Toxicological Review of Tert-Butyl Alcohol (Tert-Butanol)

EPA/635/R-17/015b External Review Draft www.epa.gov/iris

Toxicological Review of tert-Butyl Alcohol (tert-Butanol)

(CASRN 75-65-0)

Supplemental Information

June 2017

NOTICE

This document is an External Review 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

1 DISCLAIMER

2 This document is a preliminary draft for review purposes only. This information is 3 distributed solely for the purpose of pre-dissemination peer review under applicable information 4 quality guidelines. It has not been formally disseminated by EPA. It does not represent and should 5 not be construed to represent any Agency determination or policy. Mention of trade names or 6 commercial products does not constitute endorsement or recommendation for use.

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1 2 CONTENTS

3 APPENDIX A. ASSESSMENTS BY OTHER NATIONAL AND INTERNATIONAL HEALTH AGENCIES ...... A-1 4 APPENDIX B. INFORMATION IN SUPPORT OF HAZARD IDENTIFICATION AND DOSE-RESPONSE 5 ANALYSIS ...... B-1 6 B.1. TOXICOKINETICS ...... B-1 7 Absorption...... B-1 8 Distribution ...... B-2 9 Metabolism ...... B-2 10 Excretion ...... B-5 11 Physiologically Based Pharmacokinetic Models ...... B-7 12 PBPK Model Code ...... B-8 13 B.2. OTHER PERTINENT TOXICITY INFORMATION ...... B-9 14 Other Toxicological Effects ...... B-9 15 Genotoxicity ...... B-22 16 Summary ...... B-26 17 APPENDIX C. DOSE-RESPONSE MODELING FOR THE DERIVATION OF REFERENCE VALUES FOR 18 EFFECTS OTHER THAN CANCER AND THE DERIVATION OF CANCER RISK 19 ESTIMATES ...... C-1 20 Noncancer Endpoints ...... C-1 21 Cancer Endpoints ...... C-23 22 APPENDIX D. SUMMARY OF PUBLIC COMMENTS AND EPA’s DISPOSITION ...... D-1 23 REFERENCES ...... R-1

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1 TABLES

2 Table A-1. Health assessments and regulatory limits by other national and international 3 health agencies ...... A-1 4 Table B-1. Changes in kidney weight in animals following exposure to tert-butanol ...... B-11 5 Table B-2. Changes in liver weight in animals following exposure to tert-butanol ...... B-14 6 Table B-3. Changes in liver histopathology in animals following exposure to tert-butanol ...... B-16 7 Table B-4. Changes in urinary bladder histopathology in animals following oral exposure to 8 tert -butanol ...... B-18 9 Table B-5. Summary of genotoxicity (both in vitro and in vivo) studies of tert-butanol ...... B-25 10 Table C-1. Noncancer endpoints selected for dose-response modeling for tert-butanol ...... C-2 11 Table C-2. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in 12 male F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 13 1995) ; BMR = 10% extra risk ...... C-3 14 Table C-3. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in 15 female F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 16 1995); BMR = 10% extra risk ...... C-6 17 Table C-4. Summary of BMD modeling results for absolute kidney weight in male F344 rats 18 exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 19 10% rel. dev. from control mean ...... C-9 20 Table C-5. Summary of BMD modeling results for absolute kidney weight in female F344 rats 21 expo sed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 22 10% rel. dev. from control mean ...... C-12 23 Table C-6. Summary of BMD modeling results for kidney inflammation in female rats 24 exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% 25 extra risk ...... C-15 26 Table C-7. Summary of BMD modeling results for absolute kidney weight in male F344 rats 27 exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 28 1997); BMR = 10% relative deviation from the mean ...... C-18 29 Table C-8. Summary of BMD modeling results for absolute kidney weight in female F344 rats 30 exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 31 1997); BMR = 10% relative deviation from the mean ...... C-21 32 Table C-9. Cancer endpoints selected for dose-response modeling for tert-butanol ...... C-24 33 Table C-10. Summary of the oral slope factor derivations ...... C-25 34 Table C-11. Summary of BMD modeling results for thyroid follicular cell adenomas in female 35 B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); 36 BMR = 10% extra risk ...... C-26 37 Table C-12. Summary of BMD modeling results for thyroid follicular cell adenomas or 38 carcinomas in male B6C3F1 mice exposed to tert-butanol in drinking water for 39 2 years (NTP, 1995); BMR = 5% extra risk ...... C-29 40 Table C-13. Summary of BMD modeling results for thyroid follicular cell adenomas or 41 carcinomas in male B6C3F1 mice exposed to tert-butanol in drinking water for 42 2 years, high dose omitted (NTP, 1995); BMR = 5% extra risk ...... C-32 43 Table C-14. Summary of BMD modeling results for renal tubule adenoma or carcinoma in 44 male F344 rats exposed to tert-butanol in drinking water for 2 years modeled 45 with administered dose units and including all dose groups (NTP, 1995); BMR 46 = 10% extra risk ...... C-35

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1 Table C-15. Summary of BMD modeling results for renal tubule adenoma or carcinoma in 2 male F344 rats exposed to tert-butanol in drinking water for 2 years modeled 3 with administered dose units and excluding high-dose group (NTP, 1995); BMR 4 = 10% extra risk...... C-37 5 Table C-16. Summary of BMD modeling results for renal tubule adenoma or carcinoma in 6 male F344 rats exposed to tert-butanol in drinking water for 2 years modeled 7 with administered dose units and including all dose groups; reanalyzed data 8 (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk ...... C-39 9 Table C-17. Summary of BMD modeling results for renal tubule adenoma or carcinoma in 10 male F344 rats exposed to tert-butanol in drinking water for 2 years modeled 11 with administered dose units and excluding high-dose group; re-analyzed data 12 (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk ...... C-39

13 FIGURES

14 Figure B-1. Biotransformation of tert-butanol in rats and humans...... B-4 15 Figure B-2. Example oral ingestion pattern for rats exposed via drinking water...... B-8 16 Figure B-3. Exposure-response array of other effects following oral exposure to tert-butanol...... B-20 17 Figure B-4. Exposure-response array of other effects following inhalation exposure to tert- 18 butanol...... B-21 19 Figure C-1. Plot of incidence by dose, with fitted curve for LogLogistic model for kidney 20 transitional epithelial hyperplasia in male F344 rats exposed to tert-butanol in 21 drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in 22 mg/g k -d...... C-4 23 Figure C-2. Plot of incidence by dose, with fitted curve for Multistage 3° model for kidney 24 transitional epithelial hyperplasia in female F344 rats exposed to tert-butanol 25 in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in 26 .mg/kg-d ...... C-6 27 Figure C-3. Plot of mean response by dose, with fitted curve for Linear model with constant 28 variance for absolute kidney weight in male F344 rats exposed to tert-butanol 29 in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control 30 mean; dose shown in mg/kg-d...... C-10 31 Figure C-4. Plot of mean response by dose, with fitted curve for Exponential (M4) model 32 with constant variance for absolute kidney weight in female F344 rats exposed 33 to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel. 34 dev. from control mean; dose shown in mg/kg-d...... C-13 35 Figure C-5. Plot of incidence by dose, with fitted curve for LogpPobit model for kidney 36 inflammation in female rats exposed to tert-butanol in drinking water for 2 37 years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d...... C-15 38 Figure C-6. Plot of mean response by concentration, with fitted curve for Hill model for 39 absolute kidney weight in male F344 rats exposed to tert-butanol via inhalation 40 for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative deviation from 41 the mean; concentration shown in mg/m3...... C-19 42 Figure C-7. Plot of mean response by concentration, with fitted curve for Hill model for 43 absolute kidney weight in female F344 rats exposed to tert-butanol via

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1 inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative 2 deviation from the mean; concentration shown in mg/m3...... C-22 3 Figure C-8. Plot of mean response by concentration, with fitted curve for Power model for 4 absolute kidney weight in female F344 rats exposed to tert-butanol via 5 inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative 6 deviation from the mean; concentration shown in mg/m3...... C-22 7 Figure C-9. Plot of incidence by dose, with fitted curve for Multistage 3° model for thyroid 8 follicular cell adenomas in female B6C3F1 mice exposed to tert-butanol in 9 drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in 10 mg/kg. -d ...... C-26 11 Figure C-10. Plot of incidence by dose, with fitted curve for Multistage 1° model for thyroid 12 follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert- 13 butanol in drinking water for 2 years (NTP, 1995); BMR = 5% extra risk; dose 14 shown in mg/kg-d...... C-29 15 Figure C-11. Plot of incidence by dose, with fitted curve for Multistage 2° model for thyroid 16 follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to tert- 17 butanl o in drinking water for 2 years, high dose omitted (NTP, 1995); BMR = 5% 18 extra risk; dose shown in mg/kg-d...... C-32 19 Figure C-12. Plot of incidence by dose, with fitted curve for Multistage 2° model for renal 20 tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in 21 drinking water for 2 years modeled with administered dose units and including 22 all dose groups (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d...... C-35 23 Figure C-13. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal 24 tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in 25 drinking water for 2 years modeled with administered dose units and excluding 26 high-dose group (NTP, 1995); BMR = 10% extra risk.; dose shown in mg/kg-d...... C-37 27 Figure C-14. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal 28 tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in 29 drinking water for 2 years modeled with administered dose units and excluding 30 high -dose group; re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% 31 extra risk; dose shown in mg/kg-d...... C-40 32

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1 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 2 APPENDIX A. ASSESSMENTS BY OTHER NATIONAL 3 AND INTERNATIONAL HEALTH AGENCIES

4 Table A-1. Health assessments and regulatory limits by other national and 5 i nternational 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 workweek. 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). 6

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1 2 APPENDIX B. INFORMATION IN SUPPORT OF 3 HAZARD IDENTIFICATION AND DOSE-RESPONSE 4 ANALYSIS

5 B.1. TOXICOKINETICS 6 Little information is available on the absorption, distribution, metabolism, or excretion of 7 tert-butyl alcohol (tert-butanol) in humans. The studies identified for this Toxicological Assessment 8 were conducted in conjunction with methyl tert-butyl ether (MTBE) or ethyl tert-butyl ether 9 (ETBE), as tert-butanol is a metabolite of both compounds. Several studies examining some aspect 10 of the toxicokinetic behavior of tert-butanol in animals have been identified. Many were carried out 11 in conjunction with other specific endpoints (e.g., developmental). ARCO (1983) determined no 12 differences in the pharmacokinetics of tert-butanol following either oral (i.e., gavage) or inhalation 13 exposure. Although some information is available for both oral and inhalation exposures, many 14 studies administered tert-butanol via intraperitoneal (i.p.) or intravenous (i.v.) injection. Although 15 these studies do not inform the absorption of tert-butanol, they can provide information on its 16 distribution, metabolism, and excretion.

17 Absorption 18 Toxicity data on tert-butanol submitted by industry to the U.S. Environmental Protection 19 Agency (EPA) under Section 8(e) of the Toxic Substances Control Act and other reporting 20 requirements indicate that tert-butanol is rapidly absorbed after oral administration. Very little of 21 the administered dose was excreted in the feces of rats, indicating 99% of the compound was 22 absorbed. Comparable blood levels of tert-butanol and its metabolites have been observed after 23 acute oral (350 mg/kg) or inhalation (6,060 mg/m3 for 6 hours) exposure in male Sprague-Dawley 24 rats (ARCO, 1983); the absorption rate after inhalation exposure could not be determined, however, 25 because the blood was saturated with radioactivity after 6 hours of exposure to 6,060 mg/m3. In 26 another study (Faulkner et al., 1989), blood concentrations indicated that absorption was complete 27 at 1.5 hours following the last of six oral gavage doses of 10.5 mmoles tert-butanol/kg (twice daily) 28 in female C57BL/6J mice. There was an apparent zero-order decline in tert-butanol concentration 29 for most of the elimination phase, and no differences in absorption or elimination rates were 30 observed between mice on a repeated dosing regimen and mice administered equivalent volumes 31 of tap water every 12 hours before administration of a single dose of 10.5 mmoles tert-butanol/kg. 32 The study therefore concluded that previous exposures did not affect the absorption or elimination 33 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, 1983). 4 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 had a partition coefficient of 0.646. The same 8 study evaluated the partition coefficients of three oxygenated ethers, including MTBE and ETBE, 9 which are metabolized to tert-butanol (see Section B.1.4). The study concluded that, although tert- 10 butanol preferentially distributes in body water, the ethers distribute uniformly throughout the 11 body with a preference for 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 and evaluated tissue levels at 12 hours. They found the radiolabel in three α 15 tissues (kidney, liver, and blood) in both sexes, but male rats retained more of the tert-butanol 16 equivalents than females (Williams and Borghoff, 2001). Radioactivity was found in the low- 17 molecular-weight protein fraction isolated from the kidney cytosol in male rats but not in female

18 rats, indicating that tert-butanol or one of its metabolites was bound to 2u-globulin. Further 19 analysis determined that tert-butanol, and not its metabolite acetone, was bound. Most tert-butanol α 20 in the kidney cytosol was eluted as the free compound in both males and females, but a small 21 amount was associated with the high-molecular-weight protein fraction in both males and females.

22 In another study on 2u-globulin nephropathy, Borghoff et al. (2001) found similar results after F- 23 344 rats were exposed to 0, 250, 450, or 1750 ppm tert-butanol by inhalation for 8 consecutive α 24 days (with tissue levels measured at 2, 4, 6, 8, and 16 hours postexposure). Male rat tert-butanol 25 kidney-to-blood ratios were significantly elevated over ratios in females at all dose levels and 26 exposure durations. Although the female tert-butanol kidney-to-blood ratio remained similar with 27 both duration and concentration, the male tert-butanol kidney-to-blood ratio increased with 28 duration. The liver-to-blood ratios were similar regardless of exposure duration, concentration, or 29 sex. Both of these studies indicate distribution of tert-butanol to the liver and kidney with kidney 30 retention of tert-butanol in the male rat.

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

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1 identified as major metabolites in rats, while acetone, tert-butanol, and tert-butanol glucuronides 2 were identified as minor metabolites (Bernauer et al., 1998). Baker et al. (1982) found that tert- 3 butanol was a source of acetone, but acetone production might have been stimulated from other 4 sources. 5 No studies identified specific enzymes responsible for biotransforming tert-butanol. Using a 6 purified enzyme from Sprague-Dawley rats or whole-liver cytosol from Wistar rats, alcohol 7 dehydrogenase had negligible or no activity toward tert-butanol (Videla et al., 1982; Arslanian et al., 8 1971). Other in vitro studies have implicated the liver microsomal mixed function oxidase (MFO) 9 system, namely cytochrome P450 (CYP450) (Cederbaum et al., 1983; Cederbaum and Cohen, 1980). 10 In the 1983 study, incubation of tert-butanol at 35 mM with Sprague-Dawley rat liver microsomes 11 and a nicotinamide adenine dinucleotide phosphate (NADPH)-generating system resulted in 12 formaldehyde production at a rate of approximately 25 nmoles/mg protein/30 min. According to 13 study authors, the amount of formaldehyde generated by tert-butanol was approximately 30% of 14 the amount of formaldehyde formed during the metabolism of 10 mM aminopyrene in a similar 15 microsomal system. The rate of formaldehyde generation from tert-butanol increased to about 16 90 nmol/mg protein/30 min upon addition of azide, which inhibits catalase and thereby prevents

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

18 formaldehyde formation was greatly reduced when H2O2 was included but NADPH was absent or 19 when the microsomes were boiled prior to incubation. Additionally, the rate of formaldehyde 20 formation in the microsomal oxidizing system depended on the concentration of tert-butanol, with

21 apparent Km and Vmax values of 30 mM and 5.5 nmol/min/mg protein, respectively. The study 22 authors concluded that tert-butanol is metabolized to formaldehyde by a mechanism involving 23 oxidation of NADPH, microsomal electron flow, and the generation of hydroxyl-radical (·OH) from

24 H2O2, possibly by a Fenton-type or a Haber-Weiss iron-catalyzed reaction involving CYP450, which 25 might serve as the iron chelate (Cederbaum and Cohen, 1980).

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CH3

glucuronide–O CH3

CH3 OOH t-butyl glucuronide OH CH3 rats, humans [O] CH3

CH3 OH 2-hydroxyisobutyric acid CYP450 O OH CH3 CH 3 CH OH rats, 3 2CH O CH3 humans OH CH3 CH3 t-butanol formaldehyde 2-methyl-1,2-propanediol O rats

- O CH CH O 3 3 S CH3 acetone O O CH3

CH3 2 t-butyl sulfate

3 Sources: NSF International (2003), ATSDR (1996), Bernauer et al. (1998), Amberg et al. (1999), and 4 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 [ethylenediaminetetraacetic 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 (O2· ). 14 Further experiments demonstrated the involvement of ·OH in either the ascorbate-Fe-EDTA or the− 15 xanthine oxidation systems based on inhibition of formaldehyde and acetone production from tert- 16 butanol when ·OH-scavenging agents (e.g., benzoate, mannitol) were added. Some experiments in 17 this study of the oxidation of tert-butanol by the microsomal metabolizing system of the liver were 18 similar to those in the previous study (Cederbaum and Cohen, 1980) except that, in addition to 19 formaldehyde, acetone formation was measured. Again, these experiments showed the dependence

20 of the microsomal metabolizing system on an NADPH-generating system and the ability of H2O2 to 21 enhance, but not replace, the NADPH-generating system. Addition of chelated iron (Fe-EDTA)

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

9 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; 1998b). Eight or 10 male human volunteers were exposed to 5, 25, or 50 ppm 19 MTBE (18.0, 90.1, and 757 mg/m3) or ETBE (20.9, 104, and 210 mg/m3) by inhalation during 2 20 hours of light exercise. The half-life of tert-butanol in urine following MTBE exposure was 8.1 ± 2.0 21 hours (average of the 25- and 50-ppm MTBE doses); the half-life of tert-butanol in urine following 22 ETBE exposure was 7.9 ± 2.7 hours (average of 25- and 50-ppm ETBE doses). In both studies, the 23 urinary excretion of tert-butanol was less than 1% of the uptake or absorption of MTBE or ETBE. 24 The renal clearance rate of tert-butanol was 0.67 ± 0.11 mL/hr-kg with MTBE exposure (average of 25 25- and 50-ppm MTBE doses); the renal clearance rate was 0.80 ± 0.34 mL/hr-kg with ETBE 26 exposure (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 f72 hours ollowing exposure. tert-Butanol and two metabolites of tert-butanol, HBA and MPD, also 31 were identified in urine. At an ETBE level of 170 mg/m3, tert-butanol displayed a half-life of 32 9.8 ± 1.4 hours. At the low-exposure ETBE concentration, the tert-butanol half-life was 8.2 ± 33 2.2 hours. The predominant urinary metabolite identified was HBA, excreted in urine at 5–10 times 34 the amount of MPD and 12–18 times the amount of tert-butanol (note: urine samples had been 35 treated with acid before analysis to cleave conjugates). HBA in urine showed a broad maximum at 36 012 –3 hours after exposure to both concentrations, with a slow decline thereafter. MPD in urine

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1 peaked at 12 and 18 hours after exposure to 170 and 18.8 mg/m3 ETBE, respectively, while tert- 2 butanol peaked at 6 hours after exposure to both concentrations. 3 Amberg et al. (2000) exposed F344 NH rats to 18.8 and 170 mg/m3 ETBE. Urine was 4 collected for 72 hours following exposure. Similar to humans, rats excreted mostly HBA in urine, 5 followed by MPD and tert-butanol. The half-life for tert-butanol in rat urine was 4.6 ± 1.4 hours at 6 ETBE levels of 170 mg/m3, but half-life could not be calculated at the ETBE concentration of 7 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 8 4.7 ± 2.6 hours for HBA. In Sprague-Dawley rats treated with radiolabeled tert-butanol by gavage at 9 1, 30, or 500 mg/kg, a generally constant fraction of the administered radioactivity (23–33%) was 10 recovered in the urine at 24 hours postdosing. Only 9% of a 1500-mg/kg administered dose was 11 recover ed in urine, however, suggesting that the urinary route of elimination is saturated following 12 this dose (ARCO, 1983). Among all tested doses, most of the urinary radiolabel was attributed to a 13 polar fraction that was not characterized, while only 0.3–5.5% of the administered dose was 14 considered tert-butanol. The saturation in urinary elimination of radioactivity with the increased 15 dose was considered a manifestation of saturated metabolic capacity; however, no further 16 information was provided on the fate or balance of the administered radiolabel at any of the tested 17 tert -butanol doses (ARCO, 1983). 18 Borghoff and Asgharian (1996) evaluated the disposition of 14C radiolabel in F344 rats and 19 CD-1 mice after nose-only inhalation exposure to 500, 1750, or 5,000 ppm 14C-ETBE for six hours. 20 Besides recovery of total radioactivity in urine, feces, and expired air, air and urine samples were 21 analyzed for ETBE and tert-butanol. Urine samples were also analyzed for tert-butanol metabolites

22 HBA and MPD, and 14CO2 was measured in exhaled air. Results were also obtained in rats after 13 23 days of exposure to 500 or 5,000 ppm ETBE. Total ETBE equivalents in exhaled air and excreted 24 urine were found to increase linearly with exposure level, with over 90% eliminated by 48 hours 25 (with the majority of exhalation occurring by 8 hours postexposure). Elimination shifted from being 26 primarily in the urine at 500 ppm to occurring primarily by exhalation at 5,000 ppm in naïve rats, 27 indicating a saturation of metabolism of ETBE to tert-butanol; this shift was greater in female 28 rats than males. In rats pre-exposed to 5,000 ppm ETBE for 13 days, most of the excretion was in 29 urine even at 5,000 ppm. For rats pre-exposed to 500 ppm ETBE, there also was a shift from 30 exhalation to urinary excretion compared with naïve rats, but to a lesser degree than that elicited 31 by the 5,000-ppm pre-exposure group. 32 Like rats, the fraction of radiolabel in exhaled volatiles increased with exposure level in 33 mice while the fraction excreted in urine decreased. The exhalation pattern observed in rats 34 showed levels of ETBE falling approximately 90% in the first 8 hours postexposure, while levels of 35 TBA exhaled rose between 0 and 3 hours postexposure and then fell more slowly between 3 and 16 36 hsour , particularly at 5,000 ppm ETBE. The increase in tert-butanol between 0 and 3 hours 37 postexposure can be explained by the continued metabolism of ETBE during that period. The

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1 slower decline after 3 hours likely results from a generally slower clearance of tert-butanol, which 2 is saturated by the higher ETBE exposure levels.

3 Physiologically Based Pharmacokinetic Models 4 Three physiologically based pharmacokinetic (PBPK) models have been developed 5 specifically for administration of tert-butanol in rats Leavens and Borghoff (2009); Salazar et al. 6 (2015), and Borghoff et al. (2016); other models have incorporated tert-butanol as a submodel 7 following MTBE administration. In Leavens and Borghoff (2009), tert-butanol is incorporated as a 8 metabolite of MTBE; in Salazar et al. (2015) and Borghoff et al. (2016), it is incorporated as a 9 metabolite of ETBE. In all three models, inhalation and oral exposure to tert-butanol can be 10 simulated in rats. A detailed summary of these toxicokinetic models is provided in a separate report 11 evaluating the PK/PBPK modeling of ETBE and tert-butanol (U.S. EPA, 2017). 12 The PBPK model described in Borghoff et al. (2016), with parameters modified as described 13 by U.S. EPA (2017), was applied to conduct oral-to-inhalation route extrapolation based on an 14 equivalent internal dose (the average concentration of tert-butanol in the blood). The time to reach 15 a consistent periodic pattern of tert-butanol blood concentrations (“periodicity”), given the 16 drinking water ingestion pattern described below, was much shorter than the duration of the oral 17 bioassay studies. To allow for possible metabolic induction, computational scripts used a simulated 18 time of 7 weeks, although periodicity was achieved in only a few days without metabolic induction. 19 The average blood concentration was calculated over the last week of the simulation and was 20 considered representative of the bioassays. To calculate steady state values for continuous 21 inhalation exposure, the simulations were run until the blood concentration had a <1% change 22 between consecutive days. The continuous inhalation exposure equivalent to a given oral exposure 23 was then selected by identifying the inhalation concentration for which the final (steady-state) 24 blood concentration of tert-butanol matched the average concentration from water ingestion, as 25 described above. 26 For simulating exposure to drinking water, the consumption was modeled as episodic, 27 based on the pattern of drinking observed in rats (Spiteri, 1982). In particular, rats were assumed 28 to ingest water in pulses or “bouts,” which were treated as continuous ingestion, interspersed with 29 periods of no ingestion. During the active dark period (12 hours/day), it was assumed that 80% of 30 total daily ingestion occurs (45-minute bouts with alternating 45-minute periods of other activity). 31 During the relatively inactive light period (12 hours/day), it was assumed that the remaining 20% 32 of daily ingestion occurs; during this time, bouts were assumed to last 30 minutes with 2.5 hours in 33 between. This resulting pattern of drinking water ingestion is thought to be more realistic than 34 assuming continuous 24 hours/day ingestion (see Figure B-2). 35

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2 Figure B-2. Example oral ingestion pattern for rats exposed via drinking 3 water. 4 5 PBPK modeling was also used to evaluate a variety of internal dose metrics (daily average 6 TBA blood concentration, daily amount of TBA metabolized in liver, daily average of ETBE blood 7 concentration, and daily amount of ETBE metabolized in liver) to assess their correlation with 8 different endpoints following exposure to ETBE or TBA (Salazar et al., 2015). Administering ETBE 9 either orally or via inhalation achieved similar or higher levels of TBA blood concentrations or TBA 10 metabolic rates as those induced by direct TBA administration. Altogether, the PBPK model-based 11 analysis by Salazar et al. (2015) [which applied a model structurally similar to Borghoff et al. 12 (2016)] indicates that kidney weight, urothelial hyperplasia, and chronic progressive nephropathy 13 (CPN) yield consistent dose-response relationships using TBA blood concentration as the dose 14 metric for both ETBE and TBA studies. For kidney and liver tumors, however, a consistent dose- 15 response pattern was not obtained using any dose metric. These data are consistent with TBA 16 mediating the noncancer kidney effects following ETBE administration, but additional factors 17 besides internal dose are necessary to explain the induction of liver and kidney tumors.

18 PBPK Model Code 19 The PBPK acslX model code is available electronically through EPA’s Health and 20 Environmental Research Online (HERO) database. All model files may be downloaded in a zipped 21 workspace from HERO (U.S. EPA, 2016). 22

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1 B.2. OTHER PERTINENT TOXICITY INFORMATION

2 Other Toxicological Effects 3 B.2.1.1. Synthesis of Other Effects 4 Effects other than those related to kidney, thyroid, reproductive, developmental, and 5 neurodevelopmental effects were observed in some of the available rodent studies. These include 6 liver and urinary bladder effects. As previously mentioned in the Study Selection section of the 7 Toxicological Review, all studies discussed employed inhalation, oral gavage, or drinking water 8 Studies are arranged in evidence tables by effect, species, duration, and 9 design. The design, conduct, and reporting of each study was reviewed, and each study was exposures for ≥30 days. 10 considered adequate to provide information pertinent to this assessment. 11 Central nervous system effects similar to those of ethanol (i.e., animals appearing 12 intoxicated and having withdrawal symptoms after cessation of oral or inhalation exposure) were 13 observed with tert-butanol. Severity of central nervous system symptoms increased with dose and 14 duration of exposure. Study quality and utility concerns associated with these studies (e.g., 15 inappropriate exposure durations, lack of data reporting, small number of animals per treatment 16 group) (Grant and Samson, 1981; Snell, 1980; Thurman et al., 1980; McComb and Goldstein, 1979a, 17 b; Wood and Laverty, 1979), preclude an understanding of potential neurotoxicity following tert- 18 butanol exposure; therefore, central nervous system studies are not discussed further. 19 Exposure-response arrays of liver and urinary bladder effects are provided in Figure B-3 20 and Figure B-4 for oral and inhalation studies, respectively.

21 Kidney effects 22 Absolute and relative kidney weight numerical data are presented in Table B-1.

23 Liver effects 24 Liver weight and body weight were demonstrated to be proportional, and liver weight 25 normalized to body weight was concluded optimal for data analysis (Bailey et al., 2004); thus, only 26 relative liver weight is presented and considered in the determination of hazard. Although some 27 rodent studies observed liver effects (organ weight changes and histopathologic lesions), the effects 28 were not consistent across the database. Increases in relative liver weight with tert-butanol 29 exposure were observed, but the results pertaining to histopathologic changes were inconsistent 30 (Table B-2 and Table B-3). The NTP (1995) oral subchronic and chronic studies did not observe 31 treatment-related effects on liver histopathology in either sex of F344 rats. In a 10-week study in 32 Wistar rats, several liver lesions (including necrosis) and increased liver glycogen were observed in 33 male rats (no females were included in the study) with the only dose used (Acharya et al., 1997; 34 Acharya et al., 1995). The study provided no incidence or severity data. The dose used in this rat 35 study was in the range of the lower doses used in the NTP (1995) subchronic rat study. An 36 increased incidence of fatty liver was observed in the male mice of the highest dose group in the 2-

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1 year mouse bioassay, but no histopathological changes were seen in the subchronic mouse study 2 (NTP, 1995). No treatment-related effects in liver histopathology were observed in rats or mice of 3 the NTP (1997) subchronic inhalation study.

4 Urinary bladder effects 5 Subchronic studies reported effects in the urinary bladder (Table B-4), although the chronic 6 studies indicated little progression in incidence with increased exposure. Transitional epithelial 7 hyperplasia of the urinary bladder was observed in male rats and male mice after 13 weeks of 8 exposure at doses of 3,610 mg/kg- ,940 mg/kg-day (male mice). In rats, the 9 increase in transitional epithelial hyperplasia of the urinary bladder was not observed in the 2-year day (male rats) and ≥3 10 study. Male mice exposed at the high dose (2,070 mg/kg-day) for 2 years exhibited minimal 11 transitional epithelial hyperplasia of the urinary bladder. Neither female rats nor female mice 12 showed increased incidences of this lesion. Both sexes of mice demonstrated incidence of minimal 13 to mild inflammation in the urinary bladder after both subchronic and chronic exposures, with a 14 greater incidence in males compared with females.

15 B.2.1.2. Mechanistic Evidence 16 No mechanistic evidence is available for liver and urinary bladder effects.

17 B.2.1.3. Summary of Other Toxicity Data 18 Based on lack of consistency and lack of progression, the available evidence does not 19 support liver and urinary bladder effects, respectively, as potential human hazards of tert-butanol 20 exposure. 21

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

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1 Table B-2. 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 mating (mg/kg-d) weight weight (mg/kg-d) weight Relative weight Females: 4 weeks prior to mating through PND21 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 Males Females 40 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 - - 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 Males Females 40 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 - - 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*

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NTP (1995) Percent change compared to control: F344/N rat; 60/sex/treatment (10/sex/treatment evaluated at 15 months) Males Females Drinking water (0, 1.25, 2.5, 5 or 10 mg/mL) Dose Absolute Relative Dose Absolute Relative M: 0, 90, 200, or 420a mg/kg-d (mg/kg-d) weight weight (mg/kg-d) weight weight F: 0, 180, 330, or 650a mg/kg-d 2 years 0 - - 0 - -

90 2 7 180 −14* −8

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 - - - - 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 - - - - 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 2 aThe high-dose group had an increase in mortality. 3 * Statistically significant p ≤ 0.05 as determined by study authors. 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. 6 Percentage change compared to control = (treated value – control value) ÷ control value × 100. 7

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1 Table B-3. 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 2 aThe high-dose group had an increase in mortality. 3 * Statistically significant p ≤ 0.05 as determined by study authors. 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 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, Dose epithelial Dose Transitional epithelial 3,610a mg/kg-d (mg/kg-d) hyperplasia (mg/kg-d) hyperplasia F: 0, 290, 590, 850, 1,560, 0 0/10 0 0/10 3,620a 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 2 aThe high-dose group had an increase in mortality. 3 * Statistically significant p ≤ 0.05 as determined by study authors. 4 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-3. 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-4. 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 induction, 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-5.

7 B.2.2.1. 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 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 at 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. 26 Mutagenicity of tert-butanol has been studied in other systems including Neurospora crassa 27 and Saccharomyces cerevisiae. Yeast strain Neurospora crassa at the ad-3A locus (allele 38701) was 28 used to test the mutagenic activity of tert-butanol at a concentration of 1.75 mol/L for 30 minutes. 29 t ert-Butanol did not induce reverse mutations in the tested strain at the exposed concentration 30 (Dickey et al., 1949). tert-Butanol without exogenous metabolic activation, however, significantly 31 increased the frequency of petite mutations (the mitochondrial DNA deletion r ) in 32 Saccharomyces cerevisiae laboratory strains K5-A5, MMY1, D517-4B, and DS8 (Jimenez et al., 1988). ho− 33 This effect on mitochondrial DNA, also observed with ethanol and other solvents, was attributed by 34 the study authors to the alteration in the lipid composition of mitochondrial membranes, and 35 mitochondrial DNA’s close association could be affected by membrane composition (Jimenez et al., 36 1988).

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1 B.2.2.2. In Vitro Mammalian Studies 2 To understand the role of tert-butanol-induced genotoxicity in mammalian systems, in vitro 3 studies have been conducted in different test systems and assays. tert-Butanol was tested to 4 evaluate its ability to induce forward mutations at the thymidine kinase locus (tk) in the L5178Y 5 tk+/ - mouse lymphoma cells using forward mutation assay. Experiments were conducted in both 6 the presence and absence of S9 metabolic activation. The mutant frequency was calculated using 7 the ratio of mutant clones per plate/total clones per plate × 200. tert-Butanol did not reliably 8 9 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 10 (1.7 -fold) increase in mutant fraction at the highest tested concentration (5,000 µg/mL) (McGregor 11 et al., 1988). 12 To further determine potential DNA or chromosomal damage induced by tert-butanol in in 13 vitro systems, NTP (1995) studied sister chromatid exchanges and chromosomal aberrations. 14 Chinese hamster ovary (CHO) cells were exposed to tert-butanol in both the presence and absence 15 of S9 activation at concentrations of 160–5,000 µg/mL for 26 hours. tert-Butanol did not induce 16 sister chromatid exchanges at any concentration tested, although in one experiment, percent 17 relative change of sister chromatid exchanges per chromosome scored slightly increased. The same 18 authors also studied the effect of tert-butanol on chromosomal aberration formation. CHO cells 19 were exposed to four concentrations (160, 500, 1,600, or 5,000 µg/mL) of tert-butanol in both the 20 presence and absence of S9. No significant increase in chromosomal aberration was observed at 21 any concentration tested. Of note is that, due to severe toxicity at the highest concentration 22 (5,000 µg/mL), only 13 metaphase cells were scored instead of 100 in the chromosomal aberration 23 assay. 24 Sgambato et al. (2009) examined the effects of tert-butanol on DNA damage using a normal 25 diploid rat fibroblast cell line. Cells were treated with 0- to 100-mM tert-butanol for 48 hours to

26 determine the half-maximal inhibitory concentration (IC50; 0.44 ± 0.2 mM). The 48-hour IC50 27 concentration then was used to determine DNA content, cell number, and phases of the cell cycle 28 after 24 and 48 hours of exposure. Total protein and DNA oxidative damage also were measured. A 29 comet assay was used to evaluate DNA fragmentation at time 0 and after 30 minutes, 4 hours, or

30 12 hours of exposure to the IC50 concentration. tert-Butanol inhibited cell division as measured by

31 the number of cells after 24 and 48 hours of exposure at IC50 concentrations and with

32 concentrations at 1/10th the IC50. Cell death did not increase, suggesting a reduction in cell number 33 due to reduced replication rather than to cytotoxicity. tert-Butanol caused an accumulation in the

34 G0/G1 phase of replication, related to different effects on the expression of the cyclin D1, p27Kip1, 35 3and p5 genes. An initial increase in DNA damage as measured by nuclear fragmentation was 36 observed at 30 minutes. The DNA damage declined drastically after 4 hours and disappeared 37 almost entirely after 12 hours of exposure to tert-butanol. This reduction in the extent of DNA

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

8 B.2.2.3. In Vivo Mammalian Studies 9 Few in vivo studies are available to understand the role of tert-butanol on genotoxicity. The 10 National Toxicology Program studied the effect of tert-butanol in a 13-week toxicity study (NTP, 11 1995). Peripheral blood samples were obtained from male and female B6CF1 mice exposed to tert- 12 butanol in drinking water at doses of 3,000–40,000 ppm. Slides were prepared to determine the 13 frequency of micronuclei in 10,000 normochromatic erythrocytes. In addition, the percentage of 14 polychromatic erythrocytes among the total erythrocyte population was determined. No increase in 15 micronucleus induction in peripheral blood lymphocytes was observed either in male or female

16 B6C3F1 mice exposed for 13 weeks to tert-butanol in drinking water at concentrations as high as 17 40,000 ppm (2,110 mg/kg-day) (NTP, 1997, 1995). Furthermore, no induction of micronuclei in 18 polychromatic erythrocytes was observed in bone marrow cells of male rats receiving 19 intr aperitoneal injections (NTP, 1997). 20 Male Kunming mice (8 per treatment) were administered 0, 0.099, 0.99, 10, 101, or 21 997 µg/kg BW 14C-tert-butanol in saline via gavage with specific activity ranging from 1.60 to 22 0.00978 mCi/mol (Yuan et al., 2007). Animals were sacrificed 6 hours after exposure, and liver, 23 kidney, and lung were collected. Tissues were prepared for DNA isolation with samples from the 24 same organs from every two mice combined. DNA adducts were measured using accelerated mass 25 spectrometry. The results of this study showed a dose-response increase in DNA adducts in all 26 three organs measured, although the methodology used to detect DNA adducts is considered 27 sensitive but could be nonspecific. The authors stated that tert-butanol was found, for the first time, 28 to form DNA adducts in mouse liver, lung, and kidney. Because this is a single and first-time study, 29 further validation of this study will provide certainty in understanding the mechanism of tert- 30 butanol -induced DNA adducts.

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1 Table B-5. 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 3333, followed. This study was part of (1987);NTP (TA98, TA100, TA1535, 10,000 µg/plate the NTP 1995 testing results. (1995) TA1537, TA1538) Reverse Mutation Assay 1000– ND + Only tested with S9 activation Williams-Hill et Salmonella typhimurium 4000 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, vehicles – distilled water and TA1535, TA1537) 5,000 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 et al. 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 et al. 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 induction , 3,000, 5,000, - 13-week, subchronic, drinking NTP (1995) B6C3F1 mouse peripheral 10,000, 20,000, water study blood cells 40,000 ppm Micronucleus induction, 39, 78, 156, 312, - i.p injections – 3 times at 24 h NTP (1997) male rats, bone marrow 625, 1250 intervals cells 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 2 a+ = positive; − = negative; ND = not determined. 3 bEffect is predicted to be due to mitochondrial membrane composition. 4 cDNA damage was completely reversed with increased exposure time. 5 Summary 6 tert-Butanol has been tested for its genotoxic potential using a variety of genotoxicity 7 assays. In general, a positive result in the Ames assay is 73-77% predictive of a positive result in the 8 rodent carcinogenicity assay (Kirkland et al., 2005). tert-Butanol did not induce mutations in most 9 bacterial strains; however, when tested in TA102, a strain that is sensitive to damage at A-T sites 10 inducible by oxidants, an increase in mutants was observed at low concentrations, although 11 conflicting results were reported in another study. Furthermore, the solvent (e.g., distilled water or 12 DMSO) used in the genotoxicity assay could influence results. In one experiment where tert-butanol 13 was dissolved in distilled water, a significant, dose-related increase in the number of mutants was 14 observed, with the maximum value reaching almost twice the control value. DMSO is known to be a 15 radical scavenger, and its presence in high concentrations might mask a mutagenic response 16 modulated by oxidative damage. Other species such as Neurospora crassa did not produce reverse 17 mutations due to exposure to tert-butanol. 18 tert-Butanol was tested in several human and animal in vitro mammalian systems for 19 genotoxicity (gene mutation, sister chromatid exchanges, chromosomal aberrations, and DNA 20 damage). No increase in gene mutations was observed in mouse lymphoma cells (L5178Y TK+/–). 21 These specific locus mutations in mammalian cells are used to demonstrate and quantify genetic 22 damage, thereby confirming or extending the data obtained in the more widely used bacterial cell 23 tests. Sister chromatid exchanges or chromosomal aberrations were not observed in CHO cells in 24 response to tert-butanol treatment. DNA damage was detected using a comet assay, however, in 25 both rat fibroblasts and HL-60 leukemia cells, with either an increase in DNA fragmentation at the 26 beginning of the exposure or dose-dependent increase in DNA damage observed. An initial increase 27 in DNA damage was observed at 30 minutes that declined drastically following 4 hours of exposure

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1 and disappeared almost entirely after 12 hours of exposure to tert-butanol. This reduction in the 2 extent of DNA fragmentation after an initial increase is likely the result of an efficient DNA repair 3 mechanism activated by cells following DNA damage induced by tert-butanol. A dose-dependent 4 increase in DNA damage was observed in human cells tested; however, because the exposure 5 occurred for only 1 hour in this study, whether DNA-repair mechanisms would occur after a longer 6 period of observation cannot be discerned. 7 Limited in vivo animal studies have been conducted on DNA adduct formation and 8 micronucleus induction. A dose-response increase in DNA adducts was observed in mouse liver, 9 kidney, and lung cells. The authors used accelerated mass spectrometry to detect DNA adducts, but 10 the identity of these adducts was not determined. The method uses 14C-labeled chemical for dosing, 11 isolated DNA is oxidized to carbon dioxide and reduced to filamentous graphite, and the ratios of 12 14C/12C are measured. The ratio then is converted to DNA adducts based on nucleotide content of 13 the DNA. Confirmation of these data will further the understanding of the mechanism of 14 t ert-butanol-induced DNA adducts. No increase in micronucleus induction was observed in mouse 15 peripheral blood cells in a 13-week drinking water study conducted by the National Toxicology 16 Program. 17 Overall, a limited database is available for understanding the role of tert-butanol-induced 18 genotoxicity for mode of action and carcinogenicity. The database is limited in terms of either the 19 array of genotoxicity tests conducted or the number of studies within the same type of test. In 20 addition, the results are either conflicting or inconsistent. The test strains, solvents, or control for 21 volatility used in certain studies are variable and could influence results. Furthermore, in some 22 st udies, the specificity of the methodology used has been challenged. Given the inconsistencies and 23 limitations of the database in terms of the methodology used, number of studies in the overall 24 database, coverage of studies across the genotoxicity battery, and the quality of the studies, the 25 weight -of-evidence analysis is inconclusive. The available data do not inform a definitive conclusion 26 on the genotoxicity of tert-butanol and thus the potential genotoxic effects of tert-butanol cannot be 27 discounted.

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1 2 APPENDIX C. DOSE-RESPONSE MODELING FOR 3 THE DERIVATION OF REFERENCE VALUES FOR 4 EFFECTS OTHER THAN CANCER AND THE 5 DERIVATION OF CANCER RISK ESTIMATES

6 This appendix provides technical detail on dose-response evaluation and determination of 7 points of departure (PODs) for relevant endpoints. The endpoints were modeled using EPA’s 8 Benchmark Dose Software (BMDS), version 2.1.2. The preambles for the cancer and noncancer 9 parts below describe the common practices used in evaluating the model fit and selecting the 10 appropriate model for determining the POD as outlined in the Benchmark Dose Technical Guidance 11 Document (U.S. EPA, 2000). In some cases, using alternative methods based on statistical judgment 12 might be appropriate; exceptions are noted as necessary in the summary of the modeling results.

13 Noncancer Endpoints 14 C.1.1.1. Data Sets 15 Data sets selected for dose-response modeling are provided in Table C-1. In all cases, 16 administered exposure was used in modeling the response data.

17 C.1.1.2. Model Fit 18 All models were fit to the data using the maximum likelihood method. The following 19 procedures were used, depending on whether data were dichotomous or continuous.

20 • For dichotomous models, the following parameter restrictions were applied: for log-logistic 21 model and for 22 Each model was tested for goodness-of-fit using , restrict slope ≥1; for gamma and Weibull models, restrict power ≥1; 23 a chi-square goodness-of- 2 p-value < 0.10 indicates lack of fit). Other factors also multistage models, restrict beta values ≥0. 24 were used to assess model fit, such as scaled residuals, visual fit, and adequacy of fit in the fit test (χ 25 low-dose region and near the benchmark response (BMR).

26 • For continuous models, the following parameter restrictions were applied: for polynomial 27 and for Hill, power, and exponential models, restrict power 28 Model fit was assessed by a series of tests. For each model, first the homogeneity of the models, restrict beta values ≥0; 29 variances was tested using a likelihood ratio test (BMDS Test 2). If Test 2 was not rejected ≥1. 30 2 p- If Test 2 was 31 2 p-value < 0.10), the variance was modeled as a power function of the mean, and (χ value ≥ 0.10), the model was fit to the data assuming constant variance. rejected (χ This document is a draft for review purposes only and does not constitute Agency policy. C-1 DRAFT—DO NOT CITE OR QUOTE Supplemental Information―tert-Butyl Alcohol

1 the variance model was tested for adequacy of fit using a likelihood ratio test (BMDS 2 Test 3). For fitting models using either constant variance or modeled variance, models for 3 the mean response were tested for adequacy of fit using a likelihood ratio test (BMDS Test 4 2 p-value < 0.10 indicating inadequate fit). Other factors also were used to assess 5 the model fit, such as scaled residuals, visual fit, and adequacy of fit in the low-dose region 4, with χ 6 and near the BMR.

7 C.1.1.3. Model Selection 8 For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as 9 estimated by the profile likelihood method) and the Akaike’s information criterion (AIC) value were 10 used to select a best-fit model among the models exhibiting adequate fit. If the BMDL estimates 11 were “sufficiently close,” that is, differed by no more than three-fold, the model selected was the 12 one that yielded the lowest AIC value. If the BMDL estimates were not sufficiently close, the lowest 13 BMDL was selected as the POD.

14 Table C-1. Noncancer endpoints selected for dose-response modeling for 15 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 1643 3274 6369 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 1643 3274 6369 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 Table2 C- . 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/Ab 117.89 Errorc Errorc 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

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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 aConstant 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. bThe Exponential (M2) model can appear equivalent to the Exponential (M3) model, however differences exist in digits not displayed in the table. cThe Exponential (M3) model can appear equivalent to the Exponential (M2) model, however differences exist in digits not displayed in the table. dBMD or BMDL computation failed for this model. eNo available degrees of freedom to calculate a goodness-of-fit value. fFor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. gFor 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. hFor 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

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 aConstant 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. bFor the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model. cNo available degrees of freedom to calculate a goodness-of-fit value. dFor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. eFor 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. fFor 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 LogpPobit 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

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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 aConstant 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. bBMC or BMCL computation failed for this model. cFor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model. dFor 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. eFor 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. fBMC or BMCL computation failed for this model.

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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 1 10:15 04/30 2014 2 Figure C-6. Plot of mean response by concentration, with fitted curve for Hill 3 model for absolute kidney weight in male 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.

6 Hill Model. (Version: 2.15; Date: 10/28/2009) 7 The form of the response function is: Y[dose] = intercept + v*dose^n/(k^n + dose^n). 8 A constant variance model is fit.

9 Benchmark Dose Computation. 10 BMR = 10% Relative risk 11 BMD = 1931.35 12 BMDL at the 95% confidence level = 1704.82

13 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 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 1.21 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 aModeled 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. bFor the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the Exponential (M2) model. cBMC or BMCL computation failed for this model. dFor 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. eFor 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) / carcinoma Male Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50 NTP (1995) Renal tubule adenoma or Rat (F344) / 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) / 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) / carcinoma; Hard Male reanalysis Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50 NTP (1995);Hard et al. (2011) 3 aEndpoint 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 × 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.1.2.1. 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

aSelected (best-fitting) model shown in boldface type. bAIC = Akaike Information Criterion. cConfidence 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 ======12 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 13 Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP 1995b_Thyroid 14 folluclar cell andenoma, female mice_MultiCanc3_10.(d) 15 Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP 16 1995b_Thyroid folluclar cell andenoma, female mice_MultiCanc3_10.plt 17 Fri May 13 15:22:18 2011 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

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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. aSelected (best-fitting) model shown in boldface type. bAIC = Akaike Information Criterion. cConfidence 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

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 ======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_Msc1-BMR05.(d) 16 Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid 17 tumors poly3_Msc1-BMR05.plt 18 Fri Jun 05 11:02:14 2015 19 ======20 21 BMDS_Model_Run 22 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ 23 24 The form of the probability function is: 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

aSelected (best-fitting) model shown in boldface type. bAIC = Akaike Information Criterion. cConfidence 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 5 11:18 06/05 2015 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 ======14 Multistage Model. (Version: 3.4; Date: 05/02/2014) 15 Input Data File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid tumors 16 poly3 -h_Msc2-BMR05.(d) 17 Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid 18 tumors poly3 -h_Msc2-BMR05.plt 19 Fri Jun 05 11:18:05 2015 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 aSelected model in bold. bBMD or BMDL computation failed for this model.

6 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation

0.5

0.4

0.3 Fraction Affected

0.2

0.1

BMDL BMD 0 50 100 150 200 250 300 350 400 dose 7 10:57 04/30 2014 8

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 aSelected model in bold. bNo available degrees of freedom to calculate a goodness of fit value.

6 Multistage Cancer Model with 0.95 Confidence Level

Multistage Cancer Linear extrapolation

0.5

0.4

0.3

Fraction Affected

0.2

0.1

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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2 Table C-16. Summary of BMD modeling results for renal tubule adenoma or 3 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 4 years modeled with administered dose units and including all dose groups; 5 reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk

6 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 aNo model was selected as a best-fitting model.

7 Table C-17. Summary of BMD modeling results for renal tubule adenoma or 8 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 9 years modeled with administered dose units and excluding high-dose group; 10 re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk

11 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. aSelected 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 50 100 150 200 dose 1 11:05 04/30 2014 2

3 Figure C-14. 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

9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30

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1 APPENDIX D. SUMMARY OF PUBLIC COMMENTS 2 AND EPA’s DISPOSITION

3 The Toxicological Review of tert-Butyl alcohol (tert-Butanol) was released for a 60-day 4 public comment period on May 16, 2016. Public comments on the assessment were submitted to 5 EPA by:

6 • Japan Petroleum Energy Center (posted June 24, 2016);

7 • Exponent, Inc. on behalf of LyondellBasell (posted June 24, 2016);

8 • Samuel M. Cohen (posted July 7, 2016);

9 • Lawrence H. Lash (posted June 24, 2016);

10 • LyondellBasell (posted June 24, 2016 and July 19, 2016);

11 • American Chemistry Council (posted July 7, 2016);

12 • Tox-Logic Consulting on behalf of ExxonMobil Biomedical Sciences (posted July 19, 13 2016);

14 • Tox Strategies on behalf of LyondellBasell (posted June 24, 2016); and

15 • American Petroleum Institute (posted July 19, 2016). 16 A summary of major public comments provided in these submissions and EPA’s response to 17 these comments are provided in the sections that follow. The comments have been synthesized and 18 paraphrased. Because several commenters often covered the same topic, the comment summaries 19 are organized by topic. Editorial changes and factual corrections offered by public commenters 20 were incorporated in the document as appropriate and are not discussed further. All public 21 comments provided were taken into consideration in revising the draft assessment prior to 22 releasing for external peer review. 23 24 Comments Related to the Preface, Preamble and Executive Summary 25 26 Comment [LyondellBasell]: The Salazar et al. (2015) model should be verified. This includes the 27 model structure, code, and data sets used. 28 29 EPA Response: This peer-review draft uses a PBPK model based on Borghoff et al. (2016). 30

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1 Comment [LyondellBasell]: The Executive Summary does not adequately capture: 2 3 1) The key uncertainties and high degree of conservatism associated with selecting rat kidney 4 transitional epithelial hyperplasia as the key response for the RfD derivation in that this response is 5 a recognized element of CPN and thus not relevant to human risk; 6 7 2) Uncertainties regarding the excessively high dose(s) used in the mouse thyroid tumor 8 assessment, which exceed both the EPA and OECD test guidance for selection of a Limit Dose and 9 other EPA and OECD guidance addressing the limitations of toxicity responses observed at dose 10 levels saturating metabolic saturation with resulting nonlinear toxicokinetics of TBA; and 11 12 3) An acknowledgment that the oral SF should be clearly annotated with the conclusion that the 13 overall “suggestive evidence” of TBA carcinogenicity does not allow for its use in quantitative 14 human risk analyses. 15 16 EPA Response: The previous Executive Summary did not include the commenter’s points because 17 they had not been conclusions of the public-comment draft. The Executive Summary has been 18 revised to reflect the conclusions of this peer-review draft, and the IRIS program has proposed a 19 charge question for the SAB/CAAC to comment on whether the Executive Summary appropriately 20 presents the major conclusions of the assessment. 21 22 Comments Related to the Literature Search and Study Quality 23 24 Comment [LyondellBasell]: Despite statements in preamble, there is no evidence that toxicity data 25 from TBAc, MTBE or ETBE was robustly searched, despite clear toxicokinetic bridging from these 26 studies to TBA. 27 28 EPA Response: The literature search was focused on tert-butanol as the primary chemical of 29 interest. Toxicity reported on chemicals extensively metabolized to tert-butanol (i.e., TBAc, MTBE, 30 and ETBE) are summarized in 1.1.4, and cross-compound comparisons for non-cancer and cancer 31 effects are discussed in Sections 1.3.1 and 1.3.2, respectively. 32 33 Comment [LyondellBasell]: Clarity is needed regarding how the primary references were selected 34 for “Sources of Health Effects Data” versus “Supporting Studies” and consistent application of 35 decision criteria. 36 37 EPA Response: Table LS-3, in the row labeled “Outcome” provides a list of the health effects that 38 cause a study to be considered a “source of health effects data.” Other pertinent studies, including

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1 mechanistic studies, are considered “supporting studies.” 2 3 Comments Related to Data Presented in Evidence Tables 4 5 Comment [LyondellBasell]: Clarification is needed on what determined the endpoints selected for 6 inclusion in evidence tables. Also, the exclusion of mechanistic key events (e.g., hyaline droplet 7 accumulation) is not consistent with the intent of the EPA IRIS program and does not lead to the 8 development of useful hazard evaluation. 9 10 EPA Response: Primary health effects information are included in evidence tables. Hyaline droplets 11 do not constitute primary health effects information, but it is included in a table of mechanistic 12 events used to evaluate the -globulin mode of action (Table 1-4). 13 α2u 14 Comments Related to Kidney Effects 15 16 Comment [Dr. Bogen on behalf of American Petroleum Institute]: tert-Butanol induced male rat 17 kidney tumors are not relevant to humans because tert-butanol-associated male rat kidney tumors 18 were exacerbated by a CPN mode of action that is specific to rats. CPN has no human counterpart 19 and is not considered relevant for human health risk assessment. 20 21 EPA Response: CPN is a common and well-established constellation of age-related lesions in the 22 kidney of rats, and there is no known counterpart to CPN in aging humans. However, CPN is not a 23 specific diagnosis on its own. These individual lesions or processes (tubular 24 degeneration/regeneration and dilatation, glomerular sclerosis and atrophy, interstitial fibrosis 25 and inflammation, etc.) could certainly occur in a human kidney. Because they happen to occur as a 26 group in the aged rat kidney does not necessarily make them rat-specific individually if there is a 27 treatment effect for one or more of them. In addition, exacerbation of one or more of these 28 processes likely reflects some type of cell injury/cytotoxicity, which is relevant to the human 29 kidney. One potential confounder is the alpha-2u globulin nephropathy in males which could also 30 exacerbate CPN but would not be considered relevant to human risk. 31 In a recent draft proposal for public comment (2015), FDA used CPN in their calculation of PDEs for 32 MIBK (http://www.fda.gov/ucm/groups/fdagov-public/@fdagov-drugs- 33 gen/documents/document/ucm467089.pdf). Similarly, EPA considered the rat kidney tumors to be 34 relevant to human health risk assessment. 35 36 Comment [Dr. Cohen, Dr. Hard, and LyondellBasell]: All the kidney changes identified in the 37 assessment associated with tert-butanol exposure are associated with -globulin nephropathy 38 or/and CPN, except for the cortical-medullary calcification that is common in F344 rats. Cortical- α2u This document is a draft for review purposes only and does not constitute Agency policy. D-3 DRAFT—DO NOT CITE OR QUOTE Supplemental Information―tert-Butyl Alcohol

1 medullary calcification also is not relevant to humans based on a long series of articles published 2 over the past 30 years or more. They asserted that transitional epithelial hyperplasia is not a valid 3 endpoint for dose response because the lesion is a component of CPN, and that tert-butanol male 4 rat renal tumors are adequately explained by alpha2u-globulin nephropathy combined with 5 advanced CPN. 6 7 EPA Response: Section 1.2.1 shows that, although renal tumors are correlated with CPN in male 8 rats, this correlation is weak in female rats and so the renal tumors cannot be attributed to solely to 9 CPN. The peer-review draft does not consider cortical-medullary calcification relevant to humans, 10 nor does it use TEH as an endpoint for dose-response assessment. 11 12 Comment [LyondellBasell]: Hyaline droplet accumulation was not given adequate importance and 13 more discussion of the hyaline droplet pathology should be included. 14 15 EPA Response: Additional text describing hyaline droplets would not affect overall conclusion of 16 the MOA nor would it serve to increase the clarity of the decision. 17 18 Comment [LyondellBasell]: An increase in kidney weights is a non-specific endpoint and should 19 not be a candidate for potential use in BMD modeling. 20 21 EPA Response: Changes in kidney weights are a sensitive, non-specific endpoint that is often used 22 for dose-response modeling. Althoug -globulin nephropathy are occurring and can 23 influence kidney weights, MOA analysis determined that they are only partially responsible for the h CPN and α2u 24 observed kidney effects. Therefore, kidney weight changes are relevant for human health risk 25 assessm ent. 26 27 Comment [LyondellBasell]: Suppurative inflammation in the rat kidney is a result of bacterial 28 infection, and therefore this lesion cannot be used as an indicator of chemically-induced renal 29 toxicity for the purposes of characterizing human hazard associated with tert-butanol. The 30 suppurative inflammation would have been associated with either advanced CPN or an ascending 31 infection probably related to urinary tract calculi, or both processes. 32 33 EPA Response: Suppurative inflammation is often but not always associated with bacterial 34 infection. The bacteria may not be apparent on H&E staining though; culture and/or special 35 staining are often needed. Suppurative inflammation may be part of the spectrum of CPN lesions 36 and additional analysis indicates that suppurative inflammation is correlated with CPN in females. 37 According to p39S of INHAND document: “Solitary proximal tubules affected with 38 microabscessation often occur in advanced stages of CPN, in which setting they need not be

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1 diagnosed separately (Frazier et al., 2012).” The text in the Executive Summary, Section 1.2.1, and 2 1.3.1 of the assessment has been clarified to reflect this information. 3 Comments Related to Thyroid Effects 4 Regarding the potential for high dose effects 5 6 Comment [Dr. Bus on behalf of LyondellBasell]: The dose levels at which thyroid tumors were 7 identified in male and female mice was a major concern, and discussion of the toxicity and 8 carcinogenicity findings at these high exposure concentrations would be informative, proposing 9 that the MOA most likely operates under nonlinear kinetics. If the NTP (1995) tert-butanol bioassay 10 was designed according to current dose selection guidance of EPA and OECD, mouse thyroid tumors 11 likely would not have emerged as a significant cancer concern. In addition to referencing passages 12 from OECD Guidance Document 116 (2012) describing the importance of considering rodent 13 toxicokine tic or ADME data, and suggesting that the presence of toxicokinetic inflection point could 14 be used as a surrogate for traditional target organ effects, the EPA Cancer Guidelines (2005) were 15 referenced, noting that changes in toxicokinetics with increasing dose may result “…in important 16 differences between high and low dose levels in disposition of the agent or generation of its active 17 forms. These studies play an important role in providing a rationale for dose selection in 18 carcinogenicity studies.” 19 20 EPA Response: The discussion of the thyroid follicular cell tumors (adenomas and carcinoma) as 21 well as the follicular cell hyperplasias, considered by both NTP and EPA to be pre-neoplastic lesions 22 and thus not suitable candidates for non-cancer reference value derivation, is presented in Section 23 1.2.2, while considerations and uncertainties pertaining to dose-response evaluation are discussed 24 in Sections 2.3.2 and 2.3.4, respectively. As discussed in Section 1.2.2, incidence of thyroid follicular 25 cell hyperplasia was significantly elevated in all male mice treatment groups (i.e. doses of 540, 1040 26 or 2070 mg/kg-d), in both mid and high-dose female mice groups (i.e. 1020 and 2110 mg/kg-d), 27 and was increased in low-dose female mice as well (510 mg/kg-d). As the hyperplasia was 28 considered to be a pre-neoplastic lesion, and would be a key precursor step in the progression of 29 initiated thyroid follicular cells towards neoplasia, the presence of increased hyperplasia and/or 30 neoplasia incidence in all treatment groups in both sexes of mice does not support the assertion 31 that a kinetic non-linearity exists which is responsible for a tumor-relevant response within the 32 experimental treatment range (i.e. 510 – 2110 mg/kg-d). Furthermore, no MOA was identified for 33 thyroid tumorigenesis, and no mouse PBPK model is available; as such, the available information 34 appears insufficient to clearly describe the kinetics of mouse thyroid tumorigenesis following tert- 35 butanol exposure. Therefore, there is insufficient information to predict with confidence what 36 exposure level, if any, may result in metabolic saturation of tert-butanol oxidative metabolism in

37 B6C3F1 mice, especially considering the highly inducible nature of the cytochrome p450 system 38 following repeated substrate exposure. The mouse follicular cell thyroid tumors were determined

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1 to be qualitatively and quantitatively relevant to human cancer hazard characterization following 2 recommendations from the EPA guidance on assessment of thyroid follicular cell tumors (EPA, 3 1998) and the EPA Cancer Guidelines (2005). 4 5 Comment [Dr. Bus and Dr. Borghoff on behalf of LyondellBasell]: Dose selection in these studies 6 did not follow recommendations of EPA and OECD testing guidelines, including long-established 7 limit dose guidelines of 1000 mg/kg bw/day and more recent considerations of saturated 8 metabolism and nonlinear toxicokinetics in selection of appropriate doses for carcinogenicity and 9 other test bioassays. Both male and female top dose groups reported in the NTP (1995) bioassay 10 (2,070 and 2,100 mg/kg-d, respectively) exceeded the Limit Dose by 2-fold, questioning dose- 11 relevance of thyroid tumor findings. Regarding the limit dose of 1,000 mg/kg-d, statements from a 12 OECD dose selection guidance were provided “A limit of 1000 mg/kg body weight/day may apply 13 except when human exposure indicates the need for a higher dose level to be used” (OECD, 2009), 14 along with a 1998 guideline document from the EPA Office of Prevention, Pesticides and Toxic 15 Substances (OPPTS): “The highest dose tested need not exceed 1,000 mg/kg/day.” (EPA 870.4300, 16 Combined Chronic Toxicity/Carcinogenicity, 1998). 17 18 EPA Response: The 1998 guideline document referenced from the EPA Office of Prevention, 19 Pesticides and Toxic Substances (OPPTS), informs the design of chronic animal bioassays in the 20 context of chemical testing and assessment prioritization, but does not provide instructions 21 regarding the evaluation or interpretation of similar bioassays already planned or conducted, such 22 as the NTP rodent bioassay reporting thyroid effects in mice following 2 years of oral tert-butanol 23 exposure (NTP, 1995), and so referencing any specific statement from the document without noting 24 the larger context for which it was intended can be misleading. Furthermore, the public comment 25 appears to interpret “need not” as “shall not”, whereas another section from the same EPA guidance 26 document suggests that this was not the intended interpretation, and that bioassays evaluating 27 doses higher than 1,000 mg/kg-d could be informative: “If a test at one dose level of at least 1,000 28 mg/kg body weight (expected human exposure may indicate the need for a higher dose level), using 29 the procedures described for this study, produces no observable toxic effects or if toxic effects 30 would not be expected based upon data of structurally related compounds, then a full study using 31 three dose levels might not be necessary.” Lastly, the paragraph immediately preceding the 32 sentence from EPA OPPTS guidance quoted in the public comment describes the various 33 considerations informative to selecting dose levels for a chronic rodent bioassay, which are 34 analogous to the process that NTP employs. Notably, NTP does not appear to observe an arbitrary 35 high-dose level limit, such as 1,000 mg/kg-d, as part of recent 2-year rodent bioassay study design; 36 5 NTP 2-year oral exposure technical reports (TR) published since 2010 have evaluated one or 37 more dose levels > 1,000 mg/kg-d in mice and rats (TR-578, TR-567, TR-565, TR-562 and TR-556). 38

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1 Comment [Dr. Borghoff on behalf of LyondellBasell and Dr. Fowles on behalf of Exxon Mobil 2 Biomedical Sciences]: The fact that rats did not exhibit thyroid effects may likely be due to fact that 3 rats were administered substantially lower TBA doses relative to mice (i.e. high doses of 650 4 mg/kg-d in female rats versus 2,110 mg/kg-d in female mice). Reliability of the NTP (1995) 5 bioassay is questionable because the dose levels used for rats were significantly lower than used for 6 mice. 7 8 EPA Response: The assertion is not entirely correct: treatment-related pre-neoplastic and/or 9 neoplastic thyroid lesions were observed in mouse treatment groups exposed to 510 – 2,110 10 mg/kg -d, an exposure range which overlaps with the upper end of rat treatment doses (90 – 650

11 mg/kg-d). The lowest doses administered to male and female B6C3F1 mice (540 and 510 mg/kg-d, 12 respectively) are comparable to the highest doses administered to male and female F344 rats (420 13 and 650 mg/kg-d, respectively). Therefore, the presence of treatment-associated thyroid toxicity in 14 mice, and the absence of thyroid toxicity in rats, is not due to rats being administered lower doses: 15 if rats were at least similarly sensitive, which is the general assumption (Section 1.2.2; EPA, 1998), 16 then thyroid effects should have been observed in the high dose rat groups. 17 It is unclear how the reliability of a rodent bioassay is directly related to the dose levels 18 employed; however, uncertainties in dose-response evaluations are discussed in Section 2.3.4. As 19 dose levels in NTP chronic rodent bioassays are selected based upon toxicity findings from 20 subchronic and acute range-finding studies, and renal toxicity from these studies was found to be 21 dose-limiting in rats but not mice, the higher dose-levels evaluated for mice versus rats is not 22 unexpected, and does not represent any flaw in study design or methodology pertaining to study 23 reliability. 24 25 Regarding the possible Mode of Action 26 27 Comment [Dr. Fowles on behalf of Exxon Mobil Biomedical Sciences and Dr. Bogen on behalf of 28 American Petroleum Institute]: tert-butanol is a weak CYP and SULT liver enzyme inducer in

29 female B6C3F1 mice, sharing some PB- and CAR- like induction elements (Blanck et al., 2010). 30 Furthermore, observed thyroid effects are likely secondary to a high dose hepatic enzyme induction 31 effect on thyroid hormone elimination and homeostasis in mice. While the magnitude of effects 32 were generally similar after 14 days in both the 2 and 20 mg/mL treatment groups (receiving 418 33 and 1616 mg/kg-d, respectively), early events such as the selective induction of SULT1A1, an 34 important enzyme regulating mouse thyroid hormone clearance rates, were consistent with the 35 slight reductions in T3/T4 as reported in the 14-day study, and would be expected to magnify with 36 time at the high dose. While agreeing that no liver pathology was reported in the NTP study in rats 37 or mice, as described in the tert-butanol draft, a statistically significant increase in relative liver 38 weight was seen in high dose male and female mice, and that a fatty change was observed in male

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1 high dose mice (but not females), the commenters concluded that TBA is not a general liver enzyme 2 inducer but selectively induces specific CYPs and SULT1A1, and therefore evidence of 3 histopathology associated with generalized liver enzyme induction would not be necessarily 4 expected. 5 The decreases in T3 and T4 levels reported by Blanck et al., (2010), along with increases in 6 liver enzyme levels and mRNA induction, particularly in CYP2B10, demonstrates effects which were 7 "virtually certain to have been associated with CAR activation". CAR-activation mediated anti- 8 thyroid MOA is not relevant to humans due to differences in T3/T4 hormone half-lives in humans 9 versus rodents. 10 11 EPA Response: As discussed in Section 1.2.2, based upon recommendations from the EPA guidance 12 document regarding the assessment of rodent thyroid follicular cell tumors (EPA, 1998), the 13 available evidence was found to be inadequate to determine if any anti-thyroid MOA was operative 14 in mice, including the suggested mechanism of nuclear-receptor stimulated induction of hepatic 15 enzyme expression and increased thyroid hormone metabolism. The conclusion of a high dose 16 effect is inconsistent both with the results reported in the single mechanistic study available 17 (Blanck et al., 2010), which noted similar decreases in female B6C3F1 mouse serum T3 and T4 18 levels following 14 days of exposure to either 418 or 1616 mg/kg-d, as well as with the single 19 chronic mouse bioassay available (NTP, 1995), which reported increased incidence of thyroid 20 follicular cell hyperplasia and/or neoplasia in male and female B6C3F1 mice following 2 years of 21 exposure to 540 – 2110 mg/kg-d. The effects on thyroid hormones in mice following short-term 22 exposure to 418 mg/kg-d, and on thyroid histology following chronic exposure to 540 mg/kg-d, 23 suggests that tert-butanol induces thyroid effects at the lowest doses evaluated in both studies. ≥ ≥ 24 Inter-species differences in thyroid hormone metabolism is discussed in the EPA thyroid follicular 25 cell tumor guidance (EPA, 1998), which concludes that despite these and other uncertainties, 26 rodent thyroid tumors should be considered relevant to human cancer hazard characterization. 27 As discussed in the thyroid cancer MOA analysis in Section 1.2.2, if the decreases in T3/T4 28 levels observed following 14 days of exposure to 418 or 1616 mg/kg-d tert-butanol would be 29 expected to magnify with time, then the sustained liver enzyme induction should have resulted in 30 some treatment-associated increase in liver histopathology (such as centrilobular hyprotrophy) 31 after subchronic or chronic exposures to comparable doses, i.e. 510 – 2110 mg/kg-d. However, as

32 noted in the public comments, no such liver effects were reported in male or female B6C3F1 mice. 33 Furthermore, while it is unclear whether or not a 15 or 22% increase in liver SULT1A1 mRNA levels 34 reported following 14 days to 418 or 1616 mg/kg-d exposure (Blanck et al., 2010) is sufficient to 35 increase T3/T4 catabolism, and therefore cause the decrease in serum T3/T4 levels as reported at 36 14 days, it does provide further support to the identification of thyroid effects associated with 37 thyroid carcinogenesis following exposure to low and high doses.

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1 Regarding liver effects in mice following subchronic or longer exposure, the comment is 2 assumed to reference the increased mouse relative liver weight in the 13 week subchronic 3 component of the bioassay reported by NTP (1995) since a 15 month sacrifice was not collected 4 from mice due to higher than anticipated early mortality, and organ weights were not reported at 5 the terminal harvest (i.e. 2 years). Indeed, after 13 weeks of oral exposure, relative liver weight was 6 induced in the two highest dose groups of male B6C3F1 mice (8210 and 3240 mg/kg-d), and in the 7 highest dose group of female B6C3F1 mice (11620 mg/kg-d). However, in the groups receiving 8 administered doses similar to those evaluated by Blanck et al. (2010), i.e. 418 and 1616 mg/kg-d, 9 there was no significant change in relative liver weights in male mice exposed to 640 and 1590 10 mg/kg-d, or in female mice exposed to 820 mg/kg-d, while the relative liver weights in female mice 11 exposed to 1660 mg/kg-d were significantly decreased by treatment, not increased. Notably, the 12 relative liver weights of male and female F344 rats were increased following 13 weeks of exposure 13 to 290 – 3620 mg/kg-d, and were significantly increased after 15 months of exposure in the high 14 dose males and females administered 420 and 650 mg/kg-d, respectively. However, there were no 15 liver or thyroid histopathological effects associated with tert-butanol exposure in rats, so changes 16 in relative liver weight does not appear to be linked to either liver or thyroid pathology in either 17 rats or mice following tert-butanol exposure. 18 The fatty change noted by the public comment was observed in the liver of only high dose 19 male mice after 2 years of exposure, but no such effect was present in the livers of female mice, 20 which were more sensitive to the thyroid toxicity induced by chronic tert-butanol exposure (80% of 21 high dose females had thyroid lesions versus 30% of high dose males; NTP, 1995). Also, thyroid 22 hyperplasia was induced in male mice in all treatment groups, despite fatty liver being only induced 23 in the high dose group. Because of this, the induction of fatty change in the livers of males was 24 considered to not be related to thyroid toxicity, as discussed in Section 1.2.2. 25 26 Comment [Dr. Fowles on behalf of Exxon Mobil Biomedical Sciences]: The lack of a statistically 27 significan t elevation in TSH in the short-term study does not invalidate the MOA, as TSH is a 28 notoriously variable parameter, strongly influenced by stress and diurnal factors, and that low 29 magnitude decreases in thyroid hormones in rodents may or may not trigger a measurable increase 30 in circulating TSH. After such a short-term exposure to TBA and mild reductions in T3/T4, TSH 31 levels would not be expected to be induced, as even the positive control phenobarbitol failed to 32 induce an increase in TSH (Blanck et al., 2010). 33 34 EPA Response: While detecting small, treatment-associated changes in thyroid hormone and 35 related pituitary hormone levels such as TSH maybe be experimentally difficult, complicated by 36 several factors including diurnal variation in background levels, inter-animal differences, and 37 analytical variability as pointed out by the public comment, the presence of such complications 38 does not in and of itself constitute positive evidence supporting the effect. To address these

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1 challenges, alternative endpoints (e.g. pituitary TSH subunit mRNA expression) have been 2 evaluated in studies of other compounds as an alternative measure to blood TSH levels. As 3 discussed in Section 1.2.2, changes in TSH levels was one of numerous factors evaluated in the 4 analysis of support for an anti-thyroid MOA, as described in the EPA guidance on rodent thyroid 5 follicular cell tumorigenesis (EPA, 1998). 6 7 Comments Related to Reproductive, Developmental and Neurotoxic Effects 8 Comment [LyondellBasell]: The assessment should draw a conclusion regarding reproductive 9 toxicity that indicates that there is a low concern for TBA reproductive toxicity and there is no need 10 for further reproductive testing. This conclusion is supported by studies in MTBE (Bevan et al, 11 1997) and ETBE (CIT, 2004; JPEC 2008; Fujii et al 2010; de Peyster, 2010) 12 13 EPA Response: The reproductive toxicity studies for MTBE and ETBE provide evidence for some 14 reproductive effects at higher doses, but are not consistent across studies or doses. For example, a 15 one -generation reproductive study in rats given 0, 100, 300, or 1,000 mg/kg-day ETBE for 16-17 16 weeks reported a 13.6% total incidence of total litter loss in the high dose group (control data for 17 whole litter loss ranged from 0-4.8%, mean value 0.7%), but was confounded by evidence of 18 systemic toxicity in two of the dams. There was also a slight but significant prolongation of 19 gestation in the high dose group. In another study, ETBE administration at 0, 250, 500, or 1,000 20 mg/kg-day during the pre-mating, mating, gestation, and lactation periods, and no effects on 21 reproductive endpoints were reported. 22 23 Data for maternal body weight gain after exposure to ETBE were also inconsistent across studies. In 24 Asano et al. (2001) and JPEC (2008i), New Zealand White rabbits were exposed to 0, 100, 300, or 25 1,000 mg/kg-day ETBE and showed a significant decrease in maternal weight gain at the highest 26 dose (although interpretation of maternal weight in rabbits should reviewed with caution due to 27 the high variability in weight in rabbits during pregnancy). Similarly, decreased maternal weight 28 gain was also reported by Gaoua (2004a) in Sprague Dawley rats exposed to ETBE at 1,000 mg/kg- 29 day. In contrast, ETBE induced an increase in maternal weight the same dose and rat strain in 30 another study (Fujii et al 2010 and JPEC (2008e). In other studies with similar dose 31 administrations, maternal weight was not affected (Aso et al. 2014; Asano et al 2011; Fujii et al 32 2010; Gaoua, 2004b). Taken together, these studies do not provide compelling evidence of no effect 33 in animals, therefore we cannot draw conclusions about the reproductive toxicity of ETBE. Further, 34 the inconsistent findings across these studies do not strengthen the TBA database to the level that 35 would allow a different conclusion to be drawn. 36 37 Comment [LyondellBasell]: The assessment should include a separate section on neurotoxicity 38 that includes relevant data from well-conducted TBA studies as well as available neurotoxicity and

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1 developmental neurotoxicity studies of structurally related chemicals such as other butanol 2 isomers and chemicals that are metabolized to TBA. 3 4 EPA Response: While we appreciate the comment about including other chemicals, this assessment 5 is focused on the toxicity resulting from TBA exposure as the parent compound. 6 7 Comment [LyondellBasell]: Contrary to the statement in the draft assessment on page 1-53 line 8 19-22, Nelson et al. (1991) provided detailed information on exposure methods and results to 9 indicate the studies were conducted similarly. Taken together, the data from these two studies 10 indicate that no pattern of developmental neurotoxicity was observed in studies at very high dose 11 levels. These results also support the current statement in Section 2.1.3 on database uncertainty 12 factor that further studies are unlikely to lead to identification of a more sensitive endpoint or a 13 lower point of departure than those selected by EPA for oral and inhalation exposures. This is 14 further supported by a series of studies conducted on other butanols and short-chain aliphatic 15 alcohols that should be considered relevant read-across data (Nelson et al. 1989, 1990)(note this 16 Nelson et al., 1989 is a different publication from that reported in the draft assessment, the citation 17 for this present reference is found in our reference list to this document). 18 19 EPA Response: The statement that the studies were not conducted similarly was removed. 20 However, as noted by the authors, there were still limitations in the study design and the groups 21 were exposed nonconcurrently which prevented direct comparisons between the two 22 concentrations of TBA. In regard to the read-across for other butanols, while it is true that some 23 studies point toward little to no evidence for neurotoxicity (e.g. Nelson et al, 1989) still other more 24 recent publications have concluded that there is evidence of neurotoxicity (Bale et al., 2016). 25 Therefore, it is difficult to make the conclusion that there is compelling evidence of no neurotoxicity 26 or developmental neurotoxicity due to exposure to TBA. 27 28 Comment [LyondellBasell]: “…conclusion fails to mention that the developmental toxicity 29 observed occurred only in the presence of significant maternal toxicity and it is not possible to 30 determine if the maternal toxicity observed played a role in the developmental toxicity.” In 31 addition, “there is no examination or consideration of the dose levels used in several of the studies 32 presented as causing developmental toxicity”. Also, “While developmental effects should not be 33 “discounted” because of the maternal toxicity observed, it is the responsibility of the document to 34 inform the reader of all possible explanations for the observed effects. Inclusion of the maternal 35 toxicity endpoints, in the same level of detail and accuracy as the developmental toxicity endpoints 36 is necessary for this assessment to be complete.” Finally, “In considering the fetal and maternal 37 toxicity data following tert-butanol exposure, the severity of the maternal effects were minimal and 38 therefore the developmental effects in the fetuses should not be discounted (U.S. EPA, 1991b).”

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1 2 EPA Response: Although this was mentioned in the current draft we have strengthened the 3 language in Sections 1.2.3 and 1.2.4 to clearly address this issue. The draft now calls out the higher 4 doses at which both maternal toxicity and developmental effects are observed. The draft contains 5 maternal toxicity in the developmental evidence tables. The maternal data, if collected, is presented 6 in similar fashion to that of the other data. This language has been altered and the draft no longer 7 states that the maternal effects were minimal. 8 9 Comment [LyondellBasell]: The draft assessment is incorrect in concluding that the data provide 10 inadequate information to draw conclusions regarding neurodevelopmental toxicity of TBA. The 11 Nelson et al. (1991) study is a comprehensive developmental neurotoxicity study that included 12 multiple tests of motor activity, motor coordination, and cognitive behavior including schedule 13 controlled operant behavior. 14 15 EPA Response: We appreciate the commenter’s position on the neurodevelopmental toxicity of 16 TBA. However, as noted by the authors, there were still limitations in the Nelson study including 17 not running the two concentrations of TBA concurrently and often only reporting data for the 18 significant changes. As noted by the commenters and in the draft, there are limitations with the 19 Daniel and Evans study as well. Taken together, it is difficult to make the strong conclusions about 20 the evidence of neurotoxicity or developmental neurotoxicity due to exposure to TBA. For this 21 reason, EPA concludes that the available evidence is inadequate. 22 23 Comments Related to Cancer Weight of Evidence 24 25 Comment [LyondellBasell]: The descriptor suggestive evidence represents a highly conservative 26 assessment. The overall weight of evidence indicates that tert-butanol induced rat renal cancer is 27 -globulin and 28 CPN). In addition, the mouse thyroid tumors are not quantitatively relevant to humans due the qualitatively not relevant to humans based on robust mode of action evidence (α2u 29 observation that the high-dose used in mouse oral bioassay was substantially above EPA guidance 30 recommendations for a Limit Dose, as well as being above the dose at which tert-butanol 31 metabolism was saturated with associated onset of nonlinear toxicokinetics. 32

33 EPA Response: Although the evidence suggests that tert- 2u-globulin nephropathy,

34 the data indicate that tert-butanol is a weak inducer of 2u-globulin and that this process is not butanol induces α 35 solely responsible for the renal tubule nephropathy and carcinogenicity observed in male rats. The α 36 lack of compensatory cell proliferation in male rats and evidence of nephrotoxicity in female rats

37 suggest that other processes, in addition to the 2u-globulin process, are operating. Furthermore, 38 the accumulation of hyaline droplets and the induction of renal tubule hyperplasia were affected at α 39 higher doses compared to those inducing renal tubule tumors. EPA conducted a MOA analysis

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1 under EPA’s cancer guidelines using the proposed criteria from Hard and Khan (2004) and Hard et 2 al. (2013). This analysis is presented in 1.2.1. under mode of action analysis- kidney effects. In 3 summary, considering discrepant patterns in the dose-response relationships for CPN, hyperplasia, 4 and renal tubule tumors and the lack of relationships between CPN grades and renal tubule tumors 5 in female rats, together with the lack of a generally accepted MOA for CPN, the renal tubule tumors 6 in rats cannot be attributed to CPN. Regarding the relevance of the mouse thyroid follicular cell 7 tumors, please see the EPA response to a similar comment above in the “Comments Related to 8 Thyroid Effects” Section. 9 10 Comments Related to Dose-Response 11 12 Comment [ACC]: The following analogy was not clear: “A 10% relative change from control was 13 used as a BMR for absolute kidney weight by analogy with a 10% change in body weight as an 14 indicator of toxicity.” Is a 10% change in absolute kidney weight known to be adverse? How would 15 a 10% extra risk calculation compare? 16 17 EPA Response: Extra risk and relative deviation are not alternatives; extra risk is for dichotomous 18 data and relative deviation is for continuous data. Whatever is selected as the BMR (including a 19 10% relative deviation in kidney weight) doesn’t have to be adverse per se, since the point of POD 20 selection is to identify an exposure level without adverse effects (minimally biologically significant 21 effects). 22 23 Comment [LyondellBasell]: While correct for female mice, a BMR of 5% was selected for males “to 24 represent the observed response for low-dose extrapolation”, likely because the responses for the 25 control and 3 treatment groups were 2, 0, 7 and 2 percent, respectively. The use of the 5% BMR, for 26 apparent statistical reasons only, should be clearly indicated in Table 2-9 as an additional source of 27 uncertainty in the derivation of the SF. In addition, it should be noted that NTP guidance for 28 statistical evaluation of tumors responses with a high background incidence should be evaluated 29 against a p<0.01 to reduce the potential for false positive tumor determinations. 30 31 EPA Response: The text the Toxicological Review has been clarified on page 1-42. The trend test 32 that was used tested for a linear trend in the mortality-adjusted incidences, so the apparent non- in 33 monotonicity mostly reflects noisy data (i.e., insufficient to conclude that the responses in the two 34 highest groups differ). The statement that the data were non-monotonic is an over-interpretation, 35 given the reduced effective size of the high dose group. Contrary to the comment, follicular cell 36 thyroid adenomas and carcinomas overall are not common (3.4% in females for years 1984-1994) 37 and NTP does not rely solely on p-value cut-offs for interpreting whether there is a positive 38 response. The NTP specifically noted that the adenomas were uncommon, that related hyperplasia

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1 was increased in higher dose groups, and that the only carcinoma occurred in the highest dose 2 group. Support also comes from the concordance with female mice. Although none of the NTP’s 3 reported trend tests had p<0.05, the trend test EPA applied was developed by NTP after this NTP 4 report was issued. 5 6 Comments Related to the Physiologically-Based Pharmacokinetic Model and Toxicokinetics 7 8 Comment [LyondellBasell]: Given that kidney toxicity is being considered following inhalation and 9 oral exposure, a more appropriate dose metric to evaluate would be the AUC for tert-butanol in the 10 kidney. 11 12 EPA Response: There are effects of tert-butanol in both male and female rats, showing these effects 13 are not attributable to a2u-globulin binding alone. For the females the tert-butanol blood 14 concentrations are very representative of kidney concentrations because the blood:kidney partition 15 coefficient is 1.1. For the exposure levels evaluated for route-to-route extrapolation, the ratio of the 16 AUC of the free tert-butanol concentration in kidney to blood AUC is 0.828 in female and male rats 17 (slight variation in 4th decimal place) for oral exposures. For inhalation exposures, at steady state 18 the ratio of free TBA in kidney to blood ranged from 0.832-0.834 in both male and female rats, but 19 the ratio differed by no more than 0.04% for any exposure level. Thus, use of AUC in the kidney vs. 20 blood would result in less than a 0.1% change in the resulting HECs. Given that there are many 21 more data points to inform blood AUC, there is greater confidence in the model’s ability to predict 22 blood AUC, so it was selected as a dose metric. 23 24 Comment [LyondellBasell]: A variety of questions and concerns are related to specific aspects of 25 PBPK modeling as implemented in the Salazar et al. (2015) model. 26 27 EPA Response: EPA has adopted the newly available Borghoff et al. (2016) model. 28 29 Comment [LyondellBasell]: Prior to using a model for extrapolation to derive an RfC, the model 30 and data sets used to develop and verify the model need to be confirmed. There is a lack of 31 identification of data sets from unpublished reports used for model development and review of the 32 model code is needed before its use for deriving an RfC. 33 34 EPA Response: A table has been included in the PBPK evaluation (U.S. EPA 2017), which replaces 35 most of Appendix B, summarizing all of the data sets used in the modeling, with details on specific 36 data sets provided. All citations should now be correct. All of the sources are available in HERO. 37

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1 Comment [LyondellBasell]: The differential responses in the 13 week inhalation studies versus the 2 oral studies could be attributed to the discontinuous nature of the inhalation exposures. Thus, use 3 of “similar blood TBA” is only appropriate if AUC values are the basis of the route comparisons. 4 5 EPA Response: Using a 6 h/d, 5 d/w exposure pattern, the average blood concentrations predicted 6 by the rat model are 84 and 190 mg/L for the two highest inhalation exposure levels. The 7 corresponding levels from the oral NTP bioassay range from 74 to 1900 mg/L, with the 2nd lowest 8 dose predicted to yield 200 mg/L in male rats. So when accounting for the pulsatile pattern, the 9 highest inhalation exposures are predicted to yield blood levels comparable to the two lowest oral 10 doses. So the internal dose ranges for the two overlap, though are much lower overall for 11 inhalation. 12 AUCs are the basis being used for route comparisons. But tissue levels will track with blood levels 13 and even using a model with alpha-2-u binding, when exposures are selected to match blood AUCs, 14 the free concentrations of TBA in kidney will also be similar for males exposed by DW vs. 15 inhalation, and likewise females exposed by DW vs. inhalation. So incorporation of this metric 16 and/or using alternate internal dose metrics is not likely to change the conclusion. 17 18 Comment [LyondellBasell]: Figure 4F and FG in the Salazar et al. (2015) were produced by 19 assuming only 67% of the amount of ETBE or TBA in exhaled air was collected as a cumulative 20 amount in exhaled breath following ETBE nose only inhalation exposure. While this improves the 21 model fit to the data, it is not supported by experimental evidence. 22 23 EPA Response: The 67% correction was mistakenly applied to account for the difference between 24 expired alveolar air and total expired air, which includes air that only enters the conducting 25 air ways (“dead space”). We agree that it is not appropriate and the term has been removed from 26 the calculation. 27 28 Comment [LyondellBasell]: The ARCO (1983) study reported toxicokinetics evaluations in rats 29 using radiolabeled TBA. Although this study provides useful information, the data collected in this 30 study needs to be described clearly as to how it was recalculated to provide the actual 31 co ncentration of tert-butanol in blood. 32 33 EPA Response: The values from ARCO (1983) were calculated by combining the % tert-butanol and 34 tert -butanol equivalents from Tables 15 and 24 in the Arco report for 1 mg/kg and from Tables 37 35 and 59 for 500 mg/kg. A table is included in the PBPK evaluation (U.S. EPA, 2017), which replaces 36 Appendix B, showing the calculations. A table has been included with details on all data sources 37 used. 38 39 Comment [LyondellBasell]: The Leavens and Borghoff (2009) tert-butanol PBPK model does in 40 fact represent the tert-butanol blood levels measured in the Poet et al. (1997) study, as shown in

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1 the figure presented in these comments. As also noted, this PBPK model predicted tert-butanol 2 concentration in tissues of male and female rats exposed to tert-butanol via inhalation. 3 4 EPA Response: The U.S. EPA attempted to reconstruct the tert-butanol submodel from the Leavens 5 and Borghoff (2009) publication; the results of using that model to simulate the i.v. exposures of 6 Poet et al. (1997) are shown in the PBPK evaluation (U.S. EPA, 2017), and were deemed inadequate. 7 The Borghoff et al. (2016) model differs in several details from that of Leavens and Borghoff (2009). 8 In particular, Leavens and Borghoff (2009) shows urinary clearance as coming from the kidney 9 compartment, while Borghoff et al. (2016) describes it as coming from (mixed) venous blood. 10 Hence we cannot conclude that Leavens and Borghoff (2009) fits the Poet et al. (1997) data, though 11 it is possible that EPA’s attempt to reproduce that model was erroneous. In any case, the Borghoff et 12 al. (2016) model does fit the data. 13 14 Comment [LyondellBasell]: The metabolism of tert-butanol suggests that it is reasonable to predict 15 potential high-dose specific metabolic saturation. There is reasonable toxicokinetic data indicating 16 that the top male/female doses of greater than 2000 mg/kg bw/day, and possibly even the 17 female/male mid-doses of 1020 and 1040 mg/kg bw/day, exceeded saturation of tert-butanol 18 metabolism resulting in onset of nonlinear plasma tert-butanol toxicokinetics. Mice (C56BL6) 19 administered single intraperitoneal doses of tert-butanol at doses of 5, 10 and 20 mmol/kg bw 20 (370, 741 and 1482 mg/kg bw) resulted in respective AUC values of 28, 96 and 324 mmol.hrs/L 21 (Faulkner and Hussain, 1989). Thus, a 4-fold increase in dose (5 to 20 mmol/kg bw) resulted in an 22 11.6 -fold increase in systemic AUC; metabolic saturation may have been present even at the next 23 lowest dose of 10 mmol/kg bw in which a 2-fold increase in dose (5 to 10 mmol/kg bw) resulted in 24 a 3.4-fold increase in AUC. 25 26 EPA Response: Saturation of tert-butanol metabolism is reasonable and the PBPK model 27 incorporated Michaelis-Menten kinetics which account for saturation. The KM used is 0.379 mM. 28 Considering that this value is for rats rather than mice, it appears reasonably consistent with the 29 range reported by Faulker and Hussain (1989), 0.56-0.92 mM, from fitting a one-compartment TK 30 model separately to each dose level. What matters is that the PBPK model adequately fits the PK 31 data across the range of exposures. Since this is a PK nonlinearity which is consistent with the 32 (fairly standard) model structure, that may or may not indicate nonlinearity in pharmacodynamic 33 mechanisms, the EPA does not consider it particularly useful to point it out for each data set where 34 it occurs. One of the reasons for using a PBPK model is that it allows one to appropriately account 35 for metabolic saturation, and the impact that has on the internal dose(s) across the entire dose 36 range. 37 38 Comment [LyondellBasell]: Use of toxicokinetic data to provide a data-informed selection of the 39 appropriate top dose in animal toxicity tests has recently been described as a Kinetically Derived

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1 Maximum (KMD) dose selection strategy (Saghir et al., 2012). The KMD dose selection strategy 2 specifically emphasizes that toxicokinetic data, when available, can and should be used as an 3 alternative to conventional top dose selection strategies based on Maximum Tolerated Dose (MTD). 4 tert-Butanol would have been a strong candidate for a KMD-based dose selection strategy. 5 6 EPA Response: While the KMD approach may provide better study designs in the future, the NTP 7 studies were conducted more than 15 years prior to Saghir et al. (2012). But the U.S. EPA does not 8 agree that toxicity data collected at exposure levels which saturate a metabolic pathway are not 9 usable or relevant for estimating human health risk, in particular when part of a dose-response 10 array that spans high and low exposure levels. 11 12 Comments Related to Genotoxicity 13 14 Comment [LyondellBasell]: It is rather surprising that the draft assessment concluded that “…a 15 limited database is available for understanding the role of tert-butanol-induced genotoxicity for 16 mode of action and carcinogenicity.” LyondellBasell commented that the statement that only 17 limited animal studies were conducted to investigate micronucleus formation is inaccurate. 18 C ontrary to the above statement, the WoE from a large database informs that TBA does not have the 19 potential to be an in vivo genotoxicant and a mutagenic MOA in the etiology of animal tumors can 20 thus be excluded with a reasonable degree of certainty. Finally, the NTP conducted a total of 3 21 micronucleus studies, two in the mouse and one in the rat and all three studies were clearly 22 negative. 23 24 EPA Response: As indicated in the summary of the genotoxicity section, the database is rather small 25 for both the array of genotoxicity tests conducted as well as the number of studies within the same 26 type of test category. In addition, sometimes, the data is either conflicting or inconsistent. Since 27 there are a few studies that are positive, tert-butanol cannot be considered nongenotoxic with 28 complete certainty, therefore, the conclusion presented in Section B.3.2 of the Supplementary 29 Materials will remain unchanged. Finally, the two mouse studies referred to by LyondellBasell are 30 one study published both in NTP (1995) and NTP (1997). 31 32 Comment [LyondellBasell]: There are two key studies missing in Section B.3.2.3 under in vivo 33 mammalian studies. The first study is a rat bone marrow micronucleus test reported by the NTP 34 (1997). The second missing study is a mouse bone marrow micronucleus test reported by the NTP. 35 The two missing, negative NTP mouse and rat bone marrow micronucleus studies that were 36 discussed above should be included under “In vivo Animal Studies” section of this table. 37

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1 EPA Response: The NTP (1997) rat study is now included in the assessment. However, both 2 micronucleus tests referenced in the comments are the same study. With respect to the mouse 3 study, the NTP (1995) and NTP (1997) studies are from the same set of experiments and is already 4 present in the current assessment.

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1 2 REFERENCES

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1 Borghoff, SJ; Prescott, JS; Janszen, DB; Wong, BA; Everitt, JI. (2001). alpha2u-Globulin nephropathy, 2 renal cell proliferation, and dosimetry of inhaled tert-butyl alcohol in male and female F- 3 344 rats. Toxicol Sci. 61: 176-186. http://dx.doi.org/10.1093/toxsci/61.1.176. 4 Borghoff, SJ; Ring, C; Banton, MI; Leavens, TL. (2016). Physiologically based pharmacokinetic model 5 for ethyl tertiary-butyl ether and tertiary-butyl alcohol in rats: Contribution of binding to 6 -globulin in male rats and high-exposure nonlinear kinetics to toxicity and cancer 7 outcomes. J Appl Toxicol. http://dx.doi.org/10.1002/jat.3412. α2u 8 Cederbaum, AI; Cohen, G. (1980). Oxidative demethylation of t-butyl alcohol by rat liver 9 microsomes. Biochem Biophys Res Commun. 97: 730-736. 10 Cederbaum, AI; Qureshi, A; Cohen, G. (1983). Production of formaldehyde and acetone by hydroxyl- 11 radical generating systems during the metabolism of tertiary butyl alcohol. Biochem 12 Pharmacol. 32: 3517-3524. http://dx.doi.org/10.1016/0006-2952(83)90297-6. 13 Dickey, FH; Cleland, GH; Lotz, C. (1949). The role of organic peroxides in the induction of mutations. 14 PNAS. 35: 581-586. 15 Faulkner, TP; Wiechart, JD; Hartman, DM; Hussain, AS. (1989). The effects of prenatal tertiary 16 butanol administration in CBA/J and C57BL/6J mice. Life Sci. 45: 1989-1995. 17 FDA (U.S. Food and Drug Administration). (2011a). Indirect food additives: Adjuvants, production 18 aids, and sanitizers. Surface lubricants used in the manufacture of metallic articles. 21 CFR 19 178.3910. 20 http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=178.3910. 21 FDA (U.S. Food and Drug Administration). (2011b). Indirect food additives: Paper and paperboard 22 components. Defoaming agents used in coatings. 21 CFR 176.200. 23 http://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=176.200. 24 Galloway, SM; Deasy, DA; Bean, CL; Kraynak, AR; Armstrong, MJ; Bradley, MO. (1987). Effects of 25 high osmotic strength on chromosome aberrations, sister-chromatid exchanges and DNA 26 strand breaks, and the relation to toxicity. Mutat Res. 189: 15-25. 27 http://dx.doi.org/10.1016/0165-1218(87)90029-2. 28 Grant, KA; Samson, HH. (1981). Development of physical dependence on t-butanol in rats: An 29 examination using schedule-induced drinking. Pharmacol Biochem Behav. 14: 633-637. 30 http://dx.doi.org/10.1016/0091-3057(81)90124-6. 31 Hard, GC; Bruner, RH; Cohen, SM; Pletcher, JM; Regan, KS. (2011). Renal histopathology in toxicity 32 and carcinogenicity studies with tert-butyl alcohol administered in drinking water to F344 33 rats: A pathology working group review and re-evaluation. Regul Toxicol Pharmacol. 59: 34 430 -436. http://dx.doi.org/10.1016/j.yrtph.2011.01.007. 35 Jimenez, J; Longo, E; Benitez, T. (1988). Induction of petite yeast mutants by membrane-active 36 agents. Appl Environ Microbiol. 54: 3126-3132. 37 Kirkland, D; Aardema, M; Henderson, L; Muller, L. (2005). Evaluation of the ability of a battery of 38 three in vitro genotoxicity tests to discriminate rodent carcinogens and non-carcinogens: I. 39 Sensitivity, specificity and relative predictivity. Mutat Res. 584: 1-256. 40 http://dx.doi.org/10.1016/j.mrgentox.2005.02.004. 41 Leavens, TL; Borghoff, SJ. (2009). Physiologically based pharmacokinetic model of methyl tertiary 42 butyl ether and tertiary butyl alcohol dosimetry in male rats based on binding to alpha2u- 43 globulin. Toxicol Sci. 109: 321-335. http://dx.doi.org/10.1093/toxsci/kfp049.

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1 Lyondell Chemical Co. (Lyondell Chemical Company). (2004). Reproductive and developmental 2 toxicity screening test in rats by oral gavage. (Document Control Number: 89-040000106). 3 McComb, J; Goldstein, D. (1979a). Additive physical dependence: evidence for a common 4 mechanism in alcohol dependence. J Pharmacol Exp Ther. 210: 87-90. 5 McComb, J; Goldstein, D. (1979b). Quantitative comparison of physical dependence on tertiary 6 butanol and ethanol in mice: Correlation with lipid solubility. J Pharmacol Exp Ther. 208: 7 113 -117. 8 Mcgregor, D; Cruzan, G; Callander, R; May, K; Banton, M. (2005). The mutagenicity testing of 9 tertiary-butyl alcohol, tertiary-butyl acetate and methyl tertiary-butyl ether in Salmonella 10 typhimurium. Mutat Res. 565: 181-189. http://dx.doi.org/10.1016/j.mrgentox.2004.10.002. 11 McGregor, DB; Brown, A; Cattanach, P; Edwards, I; Mcbride, D; Caspary, WJ. (1988). Responses of 12 the L5178Y tk+/tk- mouse lymphoma cell forward mutation assay II: 18 coded chemicals. 13 Environ Mol Mutagen. 11: 91-118. 14 Nihlén, A; Lof, A; Johanson, G. (1998a). Controlled ethyl tert-butyl ether (ETBE) exposure of male 15 volunteers: I Toxicokinetics. Toxicol Sci. 46: 1-10. 16 http://dx.doi.org/10.1006/toxs.1998.2516. 17 Nihlén, A; Löf, A; Johanson, G. (1995). Liquid/air partition coefficients of methyl and ethyl t-butyl 18 ethers, t-amyl methyl ether, and t-butyl alcohol. J Expo Anal Environ Epidemiol. 5: 573-582. 19 Nihlén, A; Löf, A; Johanson, G. (1998b). Experimental exposure to methyl tertiary-butyl ether: I 20 Toxicokinetics in humans. Toxicol Appl Pharmacol. 148: 274-280. 21 http://dx.doi.org/10.1006/taap.1997.8333. 22 NIOSH (National Institute for Occupational Safety and Health). (2007). NIOSH pocket guide to 23 chemical hazards. (DHHS-2005-149. CBRNIAC-CB-112149). Cincinnati, OH. 24 http://www.cdc.gov/niosh/docs/2005-149/. 25 NSF International. (2003). t-Butanol: Oral Risk Assessment Document (CAS 75-65-0). Ann Arbor, 26 MI. 27 NTP (National Toxicology Program). (1995). Toxicology and carcinogenesis studies of t-butyl 28 alcohol (CAS no 75-65-0) in F344/N rats and B6C3F1 mice (Drinking water studies) (pp. 1- 29 305). (NTPTR436). Research Triangle Park, NC. 30 NTP (National Toxicology Program). (1997). NTP technical report on toxicity studies of t-butyl 31 alcohol (CAS no 75-65-0) administered by inhalation to F344/N rats and B6C3F1 mice (pp. 32 1-56, A51-D59). Research Triangle Park, NC. 33 http://ntp.niehs.nih.gov/ntp/htdocs/ST_rpts/tox053.pdf. 34 OSHA (Occupational Safety & Health Administration). (2006). Table Z-1: Limits for air 35 contaminants. Occupational safety and health standards, subpart Z, toxic and hazardous 36 substances. (OSHA standard 1910.1000, 29 CFR). Washington, DC: U.S. Department of 37 Labor. 38 http://www.osha.gov/pls/oshaweb/owadisp.show_document?p_table=STANDARDS&p_id= 39 9992. 40 Poet, TS; Valentine, JL; Borghoff, SJ. (1997). Pharmacokinetics of tertiary butyl alcohol in male and 41 female Fischer 344 rats. Toxicol Lett. 92: 179-186.

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1 Salazar, KD; Brinkerhoff, CJ; Lee, JS; Chiu, WA. (2015). Development and application of a rat PBPK 2 model to elucidate kidney and liver effects induced by ETBE and tert-butanol. Toxicol Appl 3 Pharmacol. 288: 439-452. http://dx.doi.org/10.1016/j.taap.2015.08.015. 4 Sgambato, A; Iavicoli, I; De Paola, B; Bianchino, G; Boninsegna, A; Bergamaschi, A; Pietroiusti, A; 5 Cittadini, A. (2009). Differential toxic effects of methyl tertiary butyl ether and tert-butanol 6 on rat fibroblasts in vitro. Toxicol Ind Health. 25: 141-151. 7 http://dx.doi.org/10.1177/0748233709104867. 8 Snell, D. (1980). Impairment of avoidance behavior following short-term ingestion of ethanol, 9 tertiary-butanol, or pentobarbital in mice. Psychopharmacology. 69: 53-57. 10 http://dx.doi.org/10.1007/BF00426521. 11 Spiteri, NJ. (1982). Circadian patterning of feeding, drinking and activity during diurnal food access 12 in rats. Physiol Behav. 28: 139-147. http://dx.doi.org/10.1016/0031-9384(82)90115-9. 13 Tang, G; Wang, J; Zhuang, Z. (1997). [Cytotoxicity and genotoxicity of methyl tert-butyl ether and its 14 metabolite to human leukemia cells]. Zhonghua Yufang Yixue Zazhi. 31: 334-337. 15 Thurman, RG; Winn, K; Urquhart, B. (1980). Rat brain cyclic AMP levels and withdrawal behavior 16 following treatment with t-butanol. Adv Exp Med Biol. 126: 271-281. 17 U.S. EPA (U.S. Environmental Protection Agency). (2000). Benchmark dose technical guidance 18 document [external review draft] [EPA Report]. (EPA/630/R-00/001). Washington, DC: U.S. 19 Environmental Protection Agency, Risk Assessment Forum. 20 http://www.epa.gov/raf/publications/benchmark-dose-doc-draft.htm. 21 U.S. EPA (U.S. Environmental Protection Agency). (2011). Recommended use of body weight 3/4 as 22 the default method in derivation of the oral reference dose. (EPA/100/R11/0001). 23 Washington, DC: U.S. Environmental Protection Agency, Risk Assessment Forum. 24 http://www.epa.gov/raf/publications/interspecies-extrapolation.htm. 25 U.S. EPA (U.S. Environmental Protection Agency). (2016). Model files for tert-butanol and ETBE. 26 U.S. EPA (U.S. Environmental Protection Agency). (2017). PK/PBPK model evaluation for the IRIS 27 assessments of ethyl tertiary butyl ether (CASRN 637-92-3) and tert-butyl alcohol (CAS No. 28 755 -6 -0) (Draft) [EPA Report]. Washington, DC: U.S. Environmental Protection Agency, 29 Pharmacokinetics Working Group. 30 Videla, LA; Fernández, V; de Marinis, A; Fernández, N; Valenzuela, A. (1982). Liver lipoperoxidative 31 pressure and glutathione status following acetaldehyde and aliphatic alcohols 32 pretreatments in the rat. Biochem Biophys Res Commun. 104: 965-970. 33 http://dx.doi.org/10.1016/0006-291X(82)91343-2. 34 Williams-Hill, D; Spears, CP; Prakash, S; Olah, GA; Shamma, T; Moin, T; Kim, LY; Hill, CK. (1999). 35 Mutagenicity studies of methyl-tert-butylether using the Ames tester strain TA102. Mutat 36 Res. 446: 15-21. http://dx.doi.org/10.1016/s1383-5718(99)00137-0. 37 Williams, TM; Borghoff, SJ. (2001). Characterization of tert-butyl alcohol binding to "alpha"2u- 38 globulin in F-344 rats. Toxicol Sci. 62: 228-235. http://dx.doi.org/10.1093/toxsci/62.2.228. 39 Wood, J; Laverty, R. (1979). Physical dependence following prolonged ethanol or t-butanol 40 administration to rats. Pharmacol Biochem Behav. 10: 113-119. 41 Yuan, Y; Wang, HF; Sun, HF; Du, HF; Xu, LH; Liu, YF; Ding, XF; Fu, DP; Liu, KX. (2007). Adduction of 42 DNA with MTBE and TBA in mice studied by accelerator mass spectrometry. Environ 43 Toxicol. 22: 630-635. http://dx.doi.org/10.1002/tox.20295.

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1 Zeiger, E; Anderson, B; Haworth, S; Lawlor, T; Mortelmans, K; Speck, W. (1987). Salmonella 2 mutagenicity tests: III. Results from the testing of 255 chemicals. Environ Mutagen. 9: 1- 3 109. http://dx.doi.org/10.1002/em.2860090602. 4

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