derivation ...... C-56

FIGURES

Figure B-1. Biotransformation of tert-butanol in rats and humans...... B-4 Figure B-2. Comparison of the tert-butanol portions of existing MTBE models with tert­ butanol concentrations from i.v. exposure by Poet et al. (1997)...... B-10 Figure B-3. Schematic of the PBPK submodel for tert-butanol in rats...... B-12 Figure B-4. Comparison of the EPA model predictions with measured tert-butanol blood concentrations for i.v., inhalation, and oral gavage exposure to tert-butanol...... B-15 Figure B-5. Comparison of the EPA model predictions with measured amounts of tert­ butanol in blood after repeated inhalation exposure to tert-butanol...... B-17 Figure B-6. Exposure-response array of other effects following oral exposure to tert-butanol...... B-29 Figure B-7. Exposure-response array of other effects following inhalation exposure to tert­ butanol...... B-30 Figure C-1. Plot of incidence by dose, with fitted curve for LogLogistic model for kidney transitional epithelial hyperplasia in male F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d ...... C-4 Figure C-2. Plot of incidence by dose, with fitted curve for Multistage 3° model for kidney transitional epithelial hyperplasia in female F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d ...... C-6 Figure C-3. Plot of mean response by dose, with fitted curve for Linear model with constant variance for absolute kidney weight in male F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control mean; dose shown in mg/kg-d ...... C-10 Figure C-4. Plot of mean response by dose, with fitted curve for Exponential (M4) model with constant variance for absolute kidney weight in female F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control mean; dose shown in mg/kg-d ...... C-13 Figure C-5. Plot of incidence by dose, with fitted curve for Logprobit model for kidney inflammation in female rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d ...... C-15 Figure C-6. Plot of mean response by concentration, with fitted curve for Hill model for absolute kidney weight in male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean; concentration shown in mg/m3 ...... C-19 Figure C-7. Plot of mean response by concentration, with fitted curve for Hill model for absolute kidney weight in female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean; concentration shown in mg/m3 ...... C-22

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Figure C-8. Plot of mean response by concentration, with fitted curve for Power model for absolute kidney weight in female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean; concentration shown in mg/m3 ...... C-22 Figure C-9. Plot of incidence by dose, with fitted curve for Multistage 3° model for thyroid follicular cell adenomas in female B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d ...... C-26 Figure C-10. Plot of incidence by dose, with fitted curve for Multistage 1° model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert­ butanol in drinking water for 2 years (NTP, 1995); BMR = 5% extra risk; dose shown in mg/kg-d ...... C-29 Figure C-11. Plot of incidence by dose, with fitted curve for Multistage 2° model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert­ butanol in drinking water for 2 years, high dose omitted (NTP, 1995); BMR = 5% extra risk; dose shown in mg/kg-d ...... C-32 Figure C-12. Plot of incidence by dose, with fitted curve for Multistage 2° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d...... C-35 Figure C-13. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk.; dose shown in mg/kg-d...... C-37 Figure C-14. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk.; dose shown in mg/L...... C-39 Figure C-15. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk; dose shown in mg/L...... C-41 Figure C-16. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and including all dose groups (NTP, 1995); BMR = 10% extra risk; dose shown in mg/hr...... C-43 Figure C-17. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk; dose shown in mg/hr...... C-45 Figure C-18. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with administered dose units and excluding

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high-dose group; re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d...... C-48 Figure C-19. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk; dose shown in mg/L...... C-51 Figure C-20. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, mg/hr) dose units and excluding high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.; dose shown in mg/hr...... C-53

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ABBREVIATIONS

AIC Akaike’s information criterion ARCO ARCO Chemical Company BMD benchmark dose BMDL benchmark dose lower confidence limit BMDS Benchmark Dose Software BMDU benchmark dose upper confidence limit BMR benchmark response BW body weight CFR Code of Federal Regulations CHO Chinese hamster ovary CYP450 cytochrome P450 DMSO dimethyl sulfoxide DNA deoxyribonucleic acid EDTA ethylenediaminetetraacetic acid EPA U.S. Environmental Protection Agency ETBE ethyl tert-butyl ether HBA 2-hydroxyisobutyrate HL human leukemia IC50 half-maximal inhibitory concentration i.p. intraperitoneal i.v. intravenous MFO mixed function oxidase MPD 2-methyl-1,2-propanediol MTBE methyl tert-butyl ether NADPH nicotinamide adenine dinucleotide phosphate NTP National Toxicology Program ·OH hydroxyl radical PBPK physiologically based pharmacokinetic POD point of departure SD standard deviation TWA time-weighted average

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1 APPENDIX A. ASSESSMENTS BY OTHER NATIONAL 2 AND INTERNATIONAL HEALTH AGENCIES

3 Table A-1. Health assessments and regulatory limits by other national and 4 international health agencies

Organization Toxicity value National Institute of Occupational Recommended Exposure Limit – 100 ppm (300 mg/m3) time-weighted Safety and Health (NIOSH, 2007) average (TWA) for up to a 10-hour workday and a 40-hour work week Occupational Safety and Health Permissible Exposure Limit for general industry – 100 ppm (300 mg/m3) TWA (OSHA, 2006) for an 8-hour workday Food and Drug Administration tert-Butyl alcohol: Indirect food additive that may be safely used in surface (FDA, 2011a, b) lubricants employed in the manufacture of metallic articles that contact food, subject to the provisions of this section (21 Code of Federal Regulations [CFR] 178.3910); substance may be used as a defoaming agent (21 CFR 176.200). 5

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1 APPENDIX B. INFORMATION IN SUPPORT OF 2 HAZARD IDENTIFICATION AND DOSE-RESPONSE 3 ANALYSIS

4 B.1. TOXICOKINETICS 5 Little information is available on the absorption, distribution, metabolism, or excretion of 6 tert-butyl alcohol (tert-butanol) in humans. The studies identified for this Toxicological Assessment 7 were conducted in conjunction with methyl tert-butyl ether (MTBE) or ethyl tert-butyl ether 8 (ETBE), as tert-butanol is a metabolite of both compounds. Several studies examining some aspect 9 of the toxicokinetic behavior of tert-butanol in animals have been identified. Many were carried out 10 in conjunction with other specific endpoints (e.g., developmental). ARCO (1983) determined no 11 differences in the of tert-butanol following either oral (i.e., gavage) or inhalation 12 exposure. Although some information is available for both oral and inhalation exposures, many 13 studies administered tert-butanol via intraperitoneal (i.p.) or intravenous (i.v.) injection. Although 14 these studies do not inform the absorption of tert-butanol, they can provide information on its 15 distribution, metabolism, and excretion.

16 Absorption 17 Toxicity data on tert-butanol submitted by industry to the U.S. Environmental Protection 18 Agency (EPA) under Section 8(e) of the Toxic Substances Control Act and other reporting 19 requirements indicate that tert-butanol is rapidly absorbed after oral administration. Very little of 20 the administered dose was excreted in the feces of rats, indicating 99% of the compound was 21 absorbed. Comparable blood levels of tert-butanol and its metabolites have been observed after 22 acute oral (350 mg/kg) or inhalation (6,060 mg/m3 for 6 hours) exposures in male Sprague-Dawley 23 rats (ARCO, 1983); the absorption rate after inhalation exposure could not be determined, however, 24 because the blood was saturated with radioactivity after 6 hours of exposure to 6,060 mg/m3. In 25 another study (Faulkner et al., 1989), blood concentrations indicated that absorption was complete 26 at 1.5 hours following the last of six oral gavage doses of 10.5 mmoles tert-butanol/kg (twice daily) 27 in female C57BL/6J mice. There was an apparent zero-order decline in tert-butanol concentration 28 for most of the elimination phase, and no differences in absorption or elimination rates was 29 observed between mice on a repeated dosing regimen and control mice administered equivalent 30 volumes of tap water every 12 hours before administration of a single dose of 10.5 mmoles tert­ 31 butanol/kg. The study therefore concluded that previous exposures did not affect the absorption or 32 elimination of tert-butanol (Faulkner et al., 1989).

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1 Distribution 2 The available animal data suggest that tert-butanol is distributed throughout the body 3 following oral, inhalation, and i.v. exposures (Poet et al., 1997; Faulkner et al., 1989; ARCO, 4 1983). Nihlén et al. (1995) calculated partition coefficients for tert-butanol using blood from human 5 volunteers and available information about the relative content of water and fat in each tissue. The 6 calculated tissue:blood partition coefficients for tert-butanol were slightly above 1 (from 1.02 to 7 1.06) for most tissues, except for fat:blood, which was 0.646. The same study evaluated the 8 partition coefficients of three oxygenated ethers, including MTBE and ETBE, which are metabolized 9 to tert-butanol (see Section B.1.4). The study concluded that, although tert-butanol preferentially 10 distributes in body water, the ethers distribute uniformly throughout the body with preference for 11 fatty tissues (Nihlén et al., 1995). 12 In a study aimed at determining whether tert-butanol (or metabolites) can bind to

13 2u-globulin, Williams and Borghoff (2001) exposed F-344 rats to a single gavage dose of 500 14 mg/kg 14C-tert-butanol. They found the radiolabel in three tissues (kidney, liver, and blood) in both α 15 sexes, but male rats retained more of the tert-butanol equivalents than females (Williams and 16 Borghoff, 2001). Radioactivity was found in the low-molecular-weight protein fraction isolated 17 from the kidney cytosol in male rats but not in female rats, indicating that tert-butanol or one of its

18 metabolites was bound to 2u-globulin. Further analysis determined that tert-butanol, and not its 19 metabolite acetone, was bound. Most tert-butanol in the kidney cytosol was eluted as the free α 20 compound in both males and females, but a small amount was associated with the high-molecular­

21 weight protein fraction in both males and females. In another study on 2u-globulin 22 nephropathy, Borghoff et al. (2001) found similar results after F-344 rats were exposed to 0, 250, α 23 450, or 1750 ppm tert-butanol by inhalation for 10 consecutive days. Male rat tert-butanol kidney­ 24 to-blood ratios were significantly elevated over ratios in females at all dose levels and exposure 25 durations. Although the female tert-butanol kidney-to-blood ratio remained similar with both 26 duration and concentration, the male tert-butanol kidney-to-blood ratio increased with duration. 27 The liver-to-blood ratios were similar regardless of exposure duration, concentration, or sex. Both 28 of these studies indicate distribution to the liver and kidney with kidney retention of tert-butanol in 29 the male rat.

30 Metabolism 31 A general metabolic scheme for tert-butanol, illustrating the biotransformation in rats and 32 humans, is shown in Figure B-1. Urinary metabolites of tert-butanol in a human male volunteer who 33 ingested a gelatin capsule containing 5 mg/kg [13C]-tert-butanol were reported to be 2-methyl-1,2­ 34 propanediol (MPD) and 2-hydroxyisobutyrate (Bernauer et al., 1998). Minor metabolites of 35 unconjugated tert-butanol, tert-butanol glucuronides, and traces of the sulfate conjugate also were 36 detected. The study was approved by an ethical review board, but no information regarding 37 informed consent was reported. In the same study, 2-hydroxyisobutyrate, MPD, and tert-butanol 38 sulfate were identified as major metabolites in rats, while acetone, tert-butanol, and tert-butanol

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1 glucuronides were identified as minor metabolites (Bernauer et al., 1998). Baker et al. (1982) found 2 that tert-butanol was a source of acetone, but acetone production might have been stimulated from 3 other sources. 4 No studies identified specific enzymes responsible for biotransforming tert-butanol. Using a 5 purified enzyme from Sprague-Dawley rats or whole-liver cytosol from Wistar rats, alcohol 6 dehydrogenase had negligible or no activity toward tert-butanol (Videla et al., 1982; Arslanian et al., 7 1971 ). Other in vitro studies have implicated the liver microsomal mixed function oxidase (MFO) 8 system, namely cytochrome P450 (CYP450) (Cederbaum et al., 1983; Cederbaum and Cohen, 1980). 9 In the 1983 study, incubation of tert-butanol at 35 mM with Sprague-Dawley rat liver microsomes 10 and a nicotinamide adenine dinucleotide phosphate-( NADPH) generating system resulted in 11 formaldehyde the production at a rate of approximately 25 nmoles/mg protein/30 min. According 12 to study authors, the amount of formaldehyde generated by tert-butanol was approximately 30% of 13 the amount of formaldehyde formed during the metabolism of 10 mM aminopyrene in a similar 14 microsomal system. The rate of formaldehyde generation from tert-butanol increased to about 15 90 nmol/mg protein/30 min upon addition of azide, which inhibits catalase and thereby prevents

16 the decomposition of hydrogen peroxide (H2O2). In other experiments in the same study,

17 formaldehyde formation was greatly reduced when H2O2 was included but NADPH was absent or 18 when the microsomes were boiled prior to incubation. Additionally, the rate of formaldehyde 19 formation in the microsomal oxidizing system depended on the concentration of tert-butanol, with

20 apparent Km and Vmax values of 30 mM and 5.5 nmol/min/mg protein, respectively. The study 21 authors concluded that tert-butanol is metabolized to formaldehyde by a mechanism involving 22 oxidation of NADPH, microsomal electron flow, and the generation of hydroxyl-radical (·OH) from

23 H2O2, possibly by a Fenton-type or a Haber-Weiss iron-catalyzed reaction involving CYP450, which 24 might serve as the iron chelate (Cederbaum and Cohen, 1980).

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1

CH3

glucuronide–O CH3

CH3 HO O t-butyl glucuronide HO CH3 rats, humans [O] CH3

CH3 OH 2-hydroxyisobutyric acid CYP450 O HO CH3 H C 3 H C OH rats, 3 H2C O CH3 humans OH CH3 CH3 t-butanol formaldehyde 2-methyl-1,2-propanediol O rats

- O H C CH O 3 3 S CH3 acetone O O CH3

CH3

2 t-butyl sulfate

3 Source: NSF International (2003), ATSDR (1996), Bernauer et al. (1998), Amberg et al. (1999), 4 and Cederbaum and Cohen (1980).

5 Figure B-1. Biotransformation of tert-butanol in rats and humans.

6 In a follow-up study, tert-butanol was oxidized to formaldehyde and acetone by various 7 systems known to generate ·OH radical, including rat liver microsomes or other nonmicrosomal 8 ·OH-generating systems (Cederbaum et al., 1983). The nonmicrosomal tests included two chemical 9 systems: (1) the iron-catalyzed oxidation of ascorbic acid (ascorbate-Fe-EDTA

10 [e thylenediaminetetraacetic acid]) and (2) the Fenton system of chelated ferrous iron and H2O2. In

11 both Fenton-type systems, H2O2 served as a precursor for ·OH. Additionally, a Haber-Weiss 12 enzymatic system involving xanthine oxidation by xanthine oxidase in the presence of Fe-EDTA was

13 used. In this system, ·OH is thought to be produced by the interaction of H2O2 and superoxide

14 (O2· ). Further experiments demonstrated the involvement of ·OH in either the ascorbate-Fe-EDTA 15 or the− xanthine oxidation systems based on inhibition of formaldehyde and acetone production 16 from tert-butanol when ·OH-scavenging agents (e.g., benzoate, mannitol) were added. Some 17 experiments in this study of the oxidation of tert-butanol by the microsomal metabolizing system of 18 the liver were similar to those in the previous study (Cederbaum and Cohen, 1980) except that 19 acetone formation, in addition to formaldehyde, also was measured. Again, these experiments 20 showed the dependence of the microsomal metabolizing system on an NADPH-generating system

21 and the ability of H2O2 to enhance, but not replace, the NADPH-generating system. Addition of

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1 chelated iron (Fe-EDTA) boosted the microsomal production of formaldehyde and acetone, while 2 ·OH-scavenging agents inhibited their production. The study authors noted that neither Fe-EDTA 3 nor ·OH-scavenging agents is known to affect the CYP450-catalyzed oxidation of typical MFO 4 substrates such as aminopyrene or aniline. The study also showed that known CYP450 inhibitors, 5 such as metyrapone or SKF-525A, inhibited the production of formaldehyde from aminopyrene but 6 not from tert-butanol. Finally, typical inducers of CYP450 and its MFO metabolizing activities, such 7 as phenobarbital or 3-methylcholanthrene, had no effect on microsomal metabolism of tert-butanol 8 to formaldehyde and acetone. According to the study authors, the oxidation of tert-butanol appears

9 to be mediated by ·OH (possibly via H2O2), which can be produced by any of the tested systems by a 10 Fenton-type reaction as follows:

11 H2O2 + Fe2+-chelate → ·OH + OH + Fe3+-chelate − 12 According to this reaction, reduction of ferric iron (Fe3+) to ferrous iron (Fe2+) is required 13 for continuous activity. The study authors concluded that the nature of the iron and the pathway of 14 iron reduction within the microsomes remain to be elucidated even though an NADPH-dependent

15 electron transfer or O2· might be involved (Cederbaum et al., 1983). − 16 Excretion 17 Human data on the excretion of tert-butanol derives from studies of MTBE and ETBE 18 ( Nihlén et al., 1998a, b). Eight or ten male human volunteers were exposed to 5, 25, or 50 ppm 19 MTBE (18.0, 90.1, 757 mg/m3) or ETBE (20.9, 104, and 210 mg/m3) by inhalation during 2 hours of 20 light exercise. The half-life of tert-butanol in urine following MTBE exposure was 8.1 ± 2.0 hours 21 (average of the 25- and 50-ppm MTBE doses); the half-life of tert-butanol in urine following ETBE 22 exposure was 7.9 ± 2.7 hours (average of 25- and 50-ppm ETBE doses). In both studies, the urinary 23 excretion of tert-butanol was less than 1% of the uptake or absorption of MTBE or ETBE. The renal 24 clearance rate of tert-butanol was 0.67 ± 0.11 mL/hr-kg with MTBE exposure (average of 25- and 25 50-ppm MTBE doses); the renal clearance rate was 0.80 ± 0.34 mL/hr-kg with ETBE exposure 26 (average of 25- and 50-ppm ETBE doses). 27 Amberg et al. (2000) exposed six volunteers (three males and three females, 28 ± 2 years 28 old) to 18.8 and 170 mg/m3 ETBE. Each exposure lasted 4 hours, and the two concentrations were 29 administered to the same volunteers 4 weeks apart. Urine was collected at 6-hour intervals for 30 72 hours following exposure. tert-Butanol and two metabolites of tert-butanol, 31 2- hydroxyisobutyrate (HBA) and MPD, also were identified in urine. At an ETBE level of 170 32 mg/m3, tert-butanol displayed a half-life of 9.8 ± 1.4 hours. At the low-exposure ETBE 33 concentration, the tert-butanol half-life was 8.2 ± 2.2 hours. The predominant urinary metabolite 34 identified was HBA, excreted in urine at 5–10 times the amount of MPD and 12–18 times the 35 amount of tert-butanol (note: urine samples had been treated with acid before analysis to cleave 36 conjugates). HBA in urine showed a broad maximum at 12–30 hours after exposure to both

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1 concentrations, with a slow decline thereafter. MPD in urine peaked at 12 and 18 hours after 2 exposure to 170 and 18.8 mg/m3 ETBE, respectively, while tert-butanol peaked at 6 hours after 3 exposure to both concentrations. 4 Amberg et al. (2000) exposed F344 NH rats to 18.8 and 170 mg/m3 ETBE. Urine was 5 collected for 72 hours following exposure. Similar to humans, rats excreted mostly HBA in urine, 6 followed by MPD and tert-butanol. The half-life for tert-butanol in rat urine was 4.6 ± 1.4 hours at 7 ETBE levels of 170 mg/m3, but half-life could not be calculated at the ETBE concentration of 8 18.8 mg/m3. Corresponding half-lives were 2.6 ± 0.5 and 4.0 ± 0.9 hours for MPD and 3.0 ± 1.0 and 9 4.7 ± 2.6 hours for HBA. In Sprague-Dawley rats treated with radiolabeled tert-butanol by gavage at 10 1, 30, or 500 mg/kg, a generally constant fraction of the administered radioactivity (23–33%) was 11 recovered in the urine at 24 hours postdosing. Only 9% of a 1500-mg/kg administered dose was 12 recovered in urine, however, suggesting that the urinary route of elimination is saturated following 13 this dose (ARCO, 1983). Among all tested doses, most of the urinary radiolabel was attributed to a 14 polar fraction that was not characterized, while only 0.3–5.5% of the administered dose was 15 considered tert-butanol. The saturation in urinary elimination of radioactivity with the increased 16 dose was considered a manifestation of saturated metabolic capacity; however, no further 17 information was provided on the fate or balance of the administered radiolabel at any of the tested 18 tert-butanol doses (ARCO, 1983).

19 Physiologically Based Pharmacokinetic Models 20 No physiologically based pharmacokinetic (PBPK) models have been developed specifically 21 for administration of tert-butanol. Some models have been used to study tert-butanol as the 22 primary metabolite after oral or inhalation exposure to MTBE or ETBE. The most recent models for 23 MTBE oral and inhalation exposure include a component for the binding of tert-butanol to

24 2u-globulin (Borghoff et al., 2010; Leavens and Borghoff, 2009). 25 Faulkner and Hussain (1989) used a one-compartment, open model with Michaelis-Menten α 26 elimination kinetics to fit tert-butanol blood concentrations obtained from C57BL/6J mice given i.p. 27 injections of 5, 10, or 20 mmol/kg tert-butanol. Elimination was indistinguishable from first-order

28 kinetics in the range of concentrations studied. An increase in Vmax and decrease in apparent 29 volume of distribution with dose are consistent with this model and suggest the existence of 30 parallel elimination processes. 31 Borghoff et al. (1996) developed a PBPK model for MTBE and its metabolite tert-butanol in 32 rats. Doses and blood levels were taken from several published studies. The initial model included a 33 tissue-specific, five-compartment model using blood, liver, kidney, muscle, and fat with liver 34 metabolism rate constants. The model predicted the accumulation of tert-butanol in blood, but not 35 its clearance. A two-compartment model was better at predicting tert-butanol blood levels, but the 36 volume of total body water had to be changed to obtain an adequate fit, suggesting dose-dependent 37 changes in the kinetics of tert-butanol. Overall, evaluation of the tert-butanol models suggests that

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1 the clearance of tert-butanol from the blood of rats after exposure to MTBE involves processes 2 beyond metabolic elimination. 3 Nihlén and Johanson (1999) developed a PBPK model for evaluation of inhalation exposure 4 in humans to the gasoline additive ETBE. Model compartments for ETBE included lungs (with 5 arterial blood), liver, fat, rapidly perfused tissues, resting muscles, and working muscles. The same 6 set of compartments and an additional urinary excretion compartment were used for the 7 metabolite, tert-butanol. First-order metabolism was assumed in the model, and tissue/blood 8 partition coefficients were determined by in vitro methods (Nihlén et al., 1995). Estimates of 9 individual metabolite parameters of eight subjects were obtained by fitting the PBPK model to 10 experimental data from humans (5, 25, or 50 ppm ETBE; 2-hour exposure) (Nihlén et al., 1998a). 11 This model primarily was applied to predict levels of the biomarkers ETBE and tert-butanol in 12 blood, urine, and exhaled air after various scenarios, such as prolonged exposure, fluctuating 13 exposure, and exposure during physical activity (Nihlén and Johanson, 1999). 14 Rao and Ginsberg (1997) developed a PBPK model for MTBE and its principal metabolite, 15 tert-butanol, based on the Borghoff et al. (1996) model. The modified model included a skin 16 compartment to simulate dermal absorption of MTBE during bathing or showering. A brain 17 compartment was added as a target organ for MTBE-induced neurological responses. MTBE 18 metabolism to tert-butanol was assumed to occur in the liver through two saturable pathways. The 19 tert -butanol portion of the model included further metabolism of tert-butanol in the liver, 20 exhalation in the lungs, and renal excretion (in the human model only). The model was validated 21 against published human and rat data and was used to help determine the contribution of tert­ 22 butanol to the acute central nervous system effects observed after MTBE dosing. 23 The Rao and Ginsberg (1997) model used peak concentrations of MTBE and tert-butanol in 24 the blood and brain for interspecies, route-to-route, and low-/high-dose extrapolations. The 25 MTBE/tert-butanol PBPK model was adapted to humans by adjusting physiology according to 26 literature values, incorporating the blood/air partition coefficient for humans reported by Johanson 27 et al. (1995), and allometrically scaling the metabolic rate based on body weight. A renal 28 elimination component was added to account for the small percentage of MTBE disposition that 29 occurs in humans via urinary excretion of tert-butanol. tert-Butanol concentrations in human blood 30 during and after MTBE exposure (25 or 50 ppm for 2 hours) were accurately predicted by the 31 human model (Johanson et al., 1995). 32 Kim et al. (2007) expanded the Borghoff et al. (1996) model to develop a multi-exposure 33 route model for MTBE and its primary metabolite, tert-butanol, in humans. The significant features 34 and advantages of the Kim et al. (2007) model are that parameters used for quantifying the 35 pharmacokinetic behavior of MTBE and tert-butanol are calibrated using time-series 36 measurements from controlled-exposure experiments in humans as reported by Prah et al. (2004). 37 MTBE partition coefficient values described in the Licata et al. (2001) model and skin compartment 38 parameters from the Rao and Ginsberg (1997) model were incorporated. The PBPK model for

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1 MTBE consists of nine primary compartments representing the lungs, skin, fat, kidney, stomach, 2 intestine, liver, rapidly perfused tissue, and slowly perfused tissue. The tert-butanol model consists 3 of three compartments representing blood, liver, and other tissue. 4 Leavens and Borghoff (2009) developed a PBPK model for inhalation exposures in male and 5 female rats that expanded on Borghoff et al. (1996) and Rao and Ginsberg (1997) to include the sex­

6 specific effects 2u-globulin, a protein unique to male rats, and to describe the 7 induction of tert-butanol metabolism after repeated exposures. Although the primary purpose of of MTBE binding to α 8 the model was to estimate MTBE and tert-butanol tissue concentrations after MTBE exposure, the 9 model also was parameterized to include inhalation uptake of tert-butanol. The tert-butanol portion 10 of the model was calibrated using data from rat exposures to tert-butanol and to MTBE. Model 11 compartments included blood, brain, fat, gastrointestinal tissues, kidney, liver, poorly perfused 12 tissues (blood flow <100 mL/min/100 g of tissue: bone, muscle, skin, fat), and rapidly perfused 13 tissues. 14 Distribution of MTBE and tert-butanol was assumed perfusion (i.e., blood-flow) limited. 15 This model used the same assumptions as Borghoff et al. (1996) regarding MTBE metabolism and 16 kinetics and further assumed that tert-butanol was metabolized only in the liver through one low­ 17 affinity pathway and excreted through urine. The model described binding of MTBE or tert-butanol

18 2u- 2u-globulin in the kidney. As

19 2u-globulin, the rate of of the protein decreases and causes with α globulin in the kidney, due to the high concentration of α 20 accumulation in the kidney; however, 2u-globulin affects its chemicals bind to α 21 synthesis, secretion, or circulating concentrations [Borghoff et al. (1990) as cited in Leavens and there is no evidence that binding of α 22 Borghoff (2009)]. Equations describing this phenomenon were included in the model for male rats

23 only 2u-globulin on metabolism of MTBE and tert­ 24 butanol. Partition coefficient values in the model that differed from those published in previous to account for the effects of the binding with α 25 PBPK models included poorly perfused tissues:blood and kidney:blood values. The kidney:blood 26 value was based on calculated kidney:blood concentrations in female rats only because of the lack

27 2u-globulin-associated effects in female rats. The deposition of tert-butanol during inhalation in 28 the nasal cavity and upper airways was reflected in the high blood:air partition coefficient for tert­ of α 29 butanol, and the ability of tert-butanol to induce its own metabolism after chronic exposure also 30 was taken into account. No differences in the induction of metabolism were reported between 31 males and females. The model simulated concentrations of MTBE and tert-butanol in the brain, 32 liver, and kidney of male and female rats following inhalation exposure at concentrations of 100, 33 400, 1,750, or 3,000 ppm MTBE, and compared them to measured concentrations of MTBE and tert­ 34 butanol from rats exposed at those levels. 35 Concentrations of MTBE and tert-butanol in the brain and liver were similar in male and 36 female rats during exposure and postexposure, but the concentrations of the chemicals in the 37 kidney significantly differed between male rats and female rats. The additional parameter

38 2u-globulin protein binding in this PBPK model more accurately reflects the

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1 metabolism of both MTBE and tert-butanol in male rat kidneys over time compared with other 2 PBPK models. The model highlights that binding can stimulate increased renal effects in male rats 3 after exposure to MTBE and tert-butanol. The assumptions made to reflect tert-butanol metabolism 4 induction and deposition in the nasal cavity and upper airways generally were supported by 5 measured data from rats exposed to 250-, 450-, or 1,750-ppm tert-butanol as evidenced by the fact 6 that the model was within one standard deviation of the mean concentrations for most data points. 7 The model overpredicted the concentration of tert-butanol in the brain, liver, and kidney of male 8 rats, however, after repeated exposures. 9 Borghoff et al. (2010) modified the PBPK model of Leavens and Borghoff (2009) by adding 10 oral gavage and drinking water exposure components to compare different dose metrics to the 11 toxicity observed across different studies. The Borghoff et al. (2010) model assumed first-order 12 uptake of MTBE absorption from the gut, with 100% of the MTBE dose absorbed for both drinking 13 water and oral gavage exposures. They conducted a series of pharmacokinetic studies comparing 14 the effects of different rat strains and different dosing vehicles on the blood concentration-time 15 profiles of MTBE and tert-butanol following MTBE exposure. The effects of exposure to MTBE via 16 drinking water, oral gavage, and inhalation routes over 7 and 91 days on male and female rats were 17 modeled and compared with measured data collected from F344 rats (exposed 28 days) and Wistar 18 Han rats (exposed 14 and 93 days). 19 The model predicted the blood concentrations of tert-butanol observed after 250 or 1,000 20 mg/kg -day administration of MTBE in males and females and the blood concentrations of MTBE 21 after 1,000 mg/kg-day. The model did not predict peak concentrations of MTBE, however, after 250 22 mg/kg -day in males or females using either olive oil or 2% Emulphor as vehicles. When comparing 23 strains, the blood concentrations were similar across strain and sex, except in female Sprague­ 24 Dawley rats administered 1,000 mg/kg-day MTBE. Female Sprague-Dawley rats had a significantly 25 (p-value not specified) higher blood concentration of both MTBE and tert-butanol compared with 26 F344 and Wistar Han females. The study authors considered this an outlier, however, and 27 maintained the metabolic patterns were similar. The model overpredicted the amount of MTBE in 28 the male rat kidney but accurately predicted the level of tert-butanol in the male rat kidney at all 29 exposures tested. The model did not accurately predict the kidney concentrations of tert-butanol in 30 the female kidney after exposure to MTBE via drinking water, but the study authors attributed the 31 inaccuracies to the study design as opposed to the model formulation. All tert-butanol entering the 32 submodel comes from MTBE metabolism in the liver, and the model does not include a separate 33 oral intake of tert-butanol.

43 B.2. PBPK MODEL EVALUATION SUMMARY 3 5 Evaluation of Existing tert-Butanol Submodels 3 6 The Blancato et al. (2007) and Leavens and Borghoff (2009) PBPK models for MTBE were 3 7 evaluated by comparing predictions from the tert-butanol portions of the models with the tert-butanol

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1 i.v. data of Poet et al. (1997) (see Figure B-2). Neither model adequately represented the tert-butanol 2 blood concentrations. Modifications of model assumptions for alveolar ventilation, explicit pulmonary 3 compartments, and induction of metabolism of tert-butanol did not significantly improve model fits 4 to the data. Attempts to reoptimize model parameters in the tert-butanol submodels of Blancato et al. 5 (2007) and Leavens and Borghoff (2009) to match blood concentrations from the i.v. dosing study 6 were unsuccessful. 7 (A) (B)

8 9 Neither the (A) Blancato et al. (2007) nor the (B) Leavens and Borghoff (2009) model adequately 10 represents the measured tert-butanol blood concentrations.

11 Figure B-2. Comparison of the tert-butanol portions of existing MTBE models 12 with tert-butanol blood concentrations from i.v. exposure by Poet et al. 13 (1997).

14 The PBPK submodel for tert-butanol in rats was developed in acslX (Advanced Continuous 15 Simulation Language, Aegis, Inc., Huntsville, Alabama) by modifying information from the many PBPK 16 models developed in rats and humans for the structurally related substance, MTBE, and its metabolite 17 tert-butanol (Borghoff et al., 2010; Leavens and Borghoff, 2009; Blancato et al., 2007; Kim et al., 18 2007; Rao and Ginsberg, 1997; Borghoff et al., 1996). A brief description comparing the Blancato et al. 19 (2007) and Leavens and Borghoff (2009) models is provided, followed by an evaluation of the MTBE 20 models and the assumptions adopted from MTBE models or modified in the tert-butanol model. 21 The Blancato et al. (2007) model is an update of the earlier Rao and Ginsberg (1997) model, and 22 the Leavens and Borghoff (2009) model is an update of the Borghoff et al. (1996) model. Both 23 the Blancato et al. (2007) and Leavens and Borghoff (2009) models are flow-limited models that 24 predict amounts and concentrations of MTBE and its metabolite tert-butanol in blood and six tissue 25 compartments: liver, kidney, fat, brain, and rapidly and slowly perfused tissues. These tissue 26 compartments are linked through blood flow, following an anatomically accurate, typical, 27 physiologically based description (Andersen, 1991). The parent (MTBE) and metabolite

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1 (tert-butanol) models are linked by the metabolism of MTBE to tert-butanol in the liver. Routes of 2 exposure included in the models are oral and inhalation for MTBE; Leavens and Borghoff (2009) 3 included inhalation exposure to tert-butanol. Oral doses are assumed 100% bioavailable and 100% 4 absorbed from the represented with a first-order rate constant. Following 5 inhalation of MTBE or tert-butanol, the chemical is assumed to enter the systemic blood supply 6 directly, and the respiratory tract is assumed to be at pseudo-steady state. Metabolism of MTBE by 7 CYP450s to formaldehyde and tert-butanol in the liver is described with two Michaelis-Menten 8 equations representing high- and low-affinity enzymes. tert-Butanol is either conjugated with 9 glucuronide or sulfate or further metabolized to acetone through MPD and HBA; both processes are 10 described by a single Michaelis-Menten equation in the models. All model assumptions are valid for 11 tert -butanol and were applied to the EPA-modified tert-butanol PBPK model, except for the 12 separate brain compartment. The brain compartment was lumped with other richly perfused 13 tissues in the EPA-modified tert-butanol PBPK model. 14 In addition to differences in parameter values between the Blancato et al. (2007) and 15 the Leavens and Borghoff (2009) models, the model structure has three differences: (1) the alveolar 16 ventilation was reduced during exposure, (2) the rate of tert-butanol metabolism increased over time

17 due to induction of CYP enzymes, and (3) binding of MTBE and tert-butanol to α2u-globulin was 18 simulated in the kidney of male rats. The Blancato et al. (2007) model was configured through EPA’s 19 PBPK modeling framework, ERDEM (Exposure-Related Dose Estimating Model), which includes 20 explicit pulmonary compartments. The modeling assumptions related to alveolar ventilation, 21 explicit pulmonary compartments, and induction of metabolism of tert-butanol are discussed in this 22 model evaluation section.

23 MTBE and tert-butanol binding to 2u-globulin in the kidneys of male rats were incorporated in

24 the PBPK model of MTBE by Leavens and Borghoff (2009). Binding to 2u-globulin is one hypothesized α 25 mode of action for the observed kidney effects in MTBE-exposed animals. For a detailed description of α 26 the role of 2u-globulin and other modes of action in kidney effects, see the kidney mode of action 27 section of the Toxicological Review (Section 1.2.1). In the Leavens and Borghoff (2009) model, binding of α 28 MTBE to 2u-globulin was applied to sex differences in kidney concentrations of MTBE and tert­ 29 butanol, but acceptable estimates of MTBE and tert-butanol pharmacokinetics in the blood are α 30 predicted in other models that did not consider 2u-globulin binding. Given the uncertainty of tert­

31 butanol binding to 2u-globulin, it was not included in the tert-butanol PBPK submodel. α 32 Modificationα of Existing tert-Butanol Submodels 33 To account for the tert-butanol blood concentrations after i.v. tert-butanol exposure, the 34 model was modified by adding a pathway for reversible sequestration of tert-butanol in the blood (see 35 Figure B-3). The PBPK model represented the rate of change in the amount of tert-butanol in the

36 sequestered blood compartment (Ablood2) with the following equation, where KON is the binding rate

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1 constant, CV is the free tert-butanol concentration in blood, KOFF is the unbinding rate constant, and

2 Cblood2 is the concentration of tert-butanol bound in blood (equal to Ablood2/Vblood).

3 dAblood2/dt = KON*CV* − KOFF *Cblood2

4 5 6 Exposure can be via multiple routes, including inhalation, oral, or i.v. dosing. Metabolism of tert-butanol, 7 which occurs in the liver, is described by Michaelis-Menten equations with one pathway for tert-butanol. 8 tert-Butanol is cleared via exhalation and via urinary excretion. See Table B-1 for definitions of parameter 9 abbreviations.

10 Figure B-3. Schematic of the PBPK submodel for tert-butanol in rats.

11 Table B-1. PBPK model physiologic parameters and partition coefficients

Body weight and organ volumes as fraction of body weight Body weight (kg) 0.25 (Brown et al., 1977)

Body fraction that is blood perfused (Fperf ) 0.8995 (Brown et al., 1977) Liver 0.034 (Brown et al., 1977) Kidney 0.007 (Brown et al., 1977) Fat 0.07 (Brown et al., 1977)

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Rapidly perfused 0.04 (Brown et al., 1977) Slowly perfused 0.7485 a Blood 0.074 (Brown et al., 1977) Cardiac output and organ blood flows as fraction of cardiac output Cardiac output (L/hr) 5.38 (Brown et al., 1977)b Alveolar ventilation (L/hr) 5.38 (Brown et al., 1977)c Liver 0.174 (Brown et al., 1977)d Kidney 0.141 (Brown et al., 1977) Fat 0.07 (Brown et al., 1977) Rapidly perfused 0.279 e Slowly perfused 0.336 (Brown et al., 1977) Partition coefficients for tert-butanol Blood:air 481 (Borghoff et al., 1996) Liver:blood 0.83 (Borghoff et al., 1996) Fat:blood 0.4 (Borghoff et al., 1996) Rapidly perfused:blood 0.83 (Borghoff et al., 1996) Slowly perfused:blood 1.0 (Borghoff et al., 1996) Kidney:blood 0.83 (Borghoff et al., 1996)

a Fperf − Σ(other compartments). b 15.2*BW0.75 (BW = body weight). c Alveolar ventilation is set equal to cardiac output. d Sum of liver and gastrointestinal blood flows. e 1 − Σ(all other compartments).

1 The physiologic parameter values obtained from the literature are shown in Table B-1 2 ( Brown et al., 1977). tert-Butanol partition coefficients, determined by the ratios of measured 3 tissue:air and blood:air partition coefficients (Borghoff et al., 1996), also were obtained from 4 literature. The parameters describing rate constants of metabolism and elimination of tert-butanol also 5 wer e obtained from the literature (Blancato et al., 2007) and were kept fixed because they were 6 optimized to tert-butanol blood concentrations measured after MTBE exposure, which is also 7 metabolized to tert-butanol. The parameters describing tert-butanol absorption and tert-butanol 8 sequestration in blood were estimated by optimizing the model to the time-course data for blood tert­ 9 butanol for rats exposed via i.v., inhalation, and oral routes (Leavens and Borghoff, 2009; Poet et al., 10 1997 ; ARCO, 1983). The model parameters were estimated with the acslX optimization routine to 11 minimize the log-likelihood function of estimated and measured tert-butanol concentrations. The 12 Nedler-Mead algorithm was used with heteroscedasticity and allowed to vary between 0 and 2. The 13 predictions of the model with optimized parameters have a much-improved fit to the tert-butanol 14 blood concentrations after tert-butanol i.v. exposures, as shown in panel A of Figure B-4. Additionally,

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1 the model adequately estimated the tert-butanol blood concentrations after inhalation and oral gavage 2 exposures. The optimized parameter values are shown in Table B-2. The ARCO (1983) study measured 3 tert-butanol in plasma only, unlike the Poet et al. (1997) and Leavens and Borghoff (2009) studies, 4 which measured tert-butanol in whole blood. Based on the measurements of plasma and whole blood 5 by JPEC (2008), the concentration of tert-butanol in plasma is approximately 60% of the concentration 6 in whole blood. The tert-butanol plasma concentrations measured by ARCO were increased (divided by 7 60%) to the expected concentration in whole blood for comparison with the PBPK model. 8 Induction of tert-butanol-metabolizing enzymes was included in the Leavens and Borghoff 9 (2009) model of MTBE based on their study of rats exposed for 8 days to tert-butanol via inhalation. 10 The enzyme induction equation and parameters developed in the Leavens and Borghoff (2009) 11 model that were applied to the tert-butanol submodel are as follows.

12 Vmax tert-butanol IND = Vmax tert-butanol *INDMAX(1-exp(-KIND*t))

13 Vmax tert-butanol IND is the maximum metabolic rate after accounting for enzyme induction,

14 Vmax tert-butanol is the metabolism rate constant from Table B-2 for both tert-butanol pathways, 15 and INDMAX is the maximum percent increase in Vmax tert-butanol (124.9). KIND is the rate 16 constant for enzyme induction (0.3977/day). The increased tert-butanol metabolism better 17 estimates the measured tert-butanol blood concentrations as can be seen in the comparison of the 18 model predictions and experimental measurements shown in Figure B-5. The model better 19 predicted blood concentrations in female rats than male rats. The male rats had lower tert-butanol 20 blood concentrations after repeated exposures compared with female rats, and this difference could 21 indicate greater induction of tert-butanol metabolism or other physiologic changes such as 22 ventilation or urinary excretion in males. The current data for tert-butanol metabolism do not 23 provide sufficient information for resolving this difference between male and female rats. 24

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1 (A) (B)

2 3 (C)

4 5 Source: (A) i.v. data from Poet et al. (1997); (B) inhalation data from Leavens and Borghoff (2009); and (C) 6 oral gavage data from ARCO (1983) with the optimized parameter values as shown in Table B-2.

7 Figure B-4. Comparison of the EPA model predictions with measured tert­ 8 butanol blood concentrations for i.v., inhalation, and oral gavage exposure to 9 tert-butanol.

10 Table B-2. Rate constants for tert-butanol determined by optimization of the model 11 with experimental data

Rate Constant Value Source or Reference

a Metabolism (VMTBA; mg/kg-hr) 8.0 Blancato et al. (2007)

Metabolism (KMTBA; mg/L) 28.8 Blancato et al. (2007)

Urinary elimination (KELIM2; 1/hr) 0.5 Blancato et al. (2007)

TBA sequestration rate constant (KON; L/hr) 0.148 Optimized

TBA unsequestration rate constant (KOFF; L/hr) 0.0134 Optimized

Absorption from gastrointestinal tract (KAS2; 1/hr) 0.5 Optimized a Scaled by BW0.7 (0.250.7 = 0.379), BW = body weight.

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1 Summary of the PBPK Model for tert-Butanol 2 A PBPK model for tert-butanol was developed by modifying previous models for MTBE and 3 tert -butanol (Leavens and Borghoff, 2009; Blancato et al., 2007). Published tert-butanol sub-models 4 do not adequately represent the tert-butanol blood concentrations measured in the i.v. study (Poet 5 et al., 1997). The addition of a sequestered blood compartment for tert-butanol substantially 6 improved the model fit. The alternative modification—changing to diffusion-limited distribution 7 between blood and tissues—also improved the model fit, but was considered less biologically 8 plausible. Physiological parameters and partition coefficients were obtained from published 9 measurements. The rate constants for tert-butanol metabolism and elimination were from a 10 published PBPK model of MTBE with a tert-butanol subcompartment (Blancato et al., 2007). 11 Additional model parameters were estimated by calibrating to data sets for i.v., oral, and inhalation 12 exposures and repeated dosing studies for tert-butanol. Overall, the model produced acceptable fits 13 to multiple rat time-course datasets of tert-butanol blood levels following inhalation or oral gavage 14 exposures.

15 tert-Butanol Model Application 16 The PBPK model as described above was applied to toxicity studies to predict tert-butanol 17 blood concentrations (the preferred internal dose metric in the absence of evidence linking any 18 specific metabolite of tert-butanol to any toxic effect). For simulation studies where tert-butanol 19 was administered in drinking water, the consumption was modeled as episodic, based on the 20 pattern of drinking observed in rats (Spiteri, 1982).

21 PBPK Model Code 22 The PBPK acslX model code is available electronically through EPA’s Health and 23 Environmental Research Online (HERO) database. All model files may be downloaded in a zipped 24 workspace from HERO (U.S. EPA, 201#, HEROID##). 25

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1

2

3 Male rats were exposed to 239, 444, or 1726 ppm and female rats were exposed to 256, 444, or 4 1914 ppm tert-butanol for up to 8 consecutive days (Borghoff et al., 2001). tert-Butanol blood 5 concentrations are better predicted by the model after 8 days of exposure with enzyme induction (right 6 panels) compared to without enzyme induction (left panels).

7 Figure B-5. Comparison of the EPA model predictions with measured amounts 8 of tert-butanol in blood after repeated inhalation exposure to tert-butanol.

9 B.3. OTHER PERTINENT TOXICITY INFORMATION

10 Other Toxicological Effects 11 B.3.1.1. Synthesis of Other Effects 12 Effects other than those related to kidney, thyroid, reproductive, developmental, and 13 neurodevelopmental effects were observed in some of the available rodent studies. These include 14 liver and urinary bladder effects. As previously mentioned in the Study Selection section of the 15 To xicological Review, all studies discussed employed inhalation, oral gavage, or drinking water 16 Studies are arranged in evidence tables by effect, species, duration, and

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1 design. The design, conduct, and reporting of each study was reviewed, and each study was 2 considered adequate to provide information pertinent to this assessment. 3 Central nervous system effects similar to those causes, in terms of animals 4 appearing intoxicated and having withdrawal symptoms after cessation of oral or inhalation 5 exposure, were observed with tert-butanol. Severity of central nervous system symptoms such as 6 withdrawal increased with dose and duration of exposure. Study quality and utility concerns (e.g., 7 inappropriate exposure durations, lack of data reporting, small number of animals per treatment 8 group) associated with these studies (Grant and Samson, 1981; Snell, 1980; Thurman et al., 9 1980; McComb and Goldstein, 1979a, b; Wood and Laverty, 1979), however, preclude an 10 understanding of potential neurotoxicity following tert-butanol exposure, and therefore, central 11 nervous system studies are not discussed further. 12 Exposure-response arrays of these effects on liver and urinary bladder are provided in 13 Figure B-6 and Figure B-7 for oral and inhalation studies, respectively.

14 Kidney effects 15 Absolute and relative kidney weight numerical data are presented in Table B-3.

16 Liver effects 17 Liver weight and body weight were demonstrated to be proportional and liver weight 18 normalized to body weight was concluded optimal for data analysis (Bailey et al., 2004); thus, only 19 relative liver weight is presented and considered in the determination of hazard. Although some 20 rodent studies observed liver effects (organ weight changes and histopathologic lesions), the effects 21 were not consistent across the database. Increases in relative liver weight with tert-butanol 22 exposure were observed, but the results pertaining to histopathologic changes were inconsistent 23 (Table B-4). The NTP (1995) oral subchronic and chronic studies did not observe treatment-related 24 effects on liver histopathology in either sex of F344 rats. In a 10-week study in Wistar rats, several 25 liver lesions (including necrosis) and increased liver glycogen were observed in male rats (no 26 females were included in the study) with the only dose used (Acharya et al., 1997; Acharya et al., 27 1995). The study provided no incidence or severity data. The dose used in this rat study was in the 28 range of the lower doses used in the NTP (1995) subchronic rat study. An increased incidence of 29 fatty liver was observed in the male mice of the highest dose group in the 2-year mouse bioassay, 30 but no histopathological changes were seen in the subchronic mouse study (NTP, 1995). No 31 treatment-related effects in liver histopathology were observed in rats or mice of the NTP (1997) 32 subchronic inhalation study.

33 Urinary bladder effects 34 Subchronic studies reported effects in the urinary bladder (Table B-6), although the chronic 35 studies indicated little progression in incidence with increased exposure. Transitional epithelial 36 hyperplasia of the urinary bladder was observed in male rats and male mice after 13 weeks of

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1 exposure at doses of 3,610 mg/kg- ,940 mg/kg-day (male mice). In rats, the 2 increase in transitional epithelial hyperplasia of the urinary bladder was not observed in the 2-year day (male rats) and ≥3 3 study. Male mice exposed at the high dose (2,070 mg/kg-day) for 2 years exhibited minimal 4 transitional epithelial hyperplasia of the urinary bladder. Neither female rats nor female mice 5 showed increased incidences of this lesion. Both sexes of mice demonstrated incidence of minimal 6 to mild inflammation in the urinary bladder after both subchronic and chronic exposures, with a 7 greater incidence in males compared to females.

8 B.3.1.2. Mechanistic Evidence 9 No mechanistic evidence is available for these effects.

10 B.3.1.3. Summary of Other Toxicity Data 11 Based on lack of consistency and lack of progression, the available evidence does not 12 support liver and urinary bladder effects, respectively, as potential human hazards of tert-butanol 13 exposure. 14

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1 Table B-3. Changes in kidney weight in animals following exposure to 2 tert-butanol

Reference and study design Results Kidney weight (percent change as compared to control) Lyondell Chemical Co. (2004) Males Sprague-Dawley rat; Dose Left absolute Left relative Right absolute Right relative 12/sex/treatment (mg/kg-d) weight weight weight weight Gavage 0, 64, 160, 400, or 1,000 mg/kg-d 0 0 0 0 0 Males: 9 weeks beginning 4 weeks prior to mating 64 +6 +8 +6 +8 Females: ≅ 10 weeks (4 weeks 160 +9 +14* +6 +11* prior to mating through PND21) 400 +12* +14* +14* +17* 1,000 +18* +28* +20* +31* Females Dose Left absolute Left relative Right absolute Right relative (mg/kg-d) weight weight weight weight 0 0 0 0 0 64 −1 −2 +2 0 160 0 0 +1 0 400 +3 +2 +4 +2 1,000 +4 0 +7 +2 NTP (1995) Males Females F344/N rat; 10/sex/treatment Dose Absolute Relative Dose Absolute Relative Drinking water 0, 2.5, 5, 10, 20, (mg/kg-d) weight weight (mg/kg-d) weight weight 40 mg/mL M: 0, 230, 490, 840, 1,520, 0 0 0 0 0 0 3,610a mg/kg-d F: 0, 290, 590, 850, 1,560, 230 +12* +19* 290 +19* +17* a 3,620 mg/kg-d 490 +17* +26* 590 +16* +15* 13 weeks 840 +16* +32* 850 +29* +28* 1,520 +26* +54* 1,560 +39* +40* 3,610 All dead All dead 3,620 +36* +81*

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Reference and study design Results NTP (1995) Males Females B6C3F1 mouse; 10/sex/treatment Dose Absolute Relative Dose Absolute Relative Drinking water (0, 2.5, 5, 10, 20, (mg/kg-d) weight weight (mg/kg-d) weight weight 40 mg/mL) M: 0, 350, 640, 1,590, 3,940, 0 0 0 0 0 0 8,210a mg/kg-d F: 0, 500, 820, 1,660, 6,430, 350 +1 +1 500 0 −3 a 11,620 mg/kg-d 640 +3 +2 820 −3 −1 13 weeks 1,590 +2 +8 1,660 +1 0 3,940 +6 +22* 6,430 +6 +15* 8,210 0 +48* 11,620 +12* +35* NTP (1995) Males Females F344/N rat; 60/sex/treatment Dose Absolute Relative Dose Absolute Relative (10/sex/treatment evaluated at (mg/kg-d) weight weight (mg/kg-d) weight weight 15 months) Drinking water (0, 1.25, 2.5, 5, or 0 0 0 0 0 0 10 mg/mL) M: 0, 90, 200, or 420a mg/kg-d 90 +4 +8 180 +8* +14* F: 0, 180, 330, or 650a mg/kg-d 200 +11 +15* 330 +18* +21* 2 years 420 +7 +20* 650 +22* +42* Only rats sacrificed at 15 months were evaluated for organ weights.

NTP (1997) Males Females F344/N rat; 10/sex/treatment Concentration Absolute Relative Absolute Relative Inhalation analytical (mg/m3) weight weight weight weight concentration: 0, 134, 272, 542, 1,080, or 2,101 ppm (0, 406, 824, 0 0 0 0 0 1,643, 3,273 or 6,368 mg/m3) (dynamic whole-body chamber) 406 +1 +1 −4 −1 6 hr/d, 5 d/wk 824 −2 −1 0 +1 13 weeks Generation method (Sonimist 1,643 +3 +2 +4 +4 Ultrasonic spray nozzle 3,273 +11* +8* +2 +2 nebulizer), analytical concentration and method were 6,368 +9.8* +9* +4 +9* reported

Right kidney weights measured

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Reference and study design Results NTP (1997) Males Females B6C3F1 mouse; 10/sex/treatment Concentration Absolute Relative Absolute Relative Inhalation analytical (mg/m3) weight weight weight weight concentration: 0, 134, 272, 542, 1,080, or 2,101 ppm (0, 406, 824, 0 0 0 0 0 1,643, 3,273 or 6,368 mg/m3) (dynamic whole-body chamber) 406 −6 −4 +1 −3 6 hr/d, 5 d/wk 824 −1 +3 +5 +9 13 weeks Generation method (Sonimist 1,643 +4 +3 +1 −2 Ultrasonic spray nozzle 3,273 −10 −3 0 +7 nebulizer), analytical concentration and method were 6,368 +3 +6 +3 +15* reported

Right kidney weights measured 1 a The high-dose group had an increase in mortality. 2 * Statistically significant p ≤ 0.05 as determined by the study authors. 3 Percentage change compared to control = (treated value – control value) ÷ control value × 100. 4 Conversions from drinking water concentrations to mg/kg-d performed by study authors. 5 Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3.

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1 Table B-4. Changes in liver weight in animals following exposure to 2 tert-butanol

Reference and study design Results Acharya et al. (1995) No significant treatment-related effects (results were only provided in a figure) Wistar rat; 5–6 males/treatment Drinking water (0 or 0.5%), 0 or 575 mg/kg­ d 10 weeks Lyondell Chemical Co. (2004) Percent change compared to control: Sprague-Dawley rat; 12/sex/treatment Gavage 0, 64, 160, 400, or 1,000 mg/kg-d Males Females Males: 9 weeks beginning 4 weeks prior to Dose Absolute Relative Dose Absolute Relative weight mating (mg/kg-d) weight weight (mg/kg-d) weight Females: 4 weeks prior to mating through PND21 0 0 0 0 0 0

64 −1 0 64 −4 −4 160 −3 +1 160 −7 −5 400 −2 −1 400 +2 +1 1,000 +8 +16* 1,000 +8 +3 NTP (1995) Percent change compared to control: F344/N rat; 10/sex/treatment Drinking water (0, 2.5, 5, 10, 20, or 40 Males Females mg/mL) Dose Absolute Relative Dose Absolute Relative M: 0, 230, 490, 840, 1,520, 3,610a mg/kg-d (mg/kg-d) weight weight (mg/kg-d) weight weight F: 0, 290, 590, 850, 1,560, 3,620a mg/kg-d 13 weeks 0 0 0 0 0 0 230 −2 +4 290 +11* +9* 490 +1 +8* 590 +10* +9* 840 +5 +20* 850 +12* +11* 1,520 +8 +31* 1,560 +15* +16* 3,610 All dead All dead 3,620 +9* +41* NTP (1995) Percent change compared to control: B6C3F1 mouse; 10/sex/treatment Drinking water (0, 2.5, 5, 10, 20, or 40 Males Females mg/mL) Dose Absolute Relative Dose Absolute Relative M: 0, 350, 640, 1,590, 3,940, (mg/kg-d) weight weight (mg/kg-d) weight weight 8,210a mg/kg-d F: 0, 500, 820, 1,660, 6,430, 0 0 0 0 0 0 a 11,620 mg/kg-d 350 +2 +3 500 −1 −4 13 weeks 640 −1 −2 820 −5 −3 1,590 −1 +5 1,660 −8 −9* 3,940 0 +14* 6,430 −2 +6 8,210 −16 +22* 11,620 −6 +13* NTP (1995) Percent change compared to control:

Males Females

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Reference and study design Results F344/N rat; 60/sex/treatment Dose Absolute Relative Dose Absolute Relative (10/sex/treatment evaluated at 15 months) (mg/kg-d) weight weight (mg/kg-d) weight weight Drinking water (0, 1.25, 2.5, 5 or 10 mg/mL) M: 0, 90, 200, or 420a mg/kg-d 0 0 0 0 0 0 a F: 0, 180, 330, or 650 mg/kg-d 90 +2 +7 180 −14* −8 2 years 200 +8 +11 330 −3 −1

420 +1 +14* 650 −6 +9*

Only animals sacrificed at 15 months were evaluated for organ weights. Organ weights were not measured in the 2-year mouse study NTP (1997) Percent change compared to control: F344/N rat; 10/sex/treatment Inhalation analytical concentration: 0, 134, Males Females 272, 542, 1,080, or 2,101 ppm (0, 406, 824, Concentration Absolute Relative Absolute Relative 1,643, 3,273 or 6,368 mg/m3) (dynamic (mg/m3) weight weight weight weight whole body chamber) 6 hr/d, 5 d/wk 0 0 0 0 0 13 weeks Generation method (Sonimist Ultrasonic 406 −8 −8 0 +3 spray nozzle nebulizer), analytical 824 −2 −1 0 0 concentration and method were reported 1,643 +1 −1 +3 +2

3,273 +10 +7 +9 +9*

6,368 +5 +5 +4 +8*

NTP (1997) Percent change compared to control: B6C3F1 mouse; 10/sex/treatment Inhalation analytical concentration: 0, 134, Males Females 272, 542, 1,080, or 2,101 ppm (0, 406, 824, Concentration Absolute Relative Absolute Relative 1,643, 3,273 or 6,368 mg/m3) (dynamic (mg/m3) weight weight weight weight whole body chamber) 6 hr/d, 5 d/wk 0 0 0 0 0 13 weeks Generation method (Sonimist Ultrasonic 406 −1 0 +1 −4 spray nozzle nebulizer), analytical 824 +4 +9 +1 +5 concentration and method were reported 1,643 +7 +5 +5 +1

3,273 −8 -2 +2 +9*

6,368 +5 +7 +8 +21* 1 aThe high-dose group had an increase in mortality. 2 * Statistically significant p ≤ 0.05 as determined by study authors. 3 Conversions from drinking water concentrations to mg/kg-d performed by study authors. 4 Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3. 5 Percentage change compared to control = (treated value – control value) ÷ control value × 100. 6

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1 Table B-5. Changes in liver histopathology in animals following exposure to 2 tert-butanol

Reference and study design Results Acharya et al. (1997) ↑ liver glycogen (~ 7 fold)* Acharya et al. (1995) Wistar rat; 5–6 males/treatment ↑incidence of centrilobular necrosis, vacuolation of hepatocytes, loss of Drinking water (0, 0.5%), 0, 575 mg/kg-d hepatocyte architecture, peripheral proliferation, and lymphocyte 10 weeks infiltration (incidences and results of statistical tests not reported)

NTP (1995) No treatment-related effects observed. F344/N rat; 10/sex/treatment Drinking water (0, 2.5, 5, 10, 20, or 40 mg/mL) M: 0, 230, 490, 840, 1,520, 3,610a mg/kg-d F: 0, 290, 590, 850, 1,560, 3,620a mg/kg-d 13 weeks NTP (1995) No treatment-related effects observed. B6C3F1 mouse; 10/sex/treatment Drinking water (0, 2.5, 5, 10, 20, 40 mg/mL) M: 0, 350, 640, 1,590, 3,940, 8,210a mg/kg-d F: 0, 500, 820, 1,660, 6,430, 11,620a mg/kg-d 13 weeks NTP (1995) No treatment-related effects observed. F344/N rat; 60/sex/treatment (10/sex/treatment evaluated at 15 months) Drinking water (0, 1.25, 2.5, 5, 10 mg/mL) M: 0, 90, 200, or 420a mg/kg-d F: 0, 180, 330, or 650a mg/kg-d 2 years NTP (1995) Males Females B6C3F1 mouse; 60/sex/treatment Dose Incidence of fatty Dose Incidence of fatty Drinking water (0, 5, 10, 20 mg/mL) (mg/kg-d) change (mg/kg-d) change M: 0, 540, 1,040, or 2,070a mg/kg-d F: 0, 510, 1,020, or 2,110 mg/kg-d 0 12/59 0 11/60 2 years 540 5/60 510 8/60 1,040 8/59 1,020 8/60 2,070 29/59* 2,110 6/60

NTP (1997) No treatment-related effects observed in the high dose group (only F344/N rat; 10/sex/treatment treatment group with liver endpoints evaluated). Inhalation analytical concentration: 0, 134, 272, 542, 1,080, or 2,101 ppm (0, 406, 824, 1,643, 3,273 or 6,368 mg/m3) (dynamic whole body chamber) 6 hr/d, 5 d/wk 13 weeks Generation method (Sonimist Ultrasonic spray nozzle nebulizer), analytical concentration and method were reported

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Reference and study design Results NTP (1997) Authors stated that there were no treatment-related microscopic changes, B6C3F1 mouse; 10/sex/treatment but data were not provided. Inhalation analytical concentration: 0, 134, 272, 542, 1,080, or 2,101 ppm (0, 406, 824, 1,643, 3,273 or 6,368 mg/m3) (dynamic whole body chamber) 6 hr/d, 5 d/wk 13 weeks Generation method (Sonimist Ultrasonic spray nozzle nebulizer), analytical concentration and method were reported 1 aThe high-dose group had an increase in mortality. 2 * Statistically significant p ≤ 0.05 as determined by study authors. 3 Conversions from drinking water concentrations to mg/kg-d performed by study authors. 4 Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3.

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1 Table B-6. Changes in urinary bladder histopathology in animals following 2 oral exposure to tert-butanol

Reference and study design Results NTP (1995) Incidence (severity): F344/N rat; 10/sex/treatment Males Females Drinking water (0, 2.5, 5, 10, 20, 40 mg/mL) Transitional M: 0, 230, 490, 840, 1,520, 3,610a epithelial Dose (mg/kg- Transitional epithelial mg/kg-d Dose (mg/kg-d) hyperplasia d) hyperplasia F: 0, 290, 590, 850, 1,560, 3,620a 0 0/10 0 0/10 mg/kg-d 13 weeks 230 not evaluated 290 not evaluated 490 not evaluated 590 not evaluated 840 0/10 850 not evaluated 1,520 1/10 (3.0) 1,560 0/10 3,610 7/10* (2.9) 3,620 3/10 (2.0) Severity: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked NTP (1995) Incidence (severity): B6C3F mouse; 10/sex/treatment 1 Males Females Drinking water (0, 2.5, 5, 10, 20, 40 mg/mL) Transitional Transitional M: 0, 350, 640, 1,590, 3,940, Dose epithelial Inflam- Dose epithelial Inflam­ 8,210a mg/kg-d (mg/kg-d) hyperplasia mation (mg/kg-d) hyperplasia mation F: 0, 500, 820, 1,660, 6,430, 0 0/10 0/10 0 0/10 0/10 11,620a mg/kg-d 13 weeks 350 not evaluated 500 0/10 0/10 640 not evaluated 820 not evaluated 1,590 0/10 0/10 1,660 not evaluated 3,940 6/10* (1.3) 6/10* (1.3) 6,430 0/10 0/10 8,210 10/10* (2.0) 10/10* 11,620 3/9 (2.0) 6/9* (1.2) (2.3) Severity: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked NTP (1995) No treatment-related effects observed F344/N rat; 60/sex/treatment (10/sex/treatment evaluated at 15 months) Drinking water (0, 1.25, 2.5, 5, or 10 mg/mL) M: 0, 90, 200, 420a mg/kg-d F: 0, 180, 330, 650a mg/kg-d 2 years

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Reference and study design Results NTP (1995) Incidence (severity): B6C3F mouse; 60/sex/treatment 1 Males Females Drinking water (0, 5, 10, or 20 mg/mL) Transitional Transitional M: 0, 540, 1,040, 2,070a mg/kg-d Dose epithelial Inflam­ Dose epithelial Inflam­ F: 0, 510, 1,020, 2,110 mg/kg-d (mg/kg-d) hyperplasia mation (mg/kg-d) hyperplasia mation 2 years 0 1/59 (2.0) 0/59 0 0/59 0/59 540 3/59 (1.7) 3/59 (1.7) 510 0/60 0/60 1,040 1/58 (1.0) 1/58 (1.0) 1,020 0/59 0/59 2,070 17/59* 37/59* (2.0) 2,110 3/57 (1.0) 4/57* (1.8) (2.0) Severity: 1 = minimal, 2 = mild, 3 = moderate, 4 = marked 1 aThe high-dose group had an increase in mortality. 2 * Statistically significant p ≤ 0.05 as determined by study authors. 3 Conversions from drinking water concentrations to mg/kg-d performed by study authors.

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1 2 Sources: (A) (Acharya et al. (1997); Acharya et al. (1995)); (B) Lyondell Chemical Co. (2004); (C) NTP (1995)

3 Figure B-6. Exposure-response array of other effects following oral exposure 4 to tert-butanol.

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1 2 Source: (A) NTP (1997)

3 Figure B-7. Exposure-response array of other effects following inhalation 4 exposure to tert-butanol.

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1 Genotoxicity 2 The genotoxic potential of tert-butanol has been studied using a variety of genotoxicity 3 assays, including bacterial reverse mutation assays, gene mutation assays, chromosomal 4 aberrations, sister chromatid exchanges, micronucleus formation, and deoxyribonucleic acid (DNA) 5 strand breaks and adducts. The available genotoxicity data for tert-butanol are discussed below, 6 and the data summary is provided in Table B-7.

7 B.3.2.1. Bacterial Systems 8 The mutagenic potential of tert-butanol has been tested by Zeiger et al. (1987) using 9 different Salmonella typhimurium strains both in the presence and absence of S9 metabolic 10 activation. The preincubation assay protocol was followed. Salmonella strains TA98, TA100, 11 TA1535, TA1537, and TA1538 were exposed to five concentrations (100, 333, 1,000, 3,333, or 12 10,000 µg/plate) and tested in triplicate. No mutations were observed in any of the strains tested, 13 in either the presence or absence of S9 metabolic activation. 14 Conflicting results have been obtained with tert-butanol-induced mutagenicity in strain 15 Salmonella strain TA102, a strain that is sensitive to damage at A-T sites inducible by oxidants and 16 other mutagens and is excision-repair proficient. In a study by Williams-Hill et al. (1999), 17 tert-butanol induced an increase in the number of revertants in the first three concentrations with 18 S9 activation in a dose-response manner. The number of revertants decreased in the last two 19 concentrations. No discussion was provided on why the revertants decreased at higher 20 concentrations. The results of this study indicated that test strain TA102 might be a more sensitive 21 strain for monitoring tert-butanol levels (Williams-Hill et al., 1999). In another study by Mcgregor 22 et al. (2005), however, experiments were conducted on TA102 in two different laboratories using 23 similar protocols. tert-Butanol was dissolved in dimethyl sulfoxide (DMSO) or distilled water and 24 tested in both the presence and absence of S9 metabolic activation. No statistically significant 25 increase in mutants was observed in either solvent medium. In one experiment where tert-butanol 26 was dissolved in water, a significant, dose-related increase in the number of revertants occurred, 27 reaching almost twice the control value at a concentration of 2,250 µg/plate. Of note is that DMSO is 28 known to be a free radical scavenger, and its presence at high concentrations might mask a 29 mutagenic response caused by oxidative damage. 30 Mutagenicity of tert-butanol has been studied in other systems including Neurospora crassa 31 and Saccharomyces cerevisiae. strain Neurospora crassa at the ad-3A locus (allele 38701) was 32 used to test the mutagenic activity of tert-butanol at a concentration of 1.75 mol/L for 30 minutes. 33 Btert- utanol did not induce reverse mutations in the tested strain at the exposed concentration 34 (Dickey et al., 1949). tert-butanol without exogenous metabolic activation, however, significantly 35 increased the frequency of petite mutations ( ) in 36 Saccharomyces cerevisiae laboratory strains K5-A5, MMY1, D517-4B, and DS8 (Jimenez et al., 1988). the mitochondrial DNA deletion rho− 37 This effect on mitochondrial DNA, also observed with ethanol and other solvents, was attributed by 38 the study authors to the alteration in the lipid composition of mitochondrial membranes, and

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1 mitochondrial DNA’s close association could be affected by membrane composition (Jimenez et al., 2 1988 ).

3 B.3.2.2. In Vitro Mammalian Studies 4 To understand the role of tert-butanol-induced genotoxicity in mammalian systems, in vitro 5 studies have been conducted in different test systems and assays. tert-Butanol was tested to 6 evaluate its ability to induce forward mutations at the thymidine kinase locus (tk) in the L5178Y 7 tk+/- mouse lymphoma cells using forward mutation assay. Experiments were conducted in both 8 the presence and absence of S9 metabolic activation. The mutant frequency was calculated using 9 the ratio of mutant clones per plate/total clones per plate × 200. tert-Butanol did not reliably 10 11 without metabolic activation, although one experiment without addition of S9 yielded a small increase the frequency of forward mutations in L5178Y tk+/− mouse lymphoma cells with or 12 increase in mutant fraction at the highest tested concentration (5,000 µg/mL) (McGregor et al., 13 .1988 ) 14 To further determine potential DNA or chromosomal damage induced by tert-butanol in in 15 vitro systems, NTP (1995) studied sister chromatid exchanges and chromosomal aberrations. 16 Chinese hamster ovary (CHO) cells were exposed to tert-butanol in both the presence and absence 17 of S9 activation at concentrations of 160–5,000 µg/mL for 26 hours. tert-Butanol did not induce 18 sister chromatid exchanges in any concentration tested, although in one experiment, percent 19 relative change of sister chromatid exchanges per chromosome scored slightly increased. The same 20 authors also studied the effect of tert-butanol on chromosomal aberration formation. CHO cells 21 were exposed to four concentrations (160, 500, 1,600, or 5,000 µg/mL) of tert-butanol in both the 22 presence and absence of S9. No significant increase in chromosomal aberration was observed in 23 any concentration tested. Of note is that, due to severe toxicity at the highest concentration 24 (5 ,000 µg/mL), only 13 metaphase cells were scored instead of 100 in the chromosomal aberration 25 assay. 26 Sgambato et al. (2009) examined the effects of tert-butanol on DNA damage using a normal 27 diploid rat fibroblast cell line. Cells were treated with 0- to 100-mM tert-butanol for 48 hours to

28 determine the half-maximal inhibitory concentration (IC50; 0.44 ± 0.2 mM). The 48-hour IC50 29 concentration then was used to determine DNA content, cell number, and phases of the cell cycle 30 after 24 and 48 hours of exposure. Total protein and DNA oxidative damage also were measured. A 31 comet assay was used to evaluate DNA fragmentation at time 0 and after 30 minutes, 4 hours, or 12

32 hours of exposure to the IC50 concentration. tert-Butanol inhibited cell division in a dose-dependent

33 manner as measured by the number of cells after 24 and 48 hours of exposure at IC50

34 concentrations, and with concentrations at 1/10th the IC50. Cell death did not increase, suggesting a 35 reduction in cell number due to reduced replication rather than to cytotoxicity. tert-Butanol caused

36 an accumulation in the G0/G1 phase of replication, related to different effects on the expression of 37 the cyclin D1, p27Kip1, and p53 genes. An initial increase in DNA damage as measured by nuclear 38 fragmentation was observed at 30 minutes. The DNA damage declined drastically after 4 hours and

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1 disappeared almost entirely after 12 hours of exposure to tert-butanol. This reduction in the extent 2 of DNA fragmentation after the initial increase is likely the result of an efficient DNA repair 3 mechanism activated by cells following DNA damage induced by tert-butanol. 4 DNA damage caused by tert-butanol was determined by single-cell gel electrophoresis 5 (comet assay) in human promyelocytic leukemia (HL-60) cells. The cells were exposed to 6 concentrations ranging from 1 to 30 mmol/L for 1 hour, and 100 cells were evaluated for DNA 7 fragmentation. A dose-dependent increase in DNA damage was observed between 1 and 8 30 mmol/L. No cytotoxicity was observed at the concentrations tested (Tang et al., 1997).

9 B.3.2.3. In Vivo Mammalian Studies 10 Few in vivo studies are available to understand the role of tert-butanol on genotoxicity. The 11 National Toxicology Program studied the effect of tert-butanol in a 13-week toxicity study (NTP, 12 1995 ). Peripheral blood samples were obtained from male and female B6CF1 mice exposed to tert­ 13 butanol in drinking water at doses of 3,000–40,000 ppm. Slides were prepared to determine the 14 frequency of micronuclei in 10,000 normochromatic erythrocytes. In addition, the percentage of 15 polychromatic erythrocytes among the total erythrocyte population was determined. No increase in 16 micronucleus formation in peripheral blood lymphocytes was observed either in male or female

17 B6C3F1 mice exposed for 13 weeks to tert-butanol in drinking water at concentrations as high as 18 40,000 ppm (2,110 mg/kg-day) (NTP, 1995). 19 Male Kumming mice (8 per treatment) were administered 0, 0.099, 0.99, 10, 101, or 20 997 µg/kg BW 14C-tert-butanol in saline via gavage with specific activity ranging from 1.60 to 21 0.00978 mCi/mol (Yuan et al., 2007). Animals were sacrificed 6 hours after exposure, and liver, 22 kidney, and lung were collected. Tissues were prepared for DNA isolation with samples from the 23 same organs from every two mice combined. DNA adducts were measured using accelerated mass 24 spectrometry. The results of this study showed a dose-response increase in DNA adducts in all 25 three organs measured, although the methodology used to detect DNA adducts is considered 26 sensitiv e but could be nonspecific. The authors stated that tert-butanol was found, for the first time, 27 to form DNA adducts in mouse liver, lung, and kidney. Because this is a single and first-time study, 28 further validation of this study will provide certainty in understanding the mechanism of tert­ 29 buta nol-induced DNA adducts.

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1 Table B-7. Summary of genotoxicity (both in vitro and in vivo) studies of tert­ 2 butanol

Test system Dose/Conc. Resultsa Comments Reference Bacterial Systems -S9 +S9 Reverse Mutation Assay 100, 333, 1,000, - - Preincubation procedure was Zeiger et al. Salmonella typhimurium 3,333, 10,000 followed. This study was part of (1987);NTP (TA98, TA100, TA1535, µg/plate the NTP 1995 testing results. (1995) TA1537, TA1538) Reverse Mutation Assay 1,000–4,000 ND + Only tested with S9 activation Williams-Hill et Salmonella typhimurium µg/plate al. (1999) (TA102) Reverse Mutation Assay 5, 15, 50, 100, 150, - - Experiments conducted in two Mcgregor et al. Salmonella typhimurium 200, 500, 1,000, different laboratories, two (2005) (TA98, TA100, TA102, 1,500, 2,500, 5,000 vehicles – distilled water and TA1535, TA1537) µg/plate DMSO were used, different concentrations were used in experiments from different laboratories Reverse mutation 1.75mol/L - - Eighty four percent cell death Dickey et al. Neurospora crassa, ad-3A was observed; note it is a 1949 (1949) locus (allele 38701) study Mitochondrial mutation 4.0% (vol/vol) +b ND Mitochondrial mutations, Jimenez et al. Saccharomyces cerevisiae membrane solvent (1988) (K5-5A, MMY1, D517-4B, and DS8) In vitro Systems Gene Mutation Assay, 625, 1,000, 1,250, - - Cultures were exposed for 4 h, McGregor et al. Mouse lymphoma cells 2,000, 3,000, then cultured for 2 days before (1988);NTP L5178Y TK+/– 4,000, 5,000 μg/mL plating in soft agar with or (1995) without trifluorothymidine, 3 μg/mL; this study was part of the NTP 1995 testing results Sister-chromatid exchange, 160, 500, 1,600, This study was part of the NTP Galloway, Chinese Hamster Ovary cells 2,000, 3,000, - - 1995 testing results 1987; NTP 4,000, 5,000 µg/mL (1995) Chromosomal Aberrations, 160, 500, 1,600, - - This study was part of the NTP Galloway, Chinese Hamster Ovary cells 2,000, 3,000, 1995 testing results 1987 NTP 4,000, 5,000 µg/mL (1995)

c DNA damage (comet assay), 0.44 mmol/L (IC50 ) + ND Exposure duration – 30 min, Sgambato et al. Rat fibroblasts 4 h, 12 h; this study provides (2009) other information on effect of cell cycle control genes and mechanism of action for TBA

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Test system Dose/Conc. Resultsa Comments Reference DNA damage, (comet 1, 5, 10, 30 mmol/L + ND Exposure duration – 1h Tang et al. assay), HL-60 leukemia cells (1997) In vivo Animal Studies Micronucleus formation, 3,000, 5,000, - 13-week, subchronic, drinking NTP (1995) B6C3F1 mouse peripheral 10,000, 20,000, water study blood cells 40,000 ppm DNA adducts, male 0.1–1,000 µg/kg Gavage, 6-h exposure, DNA Yuan et al. Kunming mouse liver, body weight + adduct determined by (2007) kidney and lung cells accelerator mass spectrometry 1 a+ = positive; − = negative; ND = not determined. 2 bEffect is predicted to be due to mitochondrial membrane composition. 3 cDNA damage was completely reversed with increased exposure time. 4 Summary 5 tert-Butanol has been tested for its genotoxic potential using a variety of genotoxicity 6 assays. Bacterial assays that detect reverse mutations have been thought to predict carcinogenicity 7 with accuracy up to 80%. tert-Butanol did not induce mutations in most bacterial strains; however, 8 when tested in TA102, a strain that is sensitive to damage at A-T sites inducible by oxidants, an 9 increase in mutants was observed at low concentrations, although conflicting results were reported 10 in another study. Furthermore, the solvent (e.g., distilled water or DMSO) used in the genotoxicity 11 assay could influence results. In one experiment where tert-butanol was dissolved in distilled 12 water, a significant, dose-related increase in the number of mutants was observed, with the 13 maximum value reaching almost twice the control value. DMSO is known to be a radical scavenger, 14 and its presence in high concentrations might mask a mutagenic response modulated by oxidative 15 damage. Other species such as Neurospora crassa did not produce reverse mutations due to 16 exposure to tert-butanol. 17 tert-Butanol was tested in several human and animal in vitro mammalian systems for 18 genotoxicity (gene mutation, sister chromatid exchanges, chromosomal aberrations, and DNA 19 damage). No increase in gene mutations was observed in mouse lymphoma cells (L5178Y TK+/–). 20 These specific locus mutations in mammalian cells are used to demonstrate and quantify genetic 21 damage, thereby confirming or extending the data obtained in the more widely used bacterial cell 22 tests. Sister chromatid exchanges or chromosomal aberrations were not observed in CHO cells in 23 response to tert-butanol treatment. DNA damage was detected using comet assay, however, in both 24 rat fibroblasts and HL-60 leukemia cells, with either an increase in DNA fragmentation at the 25 beginning of the exposure or dose-dependent increase in DNA damage observed. An initial increase 26 in DNA damage was observed at 30 minutes that declined drastically following 4 hours of exposure 27 and disappeared almost entirely after 12 hours of exposure to tert-butanol. This reduction in the 28 extent of DNA fragmentation after an initial increase is likely the result of an efficient DNA repair 29 mechanism activated by cells following DNA damage induced by tert-butanol. A dose-dependent

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1 increase in DNA damage was observed in human cells tested; however, because the exposure 2 occurred for only 1 hour in this study, whether DNA-repair mechanisms would occur after a longer 3 period of observation cannot be discerned. 4 Limited in vivo animal studies have been conducted on DNA adduct and micronucleus 5 formation. A dose-response increase in DNA adducts was observed in mouse liver, kidney, and lung 6 cells . The authors used accelerated mass spectrometry to detect DNA adducts, but the identity of 7 these adducts was not determined. The method uses 14C-labeled chemical for dosing, isolated DNA 8 is oxidized to and reduced to filamentous graphite, and the ratios of 14C/12C are 9 measured. The ratio then is converted to DNA adducts based on nucleotide content of the DNA. 10 Confirmation of these data will further the understanding of the mechanism of tert-butanol-induced 11 DNA adducts. No increase in micronucleus formation was observed in mouse peripheral blood cells 12 in a 13-week drinking water study conducted by the National Toxicology Program. 13 Overall, a limited database is available for understanding the role of tert-butanol-induced 14 genotoxicity for mode of action and carcinogenicity. The database is limited in terms of either the 15 array of genotoxicity tests conducted or the number of studies within the same type of test. In 16 addition, the results are either conflicting or inconsistent. The test strains, solvents, or control for 17 volatility used in certain studies are variable and could influence results. Furthermore, in some 18 studies, the specificity of the methodology used has been challenged. Given the inconsistencies and 19 limitations of the database in terms of the methodology used, number of studies in the overall 20 database, coverage of studies across the genotoxicity battery, and the quality of the studies, the 21 weight of evidence analysis is inconclusive. The available data do not inform a definitive conclusion 22 on the genotoxicty of tert-butanol and thus the potential genotoxic effects of tert-butanol cannot be 23 discounted.

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1 APPENDIX C. DOSE-RESPONSE MODELING FOR 2 THE DERIVATION OF REFERENCE VALUES FOR 3 EFFECTS OTHER THAN CANCER AND THE 4 DERIVATION OF CANCER RISK ESTIMATES

5 This appendix provides technical detail on dose-response evaluation and determination of 6 points of departure (PODs) for relevant endpoints. The endpoints were modeled using EPA’s 7 Benchmark Dose Software (BMDS), version 2.1.2. The preambles for the cancer and noncancer 8 parts below describe the common practices used in evaluating the model fit and selecting the 9 appropriate model for determining the POD as outlined in the Benchmark Dose Technical Guidance 10 Document (U.S. EPA, 2000). In some cases, using alternative methods based on statistical judgment 11 might be appropriate; exceptions are noted as necessary in the summary of the modeling results.

12 Noncancer Endpoints 13 C.1.1.1. Data Sets 14 Data sets selected for dose-response modeling are provided in Table C-1. In all cases, 15 administered exposure was used in modeling the response data.

16 C.1.1.2. Model Fit 17 All models were fit to the data using the maximum likelihood method. The following 18 procedures were used, depending on whether data were dichotomous or continuous:

19 • For dichotomous models, the following parameter restrictions were applied: for log-logistic 20 model 21 Each model was tested for goodness-of-fit using a chi­ , restrict slope ≥1; for gamma and Weibull models, restrict power ≥1; for multistage 22 square goodness-of- 2 p-value < 0.10 indicates lack of fit). Other factors also were models, restrict beta values ≥0. 23 used to assess model fit, such as scaled residuals, visual fit, and adequacy of fit in the low­ fit test (χ 24 dose region and near the benchmark response (BMR).

25 • For continuous models, the following parameter restrictions were applied: for polynomial 26 27 Model fit was assessed by a series of tests. For each model, first the homogeneity of the models, restrict beta values ≥0; for Hill, power, and exponential models, restrict power ≥1. 28 variances was tested using a likelihood ratio test (BMDS Test 2). If Test 2 was not rejected 29 2 p- e model was fit to the data assuming constant variance. If Test 2 was 30 2 p-value < 0.10), the variance was modeled as a power function of the mean, and (χ value ≥ 0.10), th 31 the variance model was tested for adequacy of fit using a likelihood ratio test (BMDS rejected (χ 32 Test 3). For fitting models using either constant variance or modeled variance, models for

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1 the mean response were tested for adequacy of fit using a likelihood ratio test (BMDS Test 2 2 p-value < 0.10 indicating inadequate fit). Other factors also were used to assess 3 the model fit, such as scaled residuals, visual fit, and adequacy of fit in the low-dose region 4, with χ 4 and near the BMR.

5 C.1.1.3. Model Selection 6 For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as 7 estimated by the profile likelihood method) and the Akaike’s information criterion (AIC) value were 8 used to select a best-fit model from among the models exhibiting adequate fit. If the BMDL 9 estimates were “sufficiently close,” that is, differed by no more than three-fold, the model selected 10 was the one that yielded the lowest AIC value. If the BMDL estimates were not sufficiently close, the 11 lowest BMDL was selected as the POD.

12 Table C-1. Noncancer endpoints selected for dose-response modeling for 13 ter -butanol

Species/ Endpoint/Study Sex Doses and effect data Kidney transitional Dose (mg/kg-d) 0 90 200 420 epithelial hyperplasia Rat (F344)/Male NTP (1995) Incidence/Total 25/50 32/50 36/50 40/50 Kidney transitional Dose (mg/kg-d) 0 180 330 650 Rat epithelial hyperplasia (F344)/Female NTP (1995) Incidence/Total 0/50 0/50 3/50 17/50

Increased absolute Dose (mg/kg-d) 0 90 200 420 kidney weight Rat (F344)/Male 1.78 ± 0.18 1.85 ± 0.17 1.99 ± 0.18 1.9 ± 0.23 Mean ± SD (n) NTP (1995) (10) (10) (10) (10)

Increased absolute Dose (mg/kg-d) 0 180 330 650 Rat kidney weight 1.07 ± 0.09 1.16 ± 0.10 1.27 ± 0.08 1.31 ± 0.09 (F344)/Female Mean ± SD (n) NTP (1995) (10) (10) (10) (10)

Kidney inflammation Rat Dose (mg/kg-d) 0 180 330 650 NTP (1995) (F344)/Female Incidence/Total 2/50 3/50 13/50 17/50 Increased absolute Rat (F344)/Male Concentration 0 406 825 1,643 3,274 6,369 kidney weight (mg/m3) NTP (1997) 1.21 ± 1.21 ± 1.18 ± 1.25 ± 1.34 ± 1.32 ± Mean ± SD (n) 0.082 0.096 0.079 0.111 0.054 0.089 (10) (9) (10) (10) (10) (10) Increased absolute Rat Concentration 0 406 825 1,643 3,274 6,369 kidney weight (F344)/Female (mg/m3)

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Species/ Endpoint/Study Sex Doses and effect data NTP (1997) 0.817 ± 0.782 ± 0.821 ± 0.853 ± 0.831 ± 0.849 ± Mean ± SD (n) 0.136 0.063 0.061 0.045 0.054 0.038 (10) (10) (10) (10) (10) (10)

1 C.1.1.4. Modeling Results 2 Below are tables summarizing the modeling results for the noncancer endpoints modeled.

3 Table C-2. Summary of BMD modeling results for kidney transitional epithelial 4 hyperplasia in male F344 rats exposed to tert-butanol in drinking water for 2 5 years (NTP, 1995); BMR = 10% extra risk

Goodness of fit BMD10 BMDL10 Modela p-value AIC (mg/kg-d) (mg/kg-d) Basis for model selection Log-logistic model selected as best- Log-logistic 0.976 248.0 30 16 fitting model based on lowest AIC with all BMDL values sufficiently Gamma 0.784 248.5 46 29 close (BMDLs differed by slightly more than 3-fold). Logistic 0.661 248.8 58 41

Log-probit 0.539 249.2 84 53

Multistage, 3° 0.784 248.5 46 29

Probit 0.633 248.9 60 43

Weibull 0.784 248.5 46 29

Dichotomous-Hill 0.968 250.0 25 15 6 a Scaled residuals for selected model for doses 0, 90, 200, and 420 mg/kg-d were –0.076, 0.147, 0.046, and –0.137, 7 respectively.

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Log-Logistic Model with 0.95 Confidence Level

Log-Logistic 0.9

0.8

0.7

0.6

Fraction Affected

0.5

0.4

BMDL BMD 0 50 100 150 200 250 300 350 400 dose 1 17:16 05/13 2011 2 Figure C-1. Plot of incidence by dose, with fitted curve for LogLogistic model 3 for kidney transitional epithelial hyperplasia in male F344 rats exposed to 4 tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; 5 dose shown in mg/kg-d 6

7 ======8 Logistic Model. (Version: 2.13; Date: 10/28/2009) 9 Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\17 NTP 1995b_Kidney 10 transitional epithelial hyperplasia, male rats_LogLogistic_10.(d) 11 Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\17 NTP 12 1995b_Kidney transitional epithelial hyperplasia, male rats_LogLogistic_10.plt 13 Fri May 13 17:16:25 2011 14 ======15 16 [notes] 17 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 18 19 The form of the probability function is: 20 21 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))] 22 23 24 Dependent variable = Incidence 25 Independent variable = Dose 26 Slope parameter is restricted as slope >= 1 27 28 Total number of observations = 4 29 Total number of records with missing values = 0 30 Maximum number of iterations = 250 31 Relative Function Convergence has been set to: 1e-008 32 Parameter Convergence has been set to: 1e-008 33 34 35 36 User has chosen the log transformed model 37 38 39 Default Initial Parameter Values 40 background = 0.5 41 intercept = -5.54788

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1 slope = 1 2 3 4 Asymptotic Correlation Matrix of Parameter Estimates 5 6 ( *** The model parameter(s) -slope 7 have been estimated at a boundary point, or have been specified by the user, 8 and do not appear in the correlation matrix ) 9 10 background intercept 11 12 background 1 -0.71 13 14 intercept -0.71 1 15 16 17 18 Parameter Estimates 19 20 95.0% Wald Confidence Interval 21 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 22 background 0.505366 * * * 23 intercept -5.58826 * * * 24 slope 1 * * * 25 26 * - Indicates that this value is not calculated. 27 28 29 30 Analysis of Deviance Table 31 32 Model Log(likelihood) # Param's Deviance Test d.f. P-value 33 Full model -121.996 4 34 Fitted model -122.02 2 0.048148 2 0.9762 35 Reduced model -127.533 1 11.0732 3 0.01134 36 37 AIC: 248.04 38 39 40 Goodness of Fit 41 Scaled 42 Dose Est._Prob. Expected Observed Size Residual 43 ------44 0.0000 0.5054 25.268 25.000 50 -0.076 45 90.0000 0.6300 31.498 32.000 50 0.147 46 200.0000 0.7171 35.854 36.000 50 0.046 47 420.0000 0.8076 40.382 40.000 50 -0.137 48 49 Chi^2 = 0.05 d.f. = 2 P-value = 0.9762 50 51 52 Benchmark Dose Computation 53 54 Specified effect = 0.1 55 56 Risk Type = Extra risk 57 58 Confidence level = 0.95 59 60 BMD = 29.6967 61 62 BMDL = 15.6252 63

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1 Table C-3. Summary of BMD modeling results for kidney transitional epithelial 2 hyperplasia in female F344 rats exposed to tert-butanol in drinking water for 3 2 years (NTP, 1995); BMR = 10% extra risk

Goodness of fit

BMD10 BMDL10 Modela p-value AIC (mg/kg-d) (mg/kg-d) Basis for model selection

Gamma 0.83 91.41 409 334 Multistage 3rd-order model selected as best-fitting model Logistic 0.50 92.81 461 393 based on lowest AIC with all BMDL values sufficiently close (BMDLs LogLogistic 0.79 91.57 414 333 differed by less than 3-fold). LogProbit 0.89 91.19 400 327 Multistage 3° 0.92 89.73 412 339 Probit 0.62 92.20 439 372 Weibull 0.76 91.67 421 337 Dichotomous-Hill N/A b 117.89 Error c Error c aScaled residuals for selected model for doses 0, 180, 330, and 650 mg/m3 were 0.0, –0.664, 0.230, and 0.016, respectively. bNo available degrees of freedom to estimate a p-value. cBMD and BMDL computation failed for the Dichotomous-Hill model.

Multistage Model with 0.95 Confidence Level

Multistage 0.5

0.4

0.3

0.2 Fraction Affected

0.1

0 BMDL BMD 0 100 200 300 400 500 600 dose 4 17:18 05/13 2011 5 Figure C-2. Plot of incidence by dose, with fitted curve for Multistage 3° model 6 for kidney transitional epithelial hyperplasia in female F344 rats exposed to 7 tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; 8 dose shown in mg/kg-d

9 ======10 Multistage Model. (Version: 3.2; Date: 05/26/2010)

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1 Input Data File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\20 NTP 2 1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.(d) 3 Gnuplot Plotting File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\20 NTP 4 1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.plt 5 Mon May 09 18:31:33 2011 6 ======7 8 [notes] 9 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 10 11 The form of the probability function is: 12 13 P[response] = background + (1-background)*[1-EXP( 14 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 15 16 The parameter betas are restricted to be positive 17 18 19 Dependent variable = Incidence 20 Independent variable = Dose 21 22 Total number of observations = 4 23 Total number of records with missing values = 0 24 Total number of parameters in model = 4 25 Total number of specified parameters = 0 26 Degree of polynomial = 3 27 28 29 Maximum number of iterations = 250 30 Relative Function Convergence has been set to: 1e-008 31 Parameter Convergence has been set to: 1e-008 32 33 34 35 Default Initial Parameter Values 36 Background = 0 37 Beta(1) = 0 38 Beta(2) = 1.51408e-007 39 Beta(3) = 1.29813e-009 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 ( *** The model parameter(s) -Background -Beta(1) -Beta(2) 45 have been estimated at a boundary point, or have been specified by the user, 46 and do not appear in the correlation matrix ) 47 48 Beta(3) 49 50 Beta(3) 1 51 52 53 54 Parameter Estimates 55 56 95.0% Wald Confidence Interval 57 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 58 Background 0 * * * 59 Beta(1) 0 * * * 60 Beta(2) 0 * * * 61 Beta(3) 1.50711e-009 * * * 62 63 * - Indicates that this value is not calculated. 64 65 66 67 Analysis of Deviance Table 68 69 Model Log(likelihood) # Param's Deviance Test d.f. P-value 70 Full model -43.4002 4

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1 Fitted model -43.8652 1 0.9301 3 0.8182 2 Reduced model -65.0166 1 43.2329 3 <.0001 3 4 AIC: 89.7304 5 6 7 Goodness of Fit 8 Scaled 9 Dose Est._Prob. Expected Observed Size Residual 10 ------11 0.0000 0.0000 0.000 0.000 50 0.000 12 180.0000 0.0088 0.438 0.000 50 -0.664 13 330.0000 0.0527 2.636 3.000 50 0.230 14 650.0000 0.3389 16.946 17.000 50 0.016 15 16 Chi^2 = 0.49 d.f. = 3 P-value = 0.9200 17 18 19 Benchmark Dose Computation 20 21 Specified effect = 0.1 22 23 Risk Type = Extra risk 24 25 Confidence level = 0.95 26 27 BMD = 411.95 28 29 BMDL = 338.618 30 31 BMDU = 469.73 32 33 Taken together, (338.618, 469.73 ) is a 90 % two-sided confidence 34 interval for the BMD 35 36

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1 Table C-4. Summary of BMD modeling results for absolute kidney weight in 2 male F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 3 1995 ); BMR = 10% rel. dev. from control mean

Goodness of fit BMD10RD BMDL10RD Modela p-value AIC (mg/kg-d) (mg/kg-d) Basis for model selection Exponential (M2)b 0.123 −86.757 661 307 Of the models that provided an adequate fit and a valid BMDL Exponential (M3)c 0.123 −86.757 661 307 estimate, the linear model was Exponential (M4) 0.167 −87.041 errord 0 selected based on lowest AIC. Exponential (M5) N/Ae −85.880 errord 0 Hill 0.301 −87.880 errord errord Powerf 0.126 −86.804 657 296 Polynomial 3°g Polynomial 2°h Linear a Constant variance case presented (BMDS Test 2 p-value = 0.777), selected model in bold; scaled residuals for selected model for doses 0, 90, 200, and 420 mg/kg-d were −0.78, −0.11, 1.65, −0.76, respectively. b The Exponential (M2) model can appear equivalent to the Exponential (M3) model, however differences exist in digits not displayed in the table. c The Exponential (M3) model can appear equivalent to the Exponential (M2) model, however differences exist in digits not displayed in the table. d BMD or BMDL computation failed for this model. e No available degrees of freedom to calculate a goodness-of-fit value. f For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. g For the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model. h For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Linear model.

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Linear Model, with BMR of 0.1 Rel. Dev. for the BMD and 0.95 Lower Confidence Limit for the BMDL

Linear

2.1

2

1.9 Mean Response

1.8

1.7

BMDL BMD

0 100 200 300 400 500 600 dose 1 11:46 05/26 2015 2 Figure C-3. Plot of mean response by dose, with fitted curve for Linear model 3 with constant variance for absolute kidney weight in male F344 rats exposed 4 to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. 5 dev. from control mean; dose shown in mg/kg-d

6 Polynomial Model. (Version: 2.20; Date: 10/22/2014) 7 The form of the response function is: Y[dose] = beta_0 + beta_1*dose. 8 A constant variance model is fit.

9 Benchmark Dose Computation. 10 BMR = 10% Relative deviation 11 BMD = 656.583 12 BMDL at the 95% confidence level = 295.826

13 Parameter Estimates

Default Initial Variable Estimate Parameter Values alpha 0.0361494 0.0362125 rho n/a 0 beta_0 1.83173 1.83173 beta_1 0.000278979 0.000278979 14

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1 Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid 0 10 1.78 1.83 0.18 0.19 −0.777 90 10 1.85 1.86 0.17 0.19 −0.114 200 10 1.99 1.89 0.18 0.19 1.65 420 10 1.9 1.95 0.23 0.19 −0.763

2 Likelihoods of Interest

Model Log(likelihood) # Param's AIC A1 48.474229 5 −86.948457 A2 49.025188 8 −82.050377 A3 48.474229 5 −86.948457 fitted 46.401914 3 −86.803828 R 45.368971 2 −86.737942

3 Tests of Interest

−2*log(Likelihood Test Ratio) Test df p-value Test 1 7.31243 6 0.2929 Test 2 1.10192 3 0.7766 Test 3 1.10192 3 0.7766 Test 4 4.14463 2 0.1259 4

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1 Table C-5. Summary of BMD modeling results for absolute kidney weight in 2 female F344 rats exposed to tert-butanol in drinking water for 15 months 3 (NTP, 1995); BMR = 10% rel. dev. from control mean

Goodness of fit BMD10RD BMDL10RD Modela p-value AIC (mg/kg-d) (mg/kg-d) Basis for model selection Exponential (M2) 0.0594 −144.00 318 249 The Exponential (M4) model was Exponential (M3)b selected as the only model with adequate fit. Exponential (M4) 0.176 −145.81 164 91.4 Exponential (M5) N/Ac −145.65 207 117 Hill N/Ac −145.65 202 119 Powerd 0.0842 −144.70 294 224 Polynomial 3°e Polynomial 2°f Linear a Constant variance case presented (BMDS Test 2 p-value = 0.852), selected model in bold; scaled residuals for selected model for doses 0, 180, 330, and 650 mg/kg-d were 0.21, −0.9, 0.94, −0.25, respectively. b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model. c No available degrees of freedom to calculate a goodness-of-fit value. d For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. e For the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model. f For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Linear model. 4

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Exponential 4 Model, with BMR of 0.1 Rel. Dev. for the BMD and 0.95 Lower Confidence Limit for the BMDL

1.4 Exponential 4

1.35

1.3

1.25

1.2

Mean Response 1.15

1.1

1.05

1 BMDL BMD

0 100 200 300 400 500 600 dose 1 11:32 05/26 2015 2 Figure C-4. Plot of mean response by dose, with fitted curve for Exponential 3 (M4) model with constant variance for absolute kidney weight in female F344 4 rats exposed to tert-butanol in drinking water for 15 months (NTP, 1995); 5 BMR = 10% rel. dev. from control mean; dose shown in mg/kg-d

6 Exponential Model. (Version: 1.10; Date: 01/12/2015) 7 The form of the response function is: Y[dose] = a * [c (c 1) * exp( b * dose)]. 8 A constant variance model is fit. − − − 9 Benchmark Dose Computation. 10 BMR = 10% Relative deviation 11 BMD = 163.803 12 BMDL at the 95% confidence level = 91.3614

13 Parameter Estimates

Default Initial Variable Estimate Parameter Values lnalpha −4.84526 −4.89115 rho n/a 0 a 1.06808 1.0203 b 0.00258011 0.00282085 c 1.29013 1.35122 d n/a 1 14

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1 Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid 0 10 1.07 1.07 0.09 0.09 0.2112 180 10 1.16 1.18 0.1 0.09 −0.8984 330 10 1.27 1.25 0.08 0.09 0.9379 650 10 1.31 1.32 0.09 0.09 −0.2507

2 Likelihoods of Interest

Model Log(likelihood) # Param's AIC A1 77.82307 5 −145.6461 A2 78.21688 8 −140.4338 A3 77.82307 5 −145.6461 R 62.21809 2 −120.4362 4 76.90527 4 −145.8105

3 Tests of Interest

−2*log(Likelihood Test Ratio) Test df p-value Test 1 32 6 <0.0001 Test 2 0.7876 3 0.8524 Test 3 0.7876 3 0.8524 Test 6a 1.836 1 0.1755 4

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1 Table C-6. Summary of BMD modeling results for kidney inflammation in 2 female rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); 3 BMR = 10% extra risk

Goodness of fit

BMD10% BMDL10% Modela p-value AIC (mg/kg-d) (mg/kg-d) Basis for model selection Gamma 0.084 169.9 231 135 LogProbit was selected on the basis of the lowest AIC with all Logistic 0.082 169.7 305 252 BMDL values for fitting models being sufficiently close (BMDLs LogLogistic 0.092 169.8 228 124 differed by less than 3-fold). LogProbit 0.243 167.6 254 200

Multistage 3° 0.072 170.3 216 132

Probit 0.108 169.2 285 235

Weibull 0.081 170.0 226 134

Dichotomous-Hill N/Ab 169.5 229 186 aSelected model in bold; scaled residuals for selected model for doses 0, 180, 330, and 650 mg/kg-d were −0.067, −0.700, 1.347, and −0.724, respectively. bNo available degrees of freedom to estimate a p-value.

LogProbit Model with 0.95 Confidence Level

LogProbit 0.5

0.4

0.3

0.2 Fraction Affected

0.1

0 BMDL BMD 0 100 200 300 400 500 600 dose 4 17:17 05/13 2011 5 Figure C-5. Plot of incidence by dose, with fitted curve for Logprobit model for 6 kidney inflammation in female rats exposed to tert-butanol in drinking water 7 for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d 8

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1 ======2 Probit Model. (Version: 3.2; Date: 10/28/2009) 3 Input Data File: M:/NCEA tert-butanol/BMD modeling/BMDS Output/19 NTP 4 1995b_Kidney inflammation, female rats_LogProbit_10.(d) 5 Gnuplot Plotting File: M:/NCEA tert-butanol/BMD modeling/BMDS Output/19 NTP 6 1995b_Kidney inflammation, female rats_LogProbit_10.plt 7 Fri May 13 17:17:59 2011 8 ======9 10 [notes] 11 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 12 13 The form of the probability function is: 14 15 P[response] = Background 16 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)), 17 18 where CumNorm(.) is the cumulative normal distribution function 19 20 21 Dependent variable = Incidence 22 Independent variable = Dose 23 Slope parameter is restricted as slope >= 1 24 25 Total number of observations = 4 26 Total number of records with missing values = 0 27 Maximum number of iterations = 250 28 Relative Function Convergence has been set to: 1e-008 29 Parameter Convergence has been set to: 1e-008 30 31 32 33 User has chosen the log transformed model 34 35 36 Default Initial (and Specified) Parameter Values 37 background = 0.04 38 intercept = -8.01425 39 slope = 1.18928 40 41 42 Asymptotic Correlation Matrix of Parameter Estimates 43 44 ( *** The model parameter(s) -slope 45 have been estimated at a boundary point, or have been specified by the user, 46 and do not appear in the correlation matrix ) 47 48 background intercept 49 50 background 1 -0.51 51 52 intercept -0.51 1 53 54 55 56 Parameter Estimates 57 58 95.0% Wald Confidence Interval 59 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 60 background 0.0381743 0.0246892 -0.0102155 0.0865642 61 intercept -6.82025 0.161407 -7.1366 -6.5039 62 slope 1 NA 63 64 NA - Indicates that this parameter has hit a bound 65 implied by some inequality constraint and thus 66 has no standard error. 67 68 69 70 Analysis of Deviance Table

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1 2 Model Log(likelihood) # Param's Deviance Test d.f. P-value 3 Full model -80.4502 4 4 Fitted model -81.8218 2 2.7432 2 0.2537 5 Reduced model -92.7453 1 24.5902 3 <.0001 6 7 AIC: 167.644 8 9 10 Goodness of Fit 11 Scaled 12 Dose Est._Prob. Expected Observed Size Residual 13 ------14 0.0000 0.0382 1.909 2.000 50 0.067 15 180.0000 0.0880 4.402 3.000 50 -0.700 16 330.0000 0.1859 9.295 13.000 50 1.347 17 650.0000 0.3899 19.495 17.000 50 -0.724 18 19 Chi^2 = 2.83 d.f. = 2 P-value = 0.2427 20 21 22 Benchmark Dose Computation 23 24 Specified effect = 0.1 25 26 Risk Type = Extra risk 27 28 Confidence level = 0.95 29 30 BMD = 254.347 31 32 BMDL = 199.789 33 34

35

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1 Table C-7. Summary of BMD modeling results for absolute kidney weight in 2 male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 3 weeks (NTP, 1997); BMR = 10% relative deviation from the mean

Goodness of fit BMC10RD BMCL10RD Modela p-value AIC (mg/m3) (mg/m3) Basis for model selection Exponential (M2) <0.0001 −205.06 errorb errorb Although the Hill model was the only adequately fitting model Exponential (M3) <0.0001 −203.06 9.2E+07 7094 (p>0.1), the resulting fit was Exponential (M4) <0.0001 −203.06 errorb 0 essentially a step-function that does not support interpolation Exponential (M5) <0.0001 −201.06 errorb 0 between the well-fit Hill 0.763 −226.82 1931 1705 observations. Powerc 0.0607 −220.97 5364 3800 Linear Polynomial 5°d 1.44E−04 −207.06 −9999 errorf Polynomial 4°e Polynomial 3° Polynomial 2° 1.44E−04 −207.06 −9999 18436 a Constant variance case presented (BMDS Test 2 p-value = 0.390), selected model in bold; scaled residuals for selected model for doses 0, 406, 825, 1,643, 3,274, and 6,369 mg/m3 were 0.395, 0.374, −0.75, −1.96e−006, 0.381, and −0.381, respectively. b BMC or BMCL computation failed for this model. c For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. d For the Polynomial 5° model, the b5 and b4 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Polynomial 3° model. e For the Polynomial 4° model, the b4 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 3° model. f BMC or BMCL computation failed for this model.

Hill Model with 0.95 Confidence Level

1.4 Hill

1.35

1.3

1.25 Mean Response 1.2

1.15

BMDL BMD 1.1 0 1000 2000 3000 4000 5000 6000 dose 4 10:15 04/30 2014

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1 Figure C-6. Plot of mean response by concentration, with fitted curve for Hill 2 model for absolute kidney weight in male F344 rats exposed to tert-butanol 3 via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% 4 relative deviation from the mean; concentration shown in mg/m3

5 Hill Model. (Version: 2.15; Date: 10/28/2009) 6 The form of the response function is: Y[dose] = intercept + v*dose^n/(k^n + dose^n). 7 A constant variance model is fit.

8 Benchmark Dose Computation. 9 BMR = 10% Relative risk 10 BMD = 1931.35 11 BMDL at the 95% confidence level = 1704.82

12 Parameter Estimates

Default Initial Variable Estimate Parameter Values alpha 0.00687349 0.00750263 rho n/a 0 intercept 1.19966 1.21 v 0.130345 0.13 n 18 18 k 1685.82 4451.94 13

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1 Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid 0 10 1.21 1.2 0.0822 0.0829 0.395 406 9 1.21 1.2 0.096 0.0829 0.374 825 10 1.18 1.2 0.0791 0.0829 −0.75 1643 10 1.25 1.25 0.111 0.0829 −0.00000196 3274 10 1.34 1.33 0.0538 0.0829 0.381 6369 10 1.32 1.33 0.0885 0.0829 −0.381

2 Likelihoods of Interest

Model Log(likelihood) # Param's AIC A1 117.992549 7 −221.985098 A2 120.600135 12 −217.20027 A3 117.992549 7 −221.985098 fitted 117.41244 4 −226.82488 R 105.528775 2 −207.05755

3 Tests of Interest

Test −2*log(Likelihood Test df p-value Ratio) Test 1 30.1427 10 0.0008118 Test 2 5.21517 5 0.3902 Test 3 5.21517 5 0.3902 Test 4 1.16022 3 0.7626 4

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1 Table C-8. Summary of BMD modeling results for absolute kidney weight in 2 female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 3 13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean

Goodness of fit BMC10RD BMCL10RD Modela p-value AIC (mg/m3) (mg/m3) Basis for model selection Exponential (M2) 0.0378 −261.52 14500 7713 No model adequately fit the data. Exponential (M3)b Exponential (M4) 0.533 −267.48 errorc 0 Exponential (M5) 0.374 −265.71 errorc 0 Hill 0.227 −265.57 errorc errorc Power 0.0392 −261.61 14673 7678 Polynomial 3°d 0.0274 −261.61 14673 7678 Polynomial 2°e Linear Polynomial 5° 0.0274 −261.61 14673 7569 Polynomial 4° 0.0274 −261.61 14673 7674 a Modeled variance case presented (BMDS Test 2 p-value = 1.90E−04, BMDS Test 3 p-value = 0.374), no model was selected as a best-fitting model. b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model. c BMC or BMCL computation failed for this model. d For the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model. e For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in this row reduced to the Linear model. Note: Graphs of the better fitting models are provided for illustration. 4

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Hill Model

Hill

0.9

0.85

0.8 Mean Response

0.75

0.7 0 1000 2000 3000 4000 5000 6000 dose 1 10:32 04/30 2014

2 Figure C-7. Plot of mean response by concentration, with fitted curve for Hill 3 model for absolute kidney weight in female F344 rats exposed to tert-butanol 4 via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% 5 relative deviation from the mean; concentration shown in mg/m3 Power Model with 0.95 Confidence Level

Power

0.9

0.85

0.8 Mean Response

0.75

BMDL BMD 0.7 0 2000 4000 6000 8000 10000 12000 14000 dose 6 10:32 04/30 2014

7 Figure C-8. Plot of mean response by concentration, with fitted curve for 8 Power model for absolute kidney weight in female F344 rats exposed to tert­ 9 butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10 10% relative deviation from the mean; concentration shown in mg/m3 11

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1 Cancer Endpoints 2 C.1.2.1. Data Sets 3 The cancer data sets selected for dose-response modeling are summarized in Table C-9. In 4 all cases, administered exposure was used in modeling the response data. Due to the significant 5 difference in survival in the high-dose male mice compared with the concurrent control, the Poly-3 6 procedure (Bailer and Portier, 1988) for adjusting tumor incidence rates for intercurrent mortality 7 was used. The procedure is based on the observation that the cumulative incidence of tumors tends 8 to increase with time raised to the second through the fourth powers for a large proportion of 9 cases. In the Poly-3 procedure, for a study of T weeks’ duration, an animal that is removed from the 10 study after t weeks (t < T) without a specified type of tumor of interest is given a weight of (t/T)3. 11 An animal that survives until the terminal sacrifice at T weeks is assigned a weight of (T/T)3 = 1. An 12 animal that develops the specific type of tumor of interest obviously lived long enough to develop 13 the tumor, and is assigned a weight of 1. The Poly-3 tumor incidence, adjusted for intercurrent 14 mortality up to time T, is the number of animals in a dose group with the specified type of tumor 15 divided by the sum of the weights (the effective number of animals at risk). The tumor incidences, 16 adjusted using this procedure, also are provided in Table C-9. 17 C.1.2.2. Model Fit 18 The multistage model was fit to the cancer data sets. Model coefficients were restricted to 19 be non-negative (beta values , to estimate a monotonically increasing function. Each model was 20 fit to the data using the maximum likelihood method, and was tested for goodness-of-fit using a chi­ ≥ 0) 21 square goodness-of- 2 p-value < 0.051 indicates lack of fit). Other factors were used to 22 assess model fit, such as scaled residuals, visual fit, and adequacy of fit in the low dose region and fit test (χ 23 near the BMR. 24 For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as 25 estimated by the profile likelihood method) and AIC value were used to select a best-fit model from 26 among the models exhibiting adequate fit. For the NTP (1995) and Hard et al. (2011) data, models 27 were run with all doses included, as well as with the high dose dropped. Dropping the high dose 28 resulted in a better fit to the data. Including the high dose caused the model to overestimate the 29 control.

1A significance level of 0.05 is used for selecting cancer models because the model family (multistage) is selected a priori (U.S. EPA, 2000).

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1 Table C-9. Cancer endpoints selected for dose-response modeling for tert­ 2 butanol

Endpoint/Study Species/Sex Doses and Effect Data Thyroid Dose (mg/kg-d) 0 510 1,020 2,110 Thyroid follicular cell B6C3F1 adenoma mice/female NTP (1995) Incidence/Total 2/58 3/60 2/59 9/59

Thyroid follicular cell B6C3F1 Dose (mg/kg-d) 0 540 1,040 2,070 adenoma mice/male NTP (1995) Incidence/Total 1/60 0/59 4/59 2/60

Incidence/Poly-3 1/50 0/50 4/51 2/35 adjusted Total

Kidneya Renal tubule adenoma or Rat (F344) / Dose (mg/kg-d) 0 90 200 420 carcinoma Male Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50 NTP (1995) Renal tubule adenoma or Rat (F344) / Dose (PBPK, mg/L) 0 4.6945 12.6177 40.7135 carcinoma Male Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50 NTP (1995) Renal tubule adenoma or Rat (F344) / Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712 carcinoma Male Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50 NTP (1995) Renal tubule adenoma or Rat (F344) / Dose (mg/kg-d) 0 90 200 420 carcinoma; Hard Male reanalysis Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50 NTP (1995);Hard et al. (2011) Renal tubule adenoma or Rat (F344) / Dose (PBPK, mg/L) 0 4.6945 12.6177 40.7135 carcinoma; Hard Male reanalysis Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50 NTP (1995);Hard et al. (2011) Renal tubule adenoma or Rat (F344) / Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712 carcinoma; Hard Male reanalysis Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50 NTP (1995);Hard et al. (2011) 3 a Endpoint presented if kidney tumors are acceptable for quantitation 4

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1 Table C-10. Summary of the oral slope factor derivations

BMR BMD POD= a b (mg/kg- BMDL BMDLHED Slope factor -1 Tumor Species/Sex Selected Model d) (mg/kg-d) (mg/kg-d) (mg/kg-day) Thyroid Thyroid follicular cell Female 3° Multistage 10% 2002 1437 201 5 × 10-4 adenoma B6C3F1 mouse Kidneyc Renal tubule Male F344 1° Multistage 10% 70 42 10.1 1 × 10-2 adenoma or rat; dose as (high dose carcinoma administered dropped) Renal tubule Male F344 1° Multistage 10% 54 36 8.88 1 x 10-2 adenoma or rat; dose as (high dose carcinoma [Hard et administered dropped) al. (2011) reanalysis] 2 aHED PODs were calculated using BW3/4 scaling (U.S. EPA, 2011). b 3 Human equivalent slope factor = 0.1/BMDL10HED 4 cAlternative endpoint if kidney tumors are acceptable for quantitation. 5

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1 C.1.2.3. Modeling Results

2 Table C-11. Summary of BMD modeling results for thyroid follicular cell 3 adenomas in female B6C3F1 mice exposed to tert-butanol in drinking water 4 for 2 years (NTP, 1995); BMR = 10% extra risk

Goodness of fit c c BMD10% BMDL10% Modela p-value AIC b (mg/kg-d) (mg/kg-d) Basis for model selection Multistage 3° was selected on the basis of Three 0.75 113.665 2002 1437 the lowest AIC with all BMDL values for fitting models being sufficiently close Two 0.36 115.402 2186 1217 (BMDLs differed by less than 3-fold).

One 0.63 114.115 1987 1378

a Selected (best-fitting) model shown in boldface type. b AIC = Akaike Information Criterion. c Confidence level = 0.95.

Multistage Cancer Model with 0.95 Confidence Level 0.3 Multistage Cancer Linear extrapolation

0.25

0.2

0.15

Fraction Affected 0.1

0.05

0 BMDL BMD 0 500 1000 1500 2000 dose 5 15:22 05/13 2011 6 Figure C-9. Plot of incidence by dose, with fitted curve for Multistage 3° model 7 for thyroid follicular cell adenomas in female B6C3F1 mice exposed to tert­ 8 butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose 9 shown in mg/kg-d

10 ======11 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 12 Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP 1995b_Thyroid 13 folluclar cell andenoma, female mice_MultiCanc3_10.(d) 14 Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP 15 1995b_Thyroid folluclar cell andenoma, female mice_MultiCanc3_10.plt 16 Fri May 13 15:22:18 2011 17 ======18

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1 [notes] 2 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 3 4 The form of the probability function is: 5 6 P[response] = background + (1-background)*[1-EXP( 7 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 8 9 The parameter betas are restricted to be positive 10 11 12 Dependent variable = Incidence 13 Independent variable = Dose 14 15 Total number of observations = 4 16 Total number of records with missing values = 0 17 Total number of parameters in model = 4 18 Total number of specified parameters = 0 19 Degree of polynomial = 3 20 21 22 Maximum number of iterations = 250 23 Relative Function Convergence has been set to: 1e-008 24 Parameter Convergence has been set to: 1e-008 25 26 27 28 Default Initial Parameter Values 29 Background = 0.0347373 30 Beta(1) = 0 31 Beta(2) = 0 32 Beta(3) = 1.36917e-011 33 34 35 Asymptotic Correlation Matrix of Parameter Estimates 36 37 ( *** The model parameter(s) -Beta(1) -Beta(2) 38 have been estimated at a boundary point, or have been specified by the 39 user, 40 and do not appear in the correlation matrix ) 41 42 Background Beta(3) 43 44 Background 1 -0.53 45 46 Beta(3) -0.53 1 47 48 49 50 Parameter Estimates 51 52 95.0% Wald Confidence Interval 53 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. 54 Limit 55 Background 0.0361209 * * * 56 Beta(1) 0 * * * 57 Beta(2) 0 * * * 58 Beta(3) 1.31301e-011 * * * 59 60 * - Indicates that this value is not calculated. 61 62 63 64 Analysis of Deviance Table 65 66 Model Log(likelihood) # Param's Deviance Test d.f. P-value 67 Full model -54.5437 4 68 Fitted model -54.8326 2 0.577881 2 0.7491 69 Reduced model -58.5048 1 7.92235 3 0.04764 70 71 AIC: 113.665

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1 2 3 Goodness of Fit 4 Scaled 5 Dose Est._Prob. Expected Observed Size Residual 6 ------­ 7 0.0000 0.0361 2.095 2.000 58 -0.067 8 510.0000 0.0378 2.268 3.000 60 0.496 9 1020.0000 0.0495 2.918 2.000 59 -0.551 10 2110.0000 0.1480 8.730 9.000 59 0.099 11 12 Chi^2 = 0.56 d.f. = 2 P-value = 0.7544 13 14 15 Benchmark Dose Computation 16 17 Specified effect = 0.1 18 19 Risk Type = Extra risk 20 21 Confidence level = 0.95 22 23 BMD = 2002.03 24 25 BMDL = 1436.69 26 27 BMDU = 3802.47 28 29 Taken together, (1436.69, 3802.47) is a 90 % two-sided confidence 30 interval for the BMD 31 32 Multistage Cancer Slope Factor = 6.96043e-005 33 34

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1 Table C-12. Summary of BMD modeling results for thyroid follicular cell 2 adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in 3 drinking water for 2 years (NTP, 1995); BMR = 5% extra risk

Goodness of fit c BMD5% BMDL5% Modela p-value AIC b (mg/kg-d) (mg/kg-d) Basis for model selection One, Two, Multistage 1° was selected. Only form of 0.202 61.6 1788 787 Three multistage that resulted; fit adequate. a Selected (best-fitting) model shown in boldface type. b AIC = Akaike Information Criterion. c Confidence level = 0.95.

Multistage Cancer Model, with BMR of 5% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL

Multistage Cancer Linear extrapolation 0.2

0.15

0.1 Fraction Affected

0.05

0

BMDL BMD

0 500 1000 1500 2000 dose 4 11:02 06/05 2015

5 Figure C-10. Plot of incidence by dose, with fitted curve for Multistage 1° 6 model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice 7 exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 5% 8 extra risk; dose shown in mg/kg-d 9 10 11 ======12 Multistage Model. (Version: 3.4; Date: 05/02/2014) 13 Input Data File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid tumors 14 poly3_Msc1-BMR05.(d) 15 Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid 16 tumors poly3_Msc1-BMR05.plt 17 Fri Jun 05 11:02:14 2015 18 ======19 20 BMDS_Model_Run 21 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 22 23 The form of the probability function is: 24 25 P[response] = background + (1-background)*[1-EXP( 26 -beta1*dose^1)]

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1 2 The parameter betas are restricted to be positive 3 4 5 Dependent variable = Effect 6 Independent variable = Dose 7 8 Total number of observations = 4 9 Total number of records with missing values = 0 10 Total number of parameters in model = 2 11 Total number of specified parameters = 0 12 Degree of polynomial = 1 13 14 15 Maximum number of iterations = 500 16 Relative Function Convergence has been set to: 1e-008 17 Parameter Convergence has been set to: 1e-008 18 19 20 21 Default Initial Parameter Values 22 Background = 0.0164855 23 Beta(1) = 2.58163e-005 24 25 26 Asymptotic Correlation Matrix of Parameter Estimates 27 28 Background Beta(1) 29 30 Background 1 -0.56 31 32 Beta(1) -0.56 1 33 34 35 36 Parameter Estimates 37 38 95.0% Wald Confidence Interval 39 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 40 Background 0.0149284 0.0144833 -0.0134584 0.0433151 41 Beta(1) 2.86952e-005 1.99013e-005 -1.03105e-005 6.7701e-005 42 43 44 45 Analysis of Deviance Table 46 47 Model Log(likelihood) # Param's Deviance Test d.f. P-value 48 Full model -26.5891 4 49 Fitted model -28.808 2 4.43785 2 0.1087 50 Reduced model -29.8255 1 6.47273 3 0.09074 51 52 AIC: 61.616 53 54 55 Goodness of Fit 56 Scaled 57 Dose Est._Prob. Expected Observed Size Residual 58 ------59 0.0000 0.0149 0.746 1.000 50.000 0.296 60 540.0000 0.0301 1.504 0.000 50.000 -1.245 61 1040.0000 0.0439 2.238 4.000 51.000 1.204 62 2070.0000 0.0717 2.511 2.000 35.000 -0.335 63 64 Chi^2 = 3.20 d.f. = 2 P-value = 0.2019 65 66 67 Benchmark Dose Computation 68 69 Specified effect = 0.05 70 71 Risk Type = Extra risk

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1 2 Confidence level = 0.95 3 4 BMD = 1787.52 5 6 BMDL = 787.153 7 8 9 BMDU did not converge for BMR = 0.050000 10 BMDU calculation failed 11 BMDU = Inf

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1 Table C-13. Summary of BMD modeling results for thyroid follicular cell 2 adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in 3 drinking water for 2 years, high dose omitted (NTP, 1995); BMR = 5% extra 4 risk

Goodness of fit c BMD5% BMDL5% Modela p-value AIC b (mg/kg-d) (mg/kg-d) Basis for model selection Multistage 2° was selected based on lowest AIC. One stage 0.105 46.0 1341 538

Two stage 0.174 44.9 1028 644

a Selected (best-fitting) model shown in boldface type. b AIC = Akaike Information Criterion. c Confidence level = 0.95.

Multistage Cancer Model, with BMR of 5% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL

Multistage Cancer 0.2 Linear extrapolation

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BMDL BMD

0 200 400 600 800 1000 dose 11:18 06/05 2015 5 6 Figure C-11. Plot of incidence by dose, with fitted curve for Multistage 2° 7 model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice 8 exposed to tert-butanol in drinking water for 2 years, high dose omitted (NTP, 9 1995); BMR = 5% extra risk; dose shown in mg/kg-d

10 11 12 ======13 Multistage Model. (Version: 3.4; Date: 05/02/2014) 14 Input Data File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid tumors 15 poly3 -h_Msc2-BMR05.(d) 16 Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid 17 tumors poly3 -h_Msc2-BMR05.plt 18 Fri Jun 05 11:18:05 2015 19 ======20 21 BMDS_Model_Run

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1 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 2 3 The form of the probability function is: 4 5 P[response] = background + (1-background)*[1-EXP( 6 -beta1*dose^1-beta2*dose^2)] 7 8 The parameter betas are restricted to be positive 9 10 11 Dependent variable = Effect 12 Independent variable = Dose 13 14 Total number of observations = 3 15 Total number of records with missing values = 0 16 Total number of parameters in model = 3 17 Total number of specified parameters = 0 18 Degree of polynomial = 2 19 20 21 Maximum number of iterations = 500 22 Relative Function Convergence has been set to: 1e-008 23 Parameter Convergence has been set to: 1e-008 24 25 26 27 Default Initial Parameter Values 28 Background = 0.00347268 29 Beta(1) = 0 30 Beta(2) = 6.65923e-008 31 32 33 Asymptotic Correlation Matrix of Parameter Estimates 34 35 ( *** The model parameter(s) -Beta(1) 36 have been estimated at a boundary point, or have been specified by the user, 37 and do not appear in the correlation matrix ) 38 39 Background Beta(2) 40 41 Background 1 -0.34 42 43 Beta(2) -0.34 1 44 45 46 47 Parameter Estimates 48 49 95.0% Wald Confidence Interval 50 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit 51 Background 0.011558 0.0114911 -0.010964 0.0340801 52 Beta(1) 0 NA 53 Beta(2) 4.84624e-008 3.15009e-008 -1.32781e-008 1.10203e-007 54 55 NA - Indicates that this parameter has hit a bound 56 implied by some inequality constraint and thus 57 has no standard error. 58 59 60 61 Analysis of Deviance Table 62 63 Model Log(likelihood) # Param's Deviance Test d.f. P-value 64 Full model -18.9229 3 65 Fitted model -20.4481 2 3.05031 1 0.08072 66 Reduced model -21.9555 1 6.0651 2 0.04819 67 68 AIC: 44.8962 69 70 71 Goodness of Fit

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1 Scaled 2 Dose Est._Prob. Expected Observed Size Residual 3 ------­ 4 0.0000 0.0116 0.578 1.000 50.000 0.558 5 540.0000 0.0254 1.271 0.000 50.000 -1.142 6 1040.0000 0.0620 3.164 4.000 51.000 0.485 7 8 Chi^2 = 1.85 d.f. = 1 P-value = 0.1735 9 10 11 Benchmark Dose Computation 12 13 Specified effect = 0.05 14 15 Risk Type = Extra risk 16 17 Confidence level = 0.95 18 19 BMD = 1028.79 20 21 BMDL = 644.475 22 23 24 BMDU did not converge for BMR = 0.050000 25 BMDU calculation failed 26 BMDU = 14661.6 27 28 Cancer Slope Factor = 7.75825e-005

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1 Table C-14. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with administered dose units and including all dose groups 4 (NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct (mg/kg­ Basis for model d) selection p- Scaled residuals AIC value Three 0.0806 -0.989, 0.288, 1.719, 233.94 294 118 Multistage 2° is Two and -1.010 selected as the most parsimonious model One 0.0806 -0.989, 0.288, 1.719, 233.94 294 errorb of adequate fit. and -1.010 a Selected model in bold. b BMD or BMDL computation failed for this model.

6 Multistage Cancer Model with 0.95 Confidence Level

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9 Figure C-12. Plot of incidence by dose, with fitted curve for Multistage 2° 10 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 11 tert-butanol in drinking water for 2 years modeled with administered dose 12 units and including all dose groups (NTP, 1995); BMR = 10% extra risk; dose 13 shown in mg/kg-d. 14

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 293.978 9 BMDL at the 95% confidence level = 117.584 10 BMDU at the 95% confidence level = 543384000 11 Taken together, (117.584, 543384000) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = 0.000850453 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.217704 0.2335 Beta(1) 0.000358397 0.000268894 Beta(2) 0 0 15 16 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -112.492 4 Fitted model -114.97 2 4.95502 2 0.08395 Reduced -115.644 1 6.30404 3 0.09772 model 17 18 AIC: = 233.94 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.2177 10.885 8 50 -0.989 90 0.2425 12.127 13 50 0.288 200 0.2718 13.591 19 50 1.719 420 0.327 16.351 13 50 -1.01 21 22 Chi^2 = 5.04 d.f = 2 P-value = 0.0806 23 24

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1 Table C-15. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with administered dose units and excluding high-dose group 4 (NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct Basis for model (mg/kg-d) selection p- Scaled residuals AIC value Two N/Ab 0.000, -0.000, and ­ 173.68 75.6 41.6 Multistage 1° was 0.000 selected as the only adequately-fitting One 0.924 0.031, -0.078, and 171.69 70.1 41.6 model available 0.045 a Selected model in bold. b No available degrees of freedom to calculate a goodness of fit value.

6 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation

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BMDL BMD 0 50 100 150 200 dose 7 11:02 04/30 2014 8

9 Figure C-13. Plot of incidence by dose, with fitted curve for Multistage 1° 10 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 11 tert-butanol in drinking water for 2 years modeled with administered dose 12 units and excluding high-dose group (NTP, 1995); BMR = 10% extra risk.; dose 13 shown in mg/kg-d. 14

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 70.1068 9 BMDL at the 95% confidence level = 41.5902 10 BMDU at the 95% confidence level = 203.311 11 Taken together, (41.5902, 203.311) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = 0.00240441 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.158399 0.156954 Beta(1) 0.00150286 0.0015217 15 16 Analysis of Deviance Table Model Log(likelihood # Param's Deviance Test d.f. p-value ) Full model -83.8395 3 Fitted model -83.8441 2 0.00913685 1 0.9238 Reduced -86.9873 1 6.29546 2 0.04295 model 17 18 AIC: = 171.688 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.1584 7.92 8 50 0.031 90 0.2649 13.243 13 50 -0.078 200 0.3769 18.844 19 50 0.045 21 22 Chi^2 = 0.01 d.f = 1 P-value = 0.9239 23 24

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1 Table C-16. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with PBPK (tert-butanol, mg/L) dose units and including all 4 dose groups (NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model selection p- Scaled residuals AIC value Three 0.0518 -1.373, 0.155, 1.889, 234.83 51.8 13.9 Multistage 1° was Two and -0.668 selected as the One most parsimonious model of adequate fit. a Selected model in bold.

6 Multistage Cancer Model with 0.95 Confidence Level

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BMDL BMD 0 10 20 30 40 50 dose 7 11:19 04/30 2014 8

9 Figure C-14. Plot of incidence by dose, with fitted curve for Multistage 1° 10 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 11 tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, 12 mg/L) dose units and including all dose groups (NTP, 1995); BMR = 10% extra 13 risk.; dose shown in mg/L. 14

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 51.8357 9 BMDL at the 95% confidence level = 13.9404 10 BMDU at the 95% confidence level = error 11 Taken together, (13.9404, error) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = error 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.243327 0.253053 Beta(1) 0.00203259 0.00150893 15 16 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -112.492 4 Fitted model -115.417 2 5.84883 2 0.0537 Reduced -115.644 1 6.30404 3 0.09772 model 17 18 AIC: = 234.834 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.2433 12.166 8 50 -1.373 4.6945 0.2505 12.526 13 50 0.155 12.6177 0.2625 13.124 19 50 1.889 40.7135 0.3034 15.171 13 50 -0.668 21 22 Chi^2 = 5.92 d.f = 2 P-value = 0.0518 23

24

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1 Table C-17. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high- 4 dose group (NTP, 1995); BMR = 10% extra risk.

a Model Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model selection p- Scaled residuals AIC value Two 0.891 -0.054, 0.113, and ­ 171.70 4.33 2.54 Multistage 1° was One 0.057 selected as the most parsimonious model of adequate fit. a Selected model in bold.

5 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation

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BMDL BMD 0 2 4 6 8 10 12 dose 6 11:20 04/30 2014 7

8 Figure C-15. Plot of incidence by dose, with fitted curve for Multistage 1° 9 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 10 tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, 11 mg/L) dose units and excluding high-dose group (NTP, 1995); BMR = 10% 12 extra risk; dose shown in mg/L. 13

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 4.33496 9 BMDL at the 95% confidence level = 2.53714 10 BMDU at the 95% confidence level = 12.8097 11 Taken together, (2.53714, 12.8097) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = 0.0394144 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.162798 0.164724 Beta(1) 0.0243048 0.0238858 15 16 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -83.8395 3 Fitted model -83.8489 2 0.0187339 1 0.8911 Reduced -86.9873 1 6.29546 2 0.04295 model 17 18 AIC: = 171.698 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.1628 8.14 8 50 -0.054 4.6945 0.2531 12.654 13 50 0.113 12.6177 0.3839 19.195 19 50 -0.057 21 22 Chi^2 = 0.02 d.f = 1 P-value = 0.891 23 24

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1 Table C-18. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with PBPK (metabolized, mg/hr) dose units and including all 4 dose groups (NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/hr) BMDL10Pct (mg/hr) Basis for model selection p- Scaled residuals AIC value Three 0.0885 -0.920, 0.301, 1.677, 233.76 2.28 0.954 Multistage 1° was Two and -1.049 selected as the most One parsimonious model of adequate fit. a Selected model in bold. 6 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation

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BMDL BMD 0 0.5 1 1.5 2 2.5 3 3.5 dose 7 11:22 04/30 2014 8

9 Figure C-16. Plot of incidence by dose, with fitted curve for Multistage 1° 10 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 11 tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, 12 mg/hr) dose units and including all dose groups (NTP, 1995); BMR = 10% 13 extra risk; dose shown in mg/hr. 14

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 2.28299 9 BMDL at the 95% confidence level = 0.95436 10 BMDU at the 95% confidence level = error 11 Taken together, (0.95436, error) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = error 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.21328 0.229822 Beta(1) 0.0461502 0.0349139 15 16 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -112.492 4 Fitted model -114.879 2 4.77309 2 0.09195 Reduced -115.644 1 6.30404 3 0.09772 model 17 18 AIC: = 233.758 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.2133 10.664 8 50 -0.92 0.7992 0.2418 12.088 13 50 0.301 1.7462 0.2742 13.71 19 50 1.677 3.4712 0.3297 16.487 13 50 -1.049 21 22 Chi^2 = 4.85 d.f = 2 P-value = 0.0885 23 24

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1 Table C-19. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with PBPK (metabolized, mg/hr) dose units and excluding 4 high-dose group (NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/hr) BMDL10Pct (mg/hr) Basis for model selection p- Scaled residuals AIC value Two N/Ab -0.000, -0.000, and ­ 173.68 0.673 0.365 Multistage 1° was 0.000 selected on the basis of lowest AIC. One 0.906 0.037, -0.096, and 171.69 0.614 0.364 0.057 a Selected model in bold. b No available degrees of freedom to calculate a goodness of fit value.

Data from NTP1995 6 Multistage Cancer Model with 0.95 Confidence Level

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9 Figure C-17. Plot of incidence by dose, with fitted curve for Multistage 1° 10 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 11 tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, 12 mg/hr) dose units and excluding high-dose group (NTP, 1995); BMR = 10% 13 extra risk; dose shown in mg/hr. 14

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1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 2 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 3 beta1*dose^1-beta2*dose^2...)] 4 The parameter betas are restricted to be positive 5 6 Benchmark Dose Computation. 7 BMR = 10% Extra risk 8 BMD = 0.613798 9 BMDL at the 95% confidence level = 0.364494 10 BMDU at the 95% confidence level = 1.77845 11 Taken together, (0.364494, 1.77845) is a 90% two-sided confidence interval for the BMD 12 Multistage Cancer Slope Factor = 0.274353 13 14 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.158068 0.156284 Beta(1) 0.171653 0.174305 15 16 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -83.8395 3 Fitted model -83.8465 2 0.0138544 1 0.9063 Reduced -86.9873 1 6.29546 2 0.04295 model 17 18 AIC: = 171.693 19 20 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.1581 7.903 8 50 0.037 0.7992 0.266 13.3 13 50 -0.096 1.7462 0.3761 18.806 19 50 0.057 21 22 Chi^2 = 0.01 d.f = 1 P-value = 0.9064 23

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1 Table C-20. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with administered dose units and including all dose groups; 4 reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

5 a Model Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct Basis for model (mg/kg-d) selection p- Scaled residuals AIC value Three 0.0117 -1.476, 1.100, 1.855, 218.68 184 94.8 No model fit the Two and -1.435 data. One a No model was selected as a best-fitting model.

6 Table C-21. Summary of BMD modeling results for renal tubule adenoma or 7 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 8 years modeled with administered dose units and excluding high-dose group; 9 re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

10 a Model Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct Basis for model (mg/kg-d) selection p- Scaled residuals AIC value Two 0.572 -0.141, 0.461, and ­ 154.84 54.2 36.3 Multistage 1° was One 0.296 selected as the most parsimonious model of adequate fit. a Selected model in bold.

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Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation 0.5

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0 BMDL BMD 0 50 100 150 200 dose 1 11:05 04/30 2014 2

3 Figure C-18. Plot of incidence by dose, with fitted curve for Multistage 1° 4 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 5 tert-butanol in drinking water for 2 years modeled with administered dose 6 units and excluding high-dose group; re-analyzed data (Hard et al., 2011; NTP, 7 1995); BMR = 10% extra risk; dose shown in mg/kg-d. 8 9 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 10 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 11 beta1*dose^1-beta2*dose^2...)] 12 The parameter betas are restricted to be positive 13 14 Benchmark Dose Computation. 15 BMR = 10% Extra risk 16 BMD = 54.1642 17 BMDL at the 95% confidence level = 36.3321 18 BMDU at the 95% confidence level = 101.125 19 Taken together, (36.3321, 101.125) is a 90% two-sided confidence interval for the BMD 20 Multistage Cancer Slope Factor = 0.00275239 21 22 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.0855815 0.0981146 Beta(1) 0.00194521 0.00179645 23 24 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -75.2622 3

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Fitted model -75.4201 2 0.315716 1 0.5742 Reduced -81.4909 1 12.4574 2 0.001972 model 1 2 AIC: = 154.84 3 4 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.0856 4.279 4 50 -0.141 90 0.2324 11.622 13 50 0.461 200 0.3803 19.015 18 50 -0.296 5 6 Chi^2 = 0.32 d.f = 1 P-value = 0.5715 7 8

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1 Table C-22. Summary of BMD modeling results for renal tubule adenoma or 2 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 3 years modeled with PBPK (tert-butanol, mg/L) dose units and including all 4 dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 5 risk.

a Model Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model selection p- Scaled residuals AIC value Three 0.0048 -2.089, 0.864, 2.165, 220.82 31.4 11.7 No model fit the Two and -0.929 data. One a No model was selected as a best-fitting model.

6 Table C-23. Summary of BMD modeling results for renal tubule adenoma or 7 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 8 years modeled with PBPK (tert-butanol, mg/L) dose units and excluding high­ 9 dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 10 risk.

a Model Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model selection p- Scaled residuals AIC value Two 0.364 -0.285, 0.750, and ­ 155.33 3.35 2.21 Multistage 1° was One 0.424 selected as the most parsimonious model of adequate fit. a Selected model in bold.

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Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation 0.5

0.4

0.3

Fraction Affected 0.2

0.1

0 BMDL BMD 0 2 4 6 8 10 12 dose 1 11:30 04/30 2014 2

3 Figure C-19. Plot of incidence by dose, with fitted curve for Multistage 1° 4 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 5 tert-butanol in drinking water for 2 years modeled with PBPK (tert-butanol, 6 mg/L) dose units and excluding high-dose group; reanalyzed data (Hard et al., 7 2011; NTP, 1995); BMR = 10% extra risk; dose shown in mg/L. 8 9 10 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 11 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 12 beta1*dose^1-beta2*dose^2...)] 13 The parameter betas are restricted to be positive 14 15 Benchmark Dose Computation. 16 BMR = 10% Extra risk 17 BMD = 3.34903 18 BMDL at the 95% confidence level = 2.20865 19 BMDU at the 95% confidence level = 6.49702 20 Taken together, (2.20865, 6.49702) is a 90% two-sided confidence interval for the BMD 21 Multistage Cancer Slope Factor = 0.0452765 22 23 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.0916116 0.110649 Beta(1) 0.03146 0.0276674 24 25 Analysis of Deviance Table Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -75.2622 3

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Fitted model -75.664 2 0.803466 1 0.3701 Reduced -81.4909 1 12.4574 2 0.001972 model 1 2 AIC: = 155.328 3 4 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.0916 4.581 4 50 -0.285 4.6945 0.2163 10.817 13 50 0.75 12.6177 0.3892 19.462 18 50 -0.424 5 6 Chi^2 = 0.82 d.f = 1 P-value = 0.3643 7

8

9 Table C-24. Summary of BMD modeling results for renal tubule adenoma or 10 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 11 years modeled with PBPK (metabolized, mg/hr) dose units and including all 12 dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 13 risk.

a Model Goodness of fit BMD10Pct (mg/hr) BMDL10Pct (mg/hr) Basis for model selection p- Scaled residuals AIC value Three 0.0142 -1.367, 1.119, 1.783, 218.26 1.44 0.770 No model fit the Two and -1.484 data. One a No model was selected as a best-fitting model.

14 Table C-25. Summary of BMD modeling results for renal tubule adenoma or 15 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 16 years modeled with PBPK (metabolized, mg/hr) dose units and excluding 17 high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% 18 extra risk.

a Model Goodness of fit BMD10Pct (mg/hr) BMDL10Pct Basis for model (mg/hr) selection p-value Scaled residuals AIC Two 0.593 -0.130, 0.435, and ­ 154.81 0.474 0.319 Multistage 1° was One 0.281 selected as the most parsimonious model of adequate fit.

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a Selected model in bold.

1 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation 0.5

0.4

0.3

Fraction Affected 0.2

0.1

0 BMDL BMD 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 dose 2 11:33 04/30 2014 3

4 Figure C-20. Plot of incidence by dose, with fitted curve for Multistage 1° 5 model for renal tubule adenoma or carcinoma in male F344 rats exposed to 6 tert-butanol in drinking water for 2 years modeled with PBPK (metabolized, 7 mg/hr) dose units and excluding high-dose group; reanalyzed data (Hard et 8 al., 2011; NTP, 1995); BMR = 10% extra risk.; dose shown in mg/hr. 9 10 11 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 12 The form of the probability function is: P[response] = background + (1-background)*[1-EXP(­ 13 beta1*dose^1-beta2*dose^2...)] 14 The parameter betas are restricted to be positive 15 16 Benchmark Dose Computation. 17 BMR = 10% Extra risk 18 BMD = 0.474241 19 BMDL at the 95% confidence level = 0.318504 20 BMDU at the 95% confidence level = 0.882859 21 Taken together, (0.318504, 0.882859) is a 90% two-sided confidence interval for the BMD 22 Multistage Cancer Slope Factor = 0.313968 23 24 Parameter Estimates Variable Estimate Default Initial Parameter Values Background 0.0851364 0.0969736 Beta(1) 0.222167 0.206161 25 26 Analysis of Deviance Table

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Model Log(likelihood) # Param's Deviance Test d.f. p-value Full model -75.2622 3 Fitted model -75.4029 2 0.281435 1 0.5958 Reduced model -81.4909 1 12.4574 2 0.001972 1 2 AIC: = 154.806 3 4 Goodness of Fit Table Dose Est. Prob. Expected Observed Size Scaled Resid 0 0.0851 4.257 4 50 -0.13 0.7992 0.234 11.699 13 50 0.435 1.7462 0.3793 18.966 18 50 -0.281 5 6 Chi^2 = 0.29 d.f = 1 P-value = 0.5933 7 8

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1 C.1.2.4. Inhalation Unit Risk for Cancer

2 An inhalation unit risk was not derived because the relative contribution of the α2u-globulin 3 and other, unknown, processes to renal tumor formation cannot be determined (U.S. EPA, 1991), 4 and therefore the male rat renal tumors are not considered suitable for quantitative analysis. 5 However, if renal tumors are considered suitable for analysis then route-to-route extrapolation 6 could be performed.

7 Dose Response Analysis – Adjustments and Extrapolation Methods 8 A PBPK model for tert-butanol in rats has been developed, as described in Appendix B. 9 Using this model, route-to-route extrapolation of the oral BMDL to derive an inhalation POD was 10 performed as follows. First, the internal dose in the rat at the oral BMDL (assuming continuous 11 exposure) was estimated using the PBPK model, to derive an “internal dose BMDL.” Then, the 12 inhalation air concentration (again assuming continuous exposure) that led to the same internal 13 dose in the rat was estimated using the PBPK model, resulting in a route-to-route extrapolated 14 BMCL. 15 A critical decision in the route-to-route extrapolation is the selection of the internal dose 16 metric to use that established "equivalent” oral and inhalation exposures. For tert-butanol-induced 17 kidney effects, the two options are the concentration of tert-butanol in blood and rate of tert­ 18 butanol metabolism. Note that using the kidney concentration of tert-butanol will lead to the same 19 route -to-route extrapolation relationship as tert-butanol in blood, since the distribution from blood 20 to kidney is independent of route. There are no data that suggest metabolites of tert-butanol 21 mediate its renal toxicity. In the absence of evidence that would suggest otherwise, it is assumed 22 that tert-butanol itself is the active toxicological agent. Therefore, the concentration of tert-butanol 23 in blood was selected as the dose metric to derive the BMCL. 24 The RfC methodology provides a mechanism for deriving a HEC from the BMCL determined 25 from the animal data. The approach takes into account the extra-respiratory nature of the 26 toxicological responses and accommodates species differences by considering blood:air partition 27 coefficients for tert-butanol in the laboratory animal (rat or mouse) and humans. According to the 28 RfC guidelines (U.S. EPA, 1994), tert-butanol is a Category 3 gas because extra-respiratory effects 29 were observed. Kaneko et al. (2000) measured a blood:gas partition coefficient of 531 ± 102 for 30 tert-butanol in the male Wistar rat, while Borghoff et al. (1996) measured a value of 481 ± 29 in 31 male F344 rats. A blood:gas partition coefficient of 462 was reported for tert-butanol in humans

32 (Nihlén et al., 1995). The calculation (Hb/g )A ÷ (Hb/g )H was used to calculate a blood:gas partition 33 coefficient ratio to apply to the delivered concentration. Because F344 rats were used in the study, 34 the blood:gas partition coefficient for F344 rats was used. Thus, the calculation was: 481 ÷ 462 =

35 1.04. Therefore, a ratio of 1.04 was used to calculate the HEC. This allowed a BMCLHEC to be derived 36 as follows: 37

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1 BMCLHEC = BMCLADJ (mg/m3) × (interspecies conversion) 2 = BMCLADJ (mg/m3) × (481 ÷ 462) 3 = BMCLADJ (mg/m3) × (1.04)

4 5 The U.S. EPA Guidelines for Carcinogen Risk Assessment (U.S. EPA, 2005) recommend that the 6 method used to characterize and quantify cancer risk from a chemical is determined by what is 7 known about the MOA of the carcinogen and the shape of the cancer dose-response curve. The 8 linear approach is recommended if the MOA of carcinogenicity has not been established (U.S. EPA, 9 2005 ). In the case of tert-butanol, the mode of carcinogenic action for renal tubule tumors is not 10 fully understood (see Section 1.2.1). Therefore, a linear low-dose extrapolation approach was used 11 to estimate human carcinogenic risk associated with tert-butanol exposure.

12 Inhalation Unit Risk Derivation 13 The results from route-to-route extrapolation of the male rat renal tubule tumor data are 14 summarized in Table C-26. The lifetime inhalation unit risk for humans is defined as the slope of 15 the line from the lower 95% bound on the exposure at the POD to the control response (inhalation

16 unit risk = 0.1/BMCL10). This slope, a 95% upper confidence limit represents a plausible upper

17 bound on the true risk. Using linear extrapolation from the BMCL10, a human equivalent inhalation 18 unit risk was derived, as listed in Table C-26. 19 Two inhalation unit risks were derived from the NTP (1995) bioassay: one based on the 20 original reported incidences and one based on the Hard et al. (2011) reanalysis. The two estimates 21 differ by less than 20%, but the Hard et al. (2011) reanalysis is considered preferable, as it is based 22 on a PWG analysis. Therefore, the recommended inhalation unit risk for providing a sense of the 23 magnitude of potential carcinogenic risk associated with lifetime inhalation exposure to 24 tert -butanol is 1 × 10-3 per mg/m3, or 2 × 10-3 per µg/m3, based on the renal tubule tumor 25 response in male F344 rats.

26 Table C-26. Summary of the inhalation unit risk derivation

POD= a b c BMDL Internal Dose BMCLHEC Unit Risk 3 3 -1 Tumor Species/Sex BMR (mg/kg-d) (mg/L) (mg/m ) (mg/m ) Renal tubule adenoma or Male F344 10% 41.6 2.01 68.7 1 × 10-3 carcinoma rat Renal tubule adenoma or Male F344 10% 36.3 1.74 59.8 2 × 10-3 carcinoma [Hard et al. rat (2011) reanalysis] 27 28 a Average blood concentration of tert-butanol under continuous oral exposure at the BMDL. 29 b Continuous inhalation human equivalent concentration that leads to the same average blood concentration of 30 tert -butanol as continuous oral exposure at the BMDL. c 31 Human equivalent inhalation unit risk = 0.1/BMCLHEC .

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1 REFERENCES

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