DRAFT DELIBERATIVE: FOR INTERAGENCY REVIEW ONLY. 

DO NOT DISTRIBUTE OUTSIDE YOUR AGENCY.

 EPA/635/R-14/378

Interagency Review Draft

www.epa.gov/iris

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

(CASRN 75-65-0)

In Support of Summary Information on the

Integrated Risk Information System (IRIS)

Supplemental Information

September 2014 

NOTICE

This document is an Interagency Science Consultation 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-Butanol

DISCLAIMER

This document is a preliminary draft for review purposes only. This information is 

distributed solely for the purpose of pre-dissemination peer review under applicable information 

quality guidelines. It has not been formally disseminated by EPA. It does not represent and should 

not be construed to represent any Agency determination or policy. Mention of trade names or 

commercial products does not constitute endorsement or recommendation for use.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert-Butanol

CONTENTS

APPENDIX A. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS .................................................... A-1

A.1. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS ........................................ A-1

APPENDIX B. INFORMATION IN SUPPORT OF HAZARD IDENTIFICATION AND DOSERESPONSE ANALYSIS......................................................................................................................... B-1

B.1. TOXICOKINETICS..................................................................................................................... B-1

B.1.1. Absorption................................................................................................................... B-1

B.1.2. Distribution................................................................................................................. B-1

B.1.3. Metabolism.................................................................................................................. B-2

B.1.4. Excretion...................................................................................................................... B-4

B.1.5. Physiologically Based Pharmacokinetic Models ......................................... B-5

B.2. PBPK MODEL EVALUATION SUMMARY......................................................................... B-9

B.2.1. Evaluation of Existing tert-Butanol Submodels........................................... B-9

B.2.2. Modification of Existing tert-Butanol Submodels.................................... B-11

B.2.3. tert-Butanol Model Application....................................................................... B-14

B.2.4. PBPK Model Code.................................................................................................. B-15

B.3. OTHER PERTINENT TOXICITY INFORMATION........................................................ B-16

B.3.1. Genotoxicity............................................................................................................. B-16

B.3.2. Summary................................................................................................................... B-21

APPENDIX C. DOSE-RESPONSE MODELING FOR THE DERIVATION OF REFERENCE 

VALUES FOR EFFECTS OTHER THAN CANCER AND THE DERIVATION OF 

CANCER RISK ESTIMATES ............................................................................................................... C-1

C.1. BENCHMARK DOSE MODELING SUMMARY................................................................. C-1

C.1.1. Noncancer Endpoints ............................................................................................. C-1

C.1.2. Cancer Endpoints ................................................................................................... C-30

APPENDIX D. SUMMARY OF EXTERNAL PEER REVIEW AND PUBLIC COMMENTS AND 

EPA’S DISPOSITION ............................................................................................................................ D-1

REFERENCES FOR APPENDICES........................................................................................................................................ 1

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TABLES

Table A-1. Other Agency and International Assessments................................................................................... A-1

Table B-1. PBPK model physiologic parameters and partition coefficients............................................. B-12

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

experimental data. .................................................................................................................................. B-14

Table B-3. Summary of genotoxicity (both in vitro and in vivo) studies of tert-butanol.................... B-20

Table C-1. Non-cancer endpoints selected for dose-response modeling for tert-butanol.................... C-2

Table C-2. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in male 

F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 

10% extra risk. ............................................................................................................................................ C-3

Table C-3. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in 

female F344 rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); 

BMR = 10% extra risk............................................................................................................................... C-6

Table C-4. Summary of BMD modeling results for relative kidney weights in male F344 rats exposed 

to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% relative 

deviation and 1 standard deviation.................................................................................................... C-9

Table C-5. Summary of BMD modeling results for relative kidney weights in female F344 rats 

exposed to tert-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% 

relative deviation and 1 standard deviation................................................................................ C-13

Table C-6. Summary of BMD modeling results for kidney inflammation in female rats exposed to 

tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk.......... C-16

Table C-7. Summary of BMD modeling results for thyroid follicular cell hyperplasia in male B6C3F1 

mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 10% 

extra risk..................................................................................................................................................... C-19

Table C-8. Summary of BMD modeling results for thyroid follicular cell hyperplasia in female 

B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 

10% extra risk. ......................................................................................................................................... C-20

Table C-9. Summary of BMD modeling results for absolute kidney weight in male F344 rats exposed 

to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% 

relative deviation from the mean. .................................................................................................... C-23

Table C-10. Summary of BMD modeling results for relative kidney weight in male F344 rats exposed 

to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% 

relative deviation from the mean. .................................................................................................... C-26

Table C-11. Summary of BMD modeling results for absolute kidney weight in female F344 rats 

exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); 

BMR = 10% relative deviation from the mean............................................................................ C-29

Table C-12. Summary of BMD modeling results for relative kidney weight in female F344 rats 

exposed to tert-butanol via inhalation for 6 hrs/d, 5d/wk for 13 weeks (NTP, 1997); 

BMR = 10% relative deviation from the mean............................................................................ C-30

Table C-13. Cancer endpoints selected for dose-response modeling for tert-butanol........................ C-31

Table C-14. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with 

administered dose units and including all dose groups (NTP, 1995); BMR = 10% extra 

risk................................................................................................................................................................. C-32

Table C-15. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with 

administered dose units and excluding high-dose group (NTP, 1995); BMR = 10% extra 

risk................................................................................................................................................................. C-34

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Table C-16. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(tert-butanol, mg/L) dose units and including all dose groups (NTP, 1995); BMR = 10% 

extra risk..................................................................................................................................................... C-36

Table C-17. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(tert-butanol, mg/L) dose units and excluding high-dose group (NTP, 1995); BMR = 

10% extra risk. ......................................................................................................................................... C-38

Table C-18. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(metabolized, mg/hr) dose units and including all dose groups (NTP, 1995); BMR = 

10% extra risk. ......................................................................................................................................... C-40

Table C-19. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(metabolized, mg/hr) dose units and excluding high-dose group (NTP, 1995); BMR = 

10% extra risk. ......................................................................................................................................... C-42

Table C-20. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with 

administered dose units and including all dose groups; reanalyzed data (Hard et al., 

2011; NTP, 1995); BMR = 10% extra risk..................................................................................... C-44

Table C-21. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with 

administered dose units and excluding high-dose group; re-analyzed data (Hard et al., 

2011; NTP, 1995); BMR = 10% extra risk..................................................................................... C-44

Table C-22. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(tert-butanol, mg/L) dose units and including all dose groups; reanalyzed data (Hard et 

al., 2011; NTP, 1995); BMR = 10% extra risk. ............................................................................. C-47

Table C-23. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(tert-butanol, mg/L) dose units and excluding high-dose group; reanalyzed data (Hard 

et al., 2011; NTP, 1995); BMR = 10% extra risk. ........................................................................ C-47

Table C-24. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(metabolized, mg/hr) dose units and including all dose groups; reanalyzed data (Hard 

et al., 2011; NTP, 1995); BMR = 10% extra risk. ........................................................................ C-49

Table C-25. Summary of BMD modeling results for renal tubule adenoma or carcinoma in male 

F344 rats exposed to tert-butanol in drinking water for 2 years modeled with PBPK 

(metabolized, mg/hr) dose units and excluding high-dose group; reanalyzed data (Hard 

et al., 2011; NTP, 1995); BMR = 10% extra risk. ........................................................................ C-49

Table C-26. Summary of BMD modeling results for thyroid follicular cell adenomas in female 

B6C3F1 mice exposed to tert-butanol in drinking water for 2 years (NTP, 1995); BMR = 

10% extra risk. ......................................................................................................................................... C-52

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FIGURES 

Figure B-1. Biotransformation of tert-butanol in rats and humans. .............................................................. B-3

Figure B-2. Comparison of the tert-butanol portions of existing MTBE models with tert-butanol 

blood concentrations from i.v. exposure by Poet et al. 1997. .................................................. B-9

Figure B-3. Schematic of the PBPK submodel for tert-butanol in rats. ...................................................... B-11

Figure B-4. Comparison of the EPA model predictions with measured tert-butanol blood 

concentrations for i.v., inhalation, and oral gavage exposure to tert-butanol. .............. B-13

Figure B-5. Comparison of the EPA model predictions with measured amounts of tert-butanol in 

blood after repeated inhalation exposure to tert-butanol. .................................................... B-16

Figure C-1. Plot of mean response by dose, with fitted curve for selected model.................................... C-4

Figure C-2. Plot of mean response by dose, with fitted curve for selected model.................................... C-7

Figure C-3. Plot of mean response by dose, with fitted curve for selected model (10% relative 

deviation). .................................................................................................................................................. C-10

Figure C-4. Plot of mean response by dose, with fitted curve for selected model (10% relative 

deviation). .................................................................................................................................................. C-13

Figure C-5. Plot of mean response by dose, with fitted curve for selected model................................. C-16

Figure C-6. Plot of mean response by dose, with fitted curve for selected model................................. C-20

Figure C-7. Plot of mean response by dose, with fitted curve for selected model; dose shown in 

mg/m3. ......................................................................................................................................................... C-24

Figure C-8. Plot of mean response by dose, with fitted curve for selected model; dose shown in 

mg/m3. ......................................................................................................................................................... C-27

Figure C-9. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/kg-d. ...................................................................................................................................................... C-32

Figure C-10. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/kg-d. ...................................................................................................................................................... C-34

Figure C-11. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/L. ............................................................................................................................................................ C-36

Figure C-12. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/L. ............................................................................................................................................................ C-38

Figure C-13. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/hr. .......................................................................................................................................................... C-40

Figure C-14. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/hr. .......................................................................................................................................................... C-42

Figure C-15. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/kg-d. ...................................................................................................................................................... C-45

Figure C-16. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/L. ............................................................................................................................................................ C-48

Figure C-17. Plot of incidence rate by dose, with fitted curve for selected model; dose shown in 

mg/hr. .......................................................................................................................................................... C-50

Figure C-18. Plot of mean response by dose, with fitted curve for selected model. ............................. C-52

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ABBREVIATIONS

AIC Akaike’s information criterion 

ARCO ARCO Chemical Company

BMD benchmark dose 

BMDL benchmark dose lower confidence limit 

BMDS Benchmark Dose Software

BMDU benchmark dose upper confidence limit

BMR benchmark response

BW body weight

CA chromosomal aberration

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 

SE standard error

TWA time-weighted average

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1 APPENDIX A. OTHER AGENCY AND 

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INTERNATIONAL ASSESSMENTS

A.1. OTHER AGENCY AND INTERNATIONAL ASSESSMENTS

Table A-1. Other Agency and International Assessments. 

Organization Toxicity value

American Conference of 

Governmental Industrial 

Hygienists (ACGIH, 2012)

Threshold Limit Value – 100 ppm (303.1493 mg/m3) time-weighted 

average (TWA) for an 8-hour workday and a 40-hour work week

National Institute of 

Occupational Safety and Health 

(NIOSH, 2007)

Recommended Exposure Limit – 100 ppm (300 mg/m3) TWA for up to 

a 10-hour workday and a 40-hour work week

Occupational Safety and Health 

(OSHA, 2006)

Permissible Exposure Limit for general industry – 100 ppm 

(300 mg/m3) TWA for an 8-hour workday

Food and Drug Administration 

(FDA, 2011a, b) 

tert-Butyl alcohol: Indirect food additive that may be safely used in 

surface 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).

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1 APPENDIX B. INFORMATION IN SUPPORT OF 

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HAZARD IDENTIFICATION AND DOSE-RESPONSE

ANALYSIS

B.1. TOXICOKINETICS

There is little information on the absorption, distribution, metabolism, or excretion of tertbutyl alcohol (tert-butanol) in humans. The studies identified were conducted in conjunction with 

methyl tert-butyl ether (MTBE) and ethyl tert-butyl ether (ETBE) because tert-butanol is a primary 

metabolite of these two compounds. Several studies examining some aspect of the toxicokinetic 

behavior of tert-butanol in animals have been identified. Many of the studies were carried out in 

conjunction with other specific endpoints (e.g., developmental). ARCO (1983) determined that 

there were no differences in the pharmacokinetics of tert-butanol following either oral (i.e., gavage) 

or inhalation exposure. Although there is some information available after both oral and inhalation 

exposures, many studies also administered tert-butanol via intraperitoneal (i.p.) or intravenous 

(i.v.) injection. Although these studies do not inform the absorption of tert-butanol, they can 

provide information on distribution, metabolism, and excretion.

B.1.1. Absorption

Extensive tert-butanol toxicity testing data submitted by industry to the U.S. Environmental 

Protection Agency (EPA) under Section 8(e) of the Toxic Substances Control Act and other 

reporting requirements indicate that tert-butanol is rapidly absorbed after oral administration.

Very little of the administered dose was excreted in the feces of rats, indicating 99% of the 

compound was absorbed. Comparable blood levels of tert-butanol and its metabolites have been 

observed after acute oral (350 mg/kg) and inhalation (6,164 mg/m3 for 6 hours) exposures (ARCO, 

1983); however, the absorption rate after inhalation exposure could not be determined because the 

blood was saturated with radioactivity after 6 hours of a 6,164-mg/m3 exposure. Based on blood 

concentrations, absorption was found to be complete at 1.5 hours following repeated oral exposure, 

with an apparent zero-order decline in tert-butanol concentration for the majority of the 

elimination phase, thus indicating that previous exposures did not affect the absorption of tertbutanol (Faulkner et al., 1989). 

B.1.2. Distribution

The available animal data suggest that tert-butanol is distributed throughout the body 

following oral, inhalation, and injection exposures (Poet et al., 1997; Faulkner et al., 1989; ARCO, 

1983). Nihlén et al. (1995) determined a partition coefficient for tert-butanol using blood from 

human volunteers. The study was approved by an ethical review board, and informed consent was 

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1 obtained from the participants. Their results indicated that tert-butanol would rapidly move from 

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the blood into the tissues. 

tert-Butanol was found in the kidney, liver, and blood of both sexes of rat following oral 

exposure, but male rats retained more tert-butanol compared with females (Williams and Borghoff, 

2001). Radioactivity was found in the low-molecular-weight protein fraction from the kidney 

cytosol in male rats but not female rats, indicating that tert-butanol or one of its metabolites was 

bound to α2u-globulin. Further analysis determined that it was tert-butanol that was bound and not 

its metabolite acetone. The majority of tert-butanol in the kidney cytosol was eluted as the free 

compound in both males and females, but a small amount was also found associated with the highmolecular-weight protein fraction in both males and females. Borghoff et al. (2001) found similar 

results in rats after inhalation exposure. Male rat kidney-to-blood ratios were significantly elevated 

over female ratios at all dose levels and exposure durations. Although the female tert-butanol

kidney-to-blood ratio remained similar with both duration and concentration, the male tert-butanol

kidney-to-blood ratio increased with duration. The liver-to-blood ratios were similar regardless of 

exposure duration, concentration, or sex. Both of these studies indicate distribution to the liver and 

kidney with kidney retention of tert-butanol in the male rat. 

B.1.3. Metabolism

A general metabolic scheme for tert-butanol, illustrating the biotransformation in rats and 

humans, is shown in Figure B–1 below. Urinary metabolites of tert-butanol in a human male 

volunteers who ingested a gelatin capsule containing 5 mg/kg [13C]-tert-butanol were reported to 

be 2-methyl-1,2-propanediol (MPD) and 2-hydroxyisobutyrate (Bernauer et al., 1998). Minor 

metabolites of unconjugated tert-butanol, tert-butanol glucuronides, and traces of the sulfate 

conjugate also were detected. The study was approved by an ethical review board; however, no 

information regarding informed consent was reported. In the same study, 2-hydroxyisobutyrate, 

MPD, and tert-butanol sulfate were identified as major metabolites in rats, while acetone, tertbutanol, and tert-butanol glucuronides were identified as minor metabolites (Bernauer et al., 1998). 

Baker et al. (1982) found that tert-butanol was a source of acetone, but also may have stimulated 

acetone production from other sources.

There are no studies that identify specific enzymes responsible for the biotransformation of 

tert-butanol. Using purified enzymes from Sprague-Dawley rats or whole-liver cytosol from Wistar 

rats, alcohol dehydrogenase had negligible or no activity toward tert-butanol (Videla et al., 1982; 

Arslanian et al., 1971). Other in vitro studies have implicated the liver microsomal mixed function 

oxidase (MFO) system, namely cytochrome P-450 (CYP450) (Cederbaum et al., 1983; Cederbaum 

and Cohen, 1980). In the first study, incubation of tert-butanol at 35 mM with Sprague-Dawley rat

liver microsomes and a nicotinamide adenine dinucleotide phosphate- (NADPH) generating system

resulted in the production of formaldehyde at a concentration of approximately 25 nmoles/mg 

protein/30 min. According to study authors, the amount of formaldehyde generated by tert-butanol 

is approximately 30% of the amount of formaldehyde formed during the metabolism of 10 mM 

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1 aminopyrene in a similar microsomal system. The rate of formaldehyde generation from 

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tert-butanol was increased to about 90 nmol/mg protein/30 min upon addition of azide, which

inhibits catalase and thereby prevents the decomposition of hydrogen peroxide (H2O2). In other 

experiments within the same study, there was a major reduction of formaldehyde formation when 

H2O2 was included but NADPH was absent or when the microsomes were boiled prior to incubation.

Additionally, the rate of formaldehyde formation in the microsomal oxidizing system was found to 

be dependent on the concentration of tert-butanol, with apparent Km and Vmax values of 30 mM and 

5.5 nmol/min/mg protein, respectively. The study authors concluded that tert-butanol is 

metabolized to formaldehyde by a mechanism involving oxidation of NADPH, microsomal electron 

flow, and the generation of hydroxyl-radical (·OH) from H2O2, possibly by a Fenton-type or a HaberWeiss iron-catalyzed reaction involving CYP450, which might serve as the iron chelate (Cederbaum 

and Cohen, 1980). 

 

CH3

OH CH3

CH3

CYP450

CH3

3CH OH

O

[O] CH3

OH CH3

OOH

3CH

CH3

OH

OH

3CH CH3

O

t-butanol 2-methyl-1,2-propanediol

acetone

2-hydroxyisobutyric acid

OO

O

S

CH3

CH3

O CH3

t-butyl sulfate

t-butyl glucuronide

CH3

CH3

CH3 glucuronide–O 

rats, humans

rats

rats,

humans 2CH O

formaldehyde

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

Source: NSF International (2003), ATSDR (1996), Bernauer et al. (1998), Amberg et al. (1999), and 

Cederbaum and Cohen (1980). 

In a follow-up study, tert-butanol was oxidized to formaldehyde and acetone by a variety of 

systems known to generate ·OH radical, including rat liver microsomes or other nonmicrosomal .

OH 

generating systems (Cederbaum et al., 1983). The nonmicrosomal tests included two chemical 

systems: (1) the iron-catalyzed oxidation of ascorbic acid (ascorbate-Fe-EDTA 

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1 [ethylenediaminetetraacetic acid]) and (2) the Fenton system of chelated ferrous iron and H2O2. In 

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both of these Fenton-type systems, H2O2 served as a precursor of ·OH. Additionally, a Haber-Weiss 

enzymatic system involving oxidation of xanthine by xanthine oxidase in the presence of Fe-EDTA 

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

(O2·-

). Further experiments demonstrated the involvement of ·OH in either the ascorbate-Fe-EDTA 

or the xanthine oxidation systems based on inhibition of formaldehyde and acetone production 

from tert-butanol upon addition of ·OH-scavenging agents (e.g., benzoate, mannitol). Some of the 

experiments in this study of the oxidation of tert-butanol by the liver microsomal metabolizing 

system were similar to those in the previous study except that, in addition to formaldehyde, 

acetone formation was also measured. Again, these experiments showed the dependence of the 

microsomal metabolizing system on an NADPH-generating system and the ability of H2O2 to 

enhance, but not replace, the NADPH-generating system. Addition of chelated iron (Fe-EDTA) 

boosted the microsomal production of formaldehyde and acetone, while ·OH scavenging agents 

inhibited their production. The study authors noted that neither Fe-EDTA nor ·OH scavenging 

agents is known to affect the CYP450 catalyzed oxidation of typical MFO substrates such as 

aminopyrene or aniline. The study also showed that known CYP450 inhibitors, such as metyrapone 

or SKF-525A, inhibited the production of formaldehyde from aminopyrene but not from tertbutanol. Finally, typical inducers of CYP450 and its MFO metabolizing activities, such as 

phenobarbital or 3-methylcholanthrene, had no effect on the extent of microsomal metabolism of 

tert-butanol to formaldehyde and acetone. According to the study authors, the oxidation of tertbutanol appears to be mediated by ·OH (possibly via H2O2), which can be produced by any of the 

tested systems by a Fenton-type reaction as follows:

H2O2 + Fe2+ -chelate → ·OH + OH- + Fe3+ -chelate

According to this reaction, reduction of ferric iron (Fe3+) to ferrous iron (Fe2+) is required 

for continuous activity. The study authors concluded that the nature of the iron and the pathway of 

iron reduction within the microsomes remain to be elucidated even though an NADPH-dependent 

electron transfer or O2·- might be involved (Cederbaum et al., 1983). 

B.1.4. Excretion

Human data on the excretion of tert-butanol comes from studies of MTBE and ETBE (Nihlén 

et al., 1998a, b). Eight or ten male human volunteers were exposed to 5, 25, or 50 ppm MTBE or 

ETBE by inhalation during 2 hours of light exercise. The half-life of tert-butanol in urine following

MTBE exposure was 8.1 ± 2.0 hours (average of the 25- and 50-ppm MTBE doses); the half-life of 

tert-butanol in urine following ETBE exposure was 7.9 ± 2.7 hours (average of 25- and 50-ppm 

ETBE doses). The renal clearance rate of tert-butanol was 0.67 ± 0.11 mL/hr-kg with MTBE

exposure (average of 25- and 50-ppm MTBE doses); the renal clearance rate was 0.80 ± 0.34 

mL/hr-kg with ETBE exposure (average of 25- and 50-ppm ETBE doses). 

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 Amberg et al. (2000) exposed six volunteers (three males and three females, 28 ± 2 years 

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old) to 18.8 and 170 mg/m3 ETBE. Each exposure lasted 4 hours, and the two concentrations were 

administered to the same volunteers 4 weeks apart. Urine was collected at 6-hour intervals for 

72 hours following exposure. tert-Butanol and two metabolites of tert-butanol, 

2-hydroxyisobutyrate (HBA) and MPD, also were identified in urine. At an ETBE level of 170 

mg/m3, tert-butanol displayed a half-life of 9.8 ± 1.4 hours. At the low-exposure ETBE

concentration, the tert-butanol half-life was 8.2 ± 2.2 hours. The predominant urinary metabolite 

identified was HBA, excreted in urine at 5–10 times the amount of MPD and 12–18 times the 

amount of tert-butanol (note: urine samples had been treated with acid before analysis to cleave 

conjugates). HBA in urine showed a broad maximum at 12–30 hours after exposure to both 

concentrations, with a slow decline thereafter. MPD in urine peaked at 12 and 18 hours after 

exposure to 170 and 18.8 mg/m3 ETBE, respectively, while tert-butanol peaked at 6 hours after 

both concentrations. 

Amberg et al. (2000) exposed F344 NH rats to 18.8 and 170 mg/m3 ETBE. Urine was 

collected for 72 hours following exposure. Similar to humans, rats excreted mostly HBA in urine, 

followed by MPD and tert-butanol. The half-life for tert-butanol in rat urine was 4.6 ± 1.4 hours at 

ETBE levels of 170 mg/m3, but half-life could not be calculated at the ETBE concentration of 

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 

4.7 ± 2.6 hours for HBA. In Sprague-Dawley rats treated with radiolabeled tert-butanol by gavage at 

1, 30, or 500 mg/kg, a fairly constant fraction of the administered radioactivity (23–33%) was 

recovered in the urine at 24 hours postdosing. However, only 9% of a 1500-mg/kg administered 

dose was recovered in urine, suggesting that the urinary route of elimination is saturated following 

this dose (ARCO, 1983). 

B.1.5. Physiologically Based Pharmacokinetic Models

There have been no physiologically based pharmacokinetic (PBPK) models developed 

specifically for administration of tert-butanol. The majority studied tert-butanol as the primary 

metabolite after oral or inhalation exposure to MTBE or ETBE. The most recent models for MTBE 

oral and inhalation exposure include a component for the binding of tert-butanol to α2u-globulin 

(Borghoff et al., 2010; Leavens and Borghoff, 2009). 

Faulkner and Hussain (1989) used a one-compartment open model with Michaelis-Menten 

elimination kinetics to fit tert-butanol blood concentrations obtained from C57BL/6J mice given i.p. 

injections of 5, 10, or 20 mmol/kg tert-butanol. Elimination was indistinguishable from first-order 

kinetics in the range of concentrations studied. An increase in Vmax and decrease in apparent 

volume of distribution with dose are consistent with this model and suggest the existence of 

parallel elimination processes.

Borghoff et al. (1996) developed a PBPK model for MTBE and its metabolite tert-butanol in 

rats. Doses and blood levels were taken from several published studies. The initial model included a 

tissue-specific five-compartment model using blood, liver, kidney, muscle, and fat with liver 

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 metabolism rate constants. The model was able to predict the accumulation of tert-butanol in blood, 

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but not its clearance. A two-compartment model was better at predicting tert-butanol blood levels, 

however, the volume of the total body water had to be changed to obtain an adequate fit, suggesting 

dose-dependent changes in the kinetics of tert-butanol. Overall, evaluation of the tert-butanol

models suggests that the clearance of tert-butanol from the blood of rats after exposure to MTBE 

involves processes beyond metabolic elimination. 

Nihlén and Johanson (1999) developed a PBPK model for evaluation of inhalation exposure 

in humans to the gasoline additive ETBE. Model compartments for ETBE included lungs (with

arterial blood), liver, fat, rapidly perfused tissues, resting muscles, and working muscles. The same 

set of compartments and an additional urinary excretion compartment were used for the 

metabolite, tert-butanol. First-order metabolism was assumed in the model, and tissue/blood 

partition coefficients were determined by in vitro methods (Nihlén et al., 1995). Estimates of 

individual metabolite parameters of eight subjects were obtained by fitting the PBPK model to 

experimental data from humans (5, 25, or 50 ppm ETBE; 2-hour exposure) (Nihlén et al., 1998a). 

This model was applied primarily to predict levels of the biomarkers ETBE and tert-butanol in 

blood, urine, and exhaled air after various scenarios, such as prolonged exposure, fluctuating 

exposure, and exposure during physical activity (Nihlén and Johanson, 1999). 

Rao and Ginsberg (1997) developed a PBPK model for MTBE and its principal metabolite, 

tert-butanol, based on the Borghoff et al. (1996) model. The modified model included a skin 

compartment to simulate dermal absorption of MTBE during bathing or showering. A brain 

compartment was added as a target organ for MTBE-induced neurological responses. MTBE 

metabolism to tert-butanol was assumed to occur in the liver through two saturable pathways. The 

tert-butanol portion of the model included further metabolism of tert-butanol in the liver, 

exhalation in the lungs, and renal excretion (in the human model only). The model was validated 

against published human and rat data and was used to help determine the contribution of tertbutanol in the acute central nervous system effects seen after MTBE dosing.

The Rao and Ginsberg (1997) model used peak concentrations of MTBE and tert-butanol in 

the blood and brain for interspecies, route-to-route, and low/high-dose extrapolations. The 

MTBE/tert-butanol PBPK model was adapted to humans by adjusting physiology according to 

literature values, incorporating the blood/air partition coefficient for humans reported by Johanson 

et al. (1995), and allometrically scaling the metabolic rate based on body weight. A renal 

elimination component was added to account for the small percentage of MTBE disposition that 

occurs in humans via urinary excretion of tert-butanol. tert-Butanol concentrations in human blood 

during and after MTBE exposure (25 or 50 ppm for 2 hours) were accurately predicted by the 

human model (Johanson et al., 1995). 

Kim et al. (2007) expanded the Borghoff et al. (1996) model to develop a multi-exposure 

route model for MTBE and its primary metabolite, tert-butanol, in humans. The significant features 

and advantages of the Kim et al. (2007) model are that parameters used for quantifying the 

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 pharmacokinetic behavior of MTBE and tert-butanol are calibrated using time-series 

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measurements from controlled-exposure experiments in humans as reported by Prah et al. (2004). 

MTBE partition coefficient values described in the Licata et al. (2001) model and skin compartment 

parameters from the Rao and Ginsberg (1997) model were incorporated. The PBPK model for 

MTBE consists of nine primary compartments representing the lungs, skin, fat, kidney, stomach, 

intestine, liver, rapidly perfused tissue, and slowly perfused tissue. The tert-butanol model consists 

of three compartments representing blood, liver, and other tissue. 

Leavens and Borghoff (2009) developed a PBPK model for inhalation exposures in male and 

female rats that expanded on Borghoff et al. (1996) and Rao and Ginsberg (1997) to include the sexspecific effects of MTBE binding to α2u-globulin, a protein unique to male rats, and to describe the 

induction of tert-butanol metabolism after repeated exposures. Although the primary purpose of 

the model was to estimate MTBE and tert-butanol tissue concentrations after MTBE exposure, the 

model was also parameterized to include inhalation uptake of tert-butanol. The tert-butanol portion 

of the model was calibrated using data from rat exposures to tert-butanol as well as MTBE. Model 

compartments included blood, brain, fat, gastrointestinal tissues, kidney, liver, poorly perfused 

tissues (blood flow of <100 mL/min/100 g of tissue: bone, muscle, skin, fat), and rapidly perfused 

tissues. 

Distribution of MTBE and tert-butanol was assumed to be perfusion (i.e., blood-flow) 

limited. This model used the same assumptions as Borghoff et al. (1996) regarding MTBE 

metabolism and kinetics, and assumed that tert-butanol was metabolized only in the liver through 

one low-affinity pathway and excreted through urine. The model described binding of MTBE or 

tert-butanol with α2u-globulin in the kidney, due to the high concentration of α2u-globulin in the 

kidney. As chemicals bind to α2u-globulin, the rate of hydrolysis of the protein decreases and causes 

accumulation in the kidney; however, there is no evidence that binding of α2u-globulin affects its 

synthesis, secretion, or circulating concentrations [Borghoff et al. (1990) as cited in Leavens and 

Borghoff (2009)]. Equations describing this phenomenon were included in the model for male rats 

only to account for the effects of the binding with α2u-globulin on metabolism of MTBE and tertbutanol. Partition coefficient values in the model that differed from those published in previous 

PBPK models included poorly perfused tissues:blood and kidney:blood values. The kidney:blood 

value was based on calculated kidney:blood concentrations in female rats only because of the lack 

of α2u-globulin-associated effects in female rats. The deposition of tert-butanol during inhalation in 

the nasal cavity and upper airways was reflected in the high blood:air partition coefficient for tertbutanol, and the ability of tert-butanol to induce its own metabolism after chronic exposure was 

also taken into account. No differences in the induction of metabolism were reported between 

males and females. The model simulated concentrations of MTBE and tert-butanol in the brain, 

liver, and kidney of male and female rats following inhalation exposure at concentrations of 100, 

400, 1,750, or 3,000 ppm MTBE, and compared them to measured concentrations of MTBE and tertbutanol from rats exposed at those levels.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 Concentrations of MTBE and tert-butanol in the brain and liver were similar in male and 

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female rats during exposure and postexposure, but the concentrations of the chemicals in the 

kidney were significantly different in male rats when compared with female rats. The additional 

parameter accounting for α2u-globulin protein-binding in this PBPK model more accurately reflects 

the metabolism of both MTBE and tert-butanol in male rat kidneys over time compared with other 

PBPK models. The model highlights that binding can stimulate increased renal effects in male rats 

after exposure to MTBE and tert-butanol. The assumptions made to reflect tert-butanol metabolism 

induction and deposition in the nasal cavity and upper airways generally were supported by 

measured data from rats exposed to 250, 450, or 1,750 ppm tert-butanol as evidenced by the fact 

that the model was within one standard deviation of the mean concentrations for most data points.

However, the model overpredicted the concentration of tert-butanol in the brain, liver, and kidney 

of male rats after repeated exposures. 

Borghoff et al. (2010) modified the PBPK model of Leavens and Borghoff (2009) by adding 

oral gavage and drinking water exposure components. This was done to compare different dose 

metrics to the toxicity observed across different studies. The Borghoff et al. (2010) model assumed 

first-order uptake of MTBE absorption from the gut, with 100% of the MTBE dose absorbed for 

both drinking water and oral gavage exposures. They conducted a series of pharmacokinetic 

studies comparing the effects of different rat strains and different dosing vehicles on the blood 

concentration-time profiles of MTBE and tert-butanol following MTBE exposure. The effects of 

exposure to MTBE via drinking water, oral gavage, and inhalation routes over 7 and 91 days on 

male and female rats were modeled and compared with measured data collected from F344 rats 

(exposed 28 days) and Wistar Han rats (exposed 14 and 93 days). 

The model predicted the blood concentrations of tert-butanol that were observed after 250 

or 1,000 mg/kg-day administration of MTBE in males and females, as well as the blood 

concentrations of MTBE after 1,000 mg/kg-day, but was not able to predict peak concentrations of 

MTBE after 250 mg/kg-day in males or females using either olive oil or 2% Emulphor as vehicles.

When comparing strains, the blood concentrations were similar across strain and sex, except in 

female Sprague-Dawley rats administered 1,000 mg/kg-day MTBE. The female Sprague-Dawley 

rats had a significantly (p-value not specified) higher blood concentration of both MTBE and tertbutanol compared with the F344 and the Wistar Han females. However, the study authors 

considered this an outlier and still considered the metabolic patterns similar. The model 

overpredicted the amount of MTBE in the male rat kidney, but it accurately predicted the level of 

tert-butanol in the male rat kidney at all exposures tested. The model did not accurately predict the

kidney concentrations of tert-butanol in the female kidney after exposure to MTBE via drinking 

water, but the study authors attributed the inaccuracies to the study design as opposed to the 

model formulation. All of the tert-butanol entering the submodel comes from MTBE metabolism in 

the liver, and the model does not include a separate oral intake of tert-butanol. 

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 B.2. PBPK MODEL EVALUATION SUMMARY

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B.2.1. Evaluation of Existing tert-Butanol Submodels

The Blancato et al. (2007) and Leavens and Borghoff (2009) PBPK models for MTBE were 

evaluated by comparing predictions from the tert-butanol portions of the models with the 

tert-butanol i.v. data of Poet et al. (1997) (see Figure B-2). Neither model adequately represented 

the tert-butanol blood concentrations. Modifications of model assumptions for alveolar ventilation, 

explicit pulmonary compartments, and induction of metabolism of tert-butanol did not significantly 

improve model fits to the data. Attempts to reoptimize model parameters in the tert-butanol

submodels of Blancato et al. (2007) and Leavens and Borghoff (2009) to match blood 

concentrations from the i.v. dosing study were unsuccessful. 

A) B)

Figure B-2. Comparison of the tert-butanol portions of existing MTBE models with 

tert-butanol blood concentrations from i.v. exposure by Poet et al. 1997. 

Neither the a) Blancato et al. (2007) nor the b) Leavens and Borghoff (2009) model adequately 

represents the measured tert-butanol blood concentrations.

The PBPK submodel for tert-butanol in rats was developed in acslX (Advanced Continuous 

Simulation Language, Aegis, Inc., Huntsville, Alabama) by adapting information from the many 

PBPK models that were developed in rats and humans for the structurally related substance, MTBE, 

and its metabolite tert-butanol (Borghoff et al., 2010; Leavens and Borghoff, 2009; Blancato et al., 

2007; Kim et al., 2007; Rao and Ginsberg, 1997; Borghoff et al., 1996). A brief description 

comparing the Blancato et al. (2007) and (Leavens and Borghoff, 2009) models is given, followed by 

an evaluation of the MTBE models and the assumptions adopted from MTBE models or modified in 

the tert-butanol model.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 The Blancato et al. (2007) model is an update of the earlier Rao and Ginsberg (1997) model, 

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and the Leavens and Borghoff (2009) model is an update of the Borghoff et al. (1996) model. Both 

the Blancato et al. (2007) and Leavens and Borghoff (2009) models are flow-limited models that 

predict amounts and concentrations of MTBE and its metabolite tert-butanol in blood and six tissue 

compartments: liver, kidney, fat, brain, and rapidly and slowly perfused tissues. These tissue 

compartments are linked through blood flow, following an anatomically accurate, typical, 

physiologically based description (Andersen, 1991). The parent (MTBE) and metabolite 

(tert-butanol) models are interlinked by the metabolism of MTBE to tert-butanol in the liver. Routes 

of exposure included in the models are oral and inhalation for MTBE; Leavens and Borghoff (2009)

included inhalation exposure to tert-butanol. Oral doses are assumed to be 100% bioavailable and 

100% absorbed from the gastrointestinal tract represented with a first-order rate constant. 

Following inhalation of MTBE or tert-butanol, the chemical is assumed to directly enter the 

systemic blood supply, and the respiratory tract is assumed to be at a pseudo-steady state. 

Metabolism of MTBE by CYP450s to formaldehyde and tert-butanol in the liver is described with 

two Michaelis-Menten equations representing high- and low-affinity enzymes. tert-Butanol is either 

conjugated with glucuronide or sulfate or further metabolized to acetone through MPD and HBA; 

both of these processes are described by a single Michaelis-Menten equation in the models. All of 

these model assumptions are valid for tert-butanol and were applied to the EPA-developed tertbutanol PBPK model, except for the separate brain compartment. The brain compartment was 

lumped with other richly perfused tissues in the EPA tert-butanol PBPK model.

In addition to differences in parameter values between the Blancato et al. (2007) and the 

Leavens and Borghoff (2009) models, there were three differences in the model structure: (1) the 

alveolar ventilation was reduced during exposure, (2) the rate of tert-butanol metabolism increased 

over time due to induction of CYP enzymes, and (3) binding of MTBE and tert-butanol to 

α2u-globulin was simulated in the kidney of male rats. The Blancato et al. (2007) model was 

configured through EPA’s PBPK modeling framework, ERDEM (Exposure-Related Dose Estimating 

Model), which includes explicit pulmonary compartments. The modeling assumptions related to 

alveolar ventilation, explicit pulmonary compartments, and induction of metabolism of tert-butanol

are discussed in the model evaluation section.

MTBE and tert-butanol binding to α2u-globulin in the kidneys of male rats were 

incorporated in the PBPK model of MTBE by Leavens and Borghoff (2009). Binding to α2u-globulin 

is one hypothesized MOA for the observed kidney effects in MTBE-exposed animals. For a detailed 

description of the role of α2u-globulin and other MOAs in kidney effects, see the kidney MOA section 

of this document (see Section 1.1.1). Binding of MTBE to α2u-globulin was applied to sex differences 

in kidney concentrations of MTBE and tert-butanol in the Leavens and Borghoff (2009) model, but 

acceptable estimates of MTBE and tert-butanol pharmacokinetics in the blood are predicted in 

other models that did not consider α2u-globulin binding. Given the uncertainty of tert-butanol

binding to α2u-globulin, it was not included in the tert-butanol PBPK submodel. 

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 B.2.2. Modification of Existing tert-Butanol Submodels

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To account for the tert-butanol blood concentrations after i.v. tert-butanol exposure, the 

model was modified by adding a pathway for reversible sequestration of tert-butanol in the blood. 

This could represent binding of tert-butanol to proteins in blood (see Figure B-3). The JPEC PK 

studies showed that approximately 60% of the radiolabel in whole blood is in the plasma, providing 

some limited evidence for association of tert-butanol with components in blood. The PBPK model 

represented the rate of change in the amount of tert-butanol in the sequestered blood compartment 

(Ablood2) with the following equation where KON is the binding rate constant, CV is the free tertbutanol concentration in blood, KOFF is the unbinding rate constant, and Cblood2 is the concentration 

of tert-butanol bound in blood (equal to Ablood2/Vblood).

dAblood2/dt = KON*CV* - KOFF*Cblood2

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

Exposure can be via multiple routes including inhalation, oral, or i.v. dosing. Metabolism of tertbutanol occurs in the liver and is described by Michaelis-Menten equations with one pathway for 

tert-butanol. tert-Butanol is cleared via exhalation and tert-butanol is additionally cleared via urinary 

excretion. See Table B-1 for definitions of parameter abbreviations.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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

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Body weight and organ volumes as fraction of body weight 

Body Weight (kg) 0.25 (Brown et al., 1977)

Body fraction that is blood perfused (Fperf) 0.8995 (Brown et al., 1977)

Liver 0.034 (Brown et al., 1977)

Kidney 0.007 (Brown et al., 1977)

Fat 0.07 (Brown et al., 1977)

Rapidly perfused 0.04 (Brown et al., 1977)

Slowly perfused 0.7485 a

Blood 0.074 (Brown et al., 1977)

Cardiac output and organ blood flows as fraction of cardiac output 

Cardiac output (L/hr) 5.38 (Brown et al., 1977)

b

Alveolar ventilation (L/hr) 5.38 (Brown et al., 1977)

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Liver 0.174 (Brown et al., 1977) d

Kidney 0.141 (Brown et al., 1977)

Fat 0.07 (Brown et al., 1977)

Rapidly perfused 0.279 e

Slowly perfused 0.336 (Brown et al., 1977)

Partition coefficients for tert-butanol

Blood:air 481 (Borghoff et al., 1996)

Liver:blood 0.83 (Borghoff et al., 1996)

Fat:blood 0.4 (Borghoff et al., 1996)

Rapidly perfused:blood 0.83 (Borghoff et al., 1996)

Slowly perfused:blood 1.0 (Borghoff et al., 1996)

Kidney:blood 0.83 (Borghoff et al., 1996)

a Fperf − Σ(other compartments) b 15.2*BW0.75 (bw = body weight) c Alveolar ventilation is set equal to cardiac output

d

 Sum of liver and gastrointestinal blood flows e 1 − Σ(all other compartments). 

The physiologic parameter values obtained from the literature are shown in Table B-1

(Brown et al., 1977). tert-Butanol partition coefficients were obtained from literature in which they 

were determined by the ratios of measured tissue:air and blood:air partition coefficients (Borghoff 

et al., 1996). The parameters describing rate constants of metabolism and elimination of 

tert-butanol were obtained from the literature (Blancato et al., 2007) and kept fixed because these 

have been optimized to tert-butanol blood concentrations measured after MTBE exposure, which is 

also metabolized to tert-butanol. The parameters describing tert-butanol absorption and 

tert-butanol sequestration in blood were estimated by optimizing the model to the blood tertbutanol time-course data for rats exposed via i.v., inhalation, and oral routes (Leavens and Borghoff, 

2009; Poet et al., 1997; ARCO, 1983). The model parameters were estimated with the acslX 

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Supplemental Information―tert Butanol

1 optimization routine to minimize the log-likelihood function of estimated and measured 

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tert-butanol concentrations. The Nedler-Mead algorithm was used with heteroscedasticity allowed 

to vary between 0 and 2. The predictions of the model with optimized parameters have a much 

improved fit to the tert-butanol blood concentrations after tert-butanol i.v., as shown in panel A of 

Figure B-4. Additionally, the model adequately estimated the tert-butanol blood concentrations 

after inhalation and oral gavage exposures. The optimized parameter values are shown in Table 

B-2. The ARCO (1983) study measured tert-butanol in plasma only, unlike the Poet et al. (1997) and 

Leavens and Borghoff (2009) studies that measured tert-butanol in whole blood. Based on the 

measurements of plasma and whole blood by JPEC 2008, the concentration of tert-butanol in 

plasma is approximately 60% of the concentration in whole blood. The tert-butanol plasma 

concentrations measured by ARCO were increased (divided by 60%) to the expected concentration 

in whole blood for comparison with the PBPK model.

A) B)

C)

Figure B-4. Comparison of the EPA model predictions with measured tert-butanol

blood concentrations for i.v., inhalation, and oral gavage exposure to tert-butanol. 

A) i.v. data from Poet et al. (1997); B) inhalation data from Leavens and Borghoff (2009); and C) oral 

gavage data from ARCO (1983) with the optimized parameter values as shown in Table B-2.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 Table B-2. Rate constants for tert-butanol determined by optimization of the 

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model with experimental data. 

Parameter Value Source or Reference

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

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

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

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

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

Absorption from gastrointestinal tract (KAS2; 1/hr) 0.5 Optimized

a scaled by BW0.7 (0.250.7 = 0.379), bw = body weight.

Induction of tert-butanol-metabolizing enzymes was included in the Leavens and Borghoff 

(2009) model of MTBE based on their study of rats exposed for 8 days to tert-butanol via inhalation. 

The enzyme induction equation and parameters developed in the Leavens and Borghoff (2009)

model that were applied to the tert-butanol submodel are as follows.

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

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

tert-butanol is the metabolism rate constant from Table B-2 for both tert-butanol pathways, and 

INDMAX is the maximum percent increase in Vmax tert-butanol (124.9). KIND is the rate constant 

for enzyme induction (0.3977/day). The increased tert-butanol metabolism better estimates the 

measured tert-butanol blood concentrations as can be seen in the comparison of the model 

predictions and experimental measurements shown in Figure B-5. The model better predicted 

blood concentrations in female rats than male rats. The male rats had lower tert-butanol blood 

concentrations after repeated exposures compared with female rats, and this difference could 

indicate greater induction of tert-butanol metabolism or other physiologic changes such as 

ventilation or urinary excretion in males. The current data for tert-butanol metabolism do not 

provide sufficient information for resolving this difference between male and female rats. 

B.2.3. Summary of the PBPK model for tert-butanol 

A PBPK model for tert-butanol was developed by adapting previous models for MTBE and 

tert-butanol (Blancato et al. (2007); Leavens and Borghoff (2009)). Published tert-butanol models 

(or sub-models) do not adequately represent the tert-butanol blood concentrations measured in 

the i.v. study (Poet et al. 1997). The addition of a sequestered blood compartment for tert-butanol 

substantially improved the model fit. The alternative modification of changing to diffusion-limited 

distribution between blood and tissues also improved the model fit, but was considered less 

biologically plausible. Physiological parameters and partition coefficients were obtained from 

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1 published measurements. The rate constants for tert-butanol metabolism and elimination were 

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from a published PBPK model of MTBE with a tert-butanol subcompartment (Blancato et al. 

(2007)). Additional model parameters were estimated by calibrating to data sets for i.v., oral and 

inhalation exposures as well as repeated dosing studies for TBA. Overall, the model produced 

acceptable fits to multiple rat time-course datasets of TBA blood levels following either inhalation 

or oral gavage exposures. 

B.2.4. tert-Butanol Model Application

The PBPK model as described above was applied to toxicity studies to predict tert-butanol

blood concentrations (the preferred internal dose metric). For simulation studies where tertbutanol was administered in drinking water, the consumption was modeled as episodic, based on 

the pattern of drinking observed in rats (Spiteri, 1982). 

B.2.5. PBPK Model Code

The PBPK acslX model code is made available electronically through EPA’s Health and 

Environmental Research Online (HERO) database. All model files may be downloaded in a zipped 

workspace from HERO (U.S. EPA, 201#, HEROID##).

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

Male rats were exposed to 239, 444, or 1726 ppm and female rats were exposed to 256, 444, or 

1914 ppm tert-butanol for up to 8 consecutive days (Borghoff et al., 2001). tert-Butanol blood 

concentrations are better predicted by the model after 8 days of exposure with enzyme induction 

(right panels) compared to without enzyme induction (left panels).

B.3. OTHER PERTINENT TOXICITY INFORMATION

B.3.1. Genotoxicity 

The genotoxic potential of tert-butanol has been studied using a variety of genotoxicity 

assays, including bacterial reverse mutation assays, gene mutation assays, chromosomal 

aberrations, sister chromatid exchanges, micronucleus formation, and DNA strand breaks and 

adducts. The available genotoxicity data for tert-butanol are discussed below, and the summary of 

the data is provided in Table B-3. 

B.3.1.1. Bacterial Systems

The mutagenic potential of tert-butanol has been tested by Zeiger et al. (1987) using 

different Salmonella typhimurium strains both in the presence and absence of S9 metabolic 

activation. The preincubation assay protocol was followed. Salmonella strains TA98, TA100, 

TA1535, TA1537, and TA1538 were exposed to five concentrations (100, 333, 1,000, 3,333, or 

10,000 μg/plate) and tested in triplicate. No mutations were observed in any of the strains tested, 

either in the presence or absence of S9 metabolic activation. 

Conflicting results have been obtained with tert-butanol-induced mutagenicity in strain 

TA102, a strain that is sensitive to damage at A-T sites inducible by oxidants and other mutagens 

and is excision-repair proficient. In a study by Williams-Hill et al. (1999), tert-butanol induced an 

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1 increase in the number of revertants in the first three concentrations with S9 activation in a dose2 

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response manner. The number of revertants decreased in the last two concentrations. No 

discussion was provided as to why the revertants decreased at higher concentrations. The results of 

this study indicated that tester strain TA102 may be a more sensitive strain for monitoring tertbutanol levels (Williams-Hill et al., 1999). However, in another study by Mcgregor et al. (2005), 

experiments were conducted on Salmonella strain TA102 in two different laboratories using similar 

protocols. tert-Butanol was dissolved in dimethyl sulfoxide (DMSO) or distilled water and tested 

both in the presence and absence of S9 metabolic activation. No statistically significant increase in 

mutants was observed in either of the solvent media. In one experiment where tert-butanol was 

dissolved in water, a significant, dose-related increase in the number of revertants was produced, 

reaching almost two-fold the control value at a concentration of 2,250 μg/plate. It should be noted 

that DMSO is known to be a free radical scavenger, and its presence at high concentrations might 

mask a mutagenic response caused due to oxidative damage. 

Mutagenicity of tert-butanol has been studied in other systems including Neurospora crassa

and Saccharomyces cerevisiae. Yeast strain Neurospora crassa at the ad-3A locus (allele 38701) was 

used to test the mutagenic activity of tert-butanol at a concentration of 1.75 mol/L for 30 minutes.

tert-Butanol did not induce reverse mutations in the tested strain at the exposed concentration 

(Dickey et al., 1949). On the other hand, tert-butanol, without exogenous metabolic activation, 

significantly increased the frequency of petite mutations (the mitochondrial deoxyribonucleic acid 

[DNA] deletion rho−) in Saccharomyces cerevisiae laboratory strains K5-A5, MMY1, D517-4B, and 

DS8 (Jimenez et al., 1988). This effect on mitochondrial DNA, also observed with ethanol and other 

solvents, was attributed by the study authors to the alteration in the lipid composition of 

mitochondrial membranes, and mitochondrial DNA’s close association could be affected by 

membrane composition (Jimenez et al., 1988). 

B.3.1.2. In Vitro Mammalian Studies

To understand the role of tert-butanol-induced genotoxicity in mammalian systems, in vitro

studies have been conducted in different test systems and assays. tert-Butanol was tested to 

evaluate its ability to induce forward mutations at the thymidine kinase locus (tk) in the L5178Y 

tk+/- mouse lymphoma cells using forward mutation assay. Experiments were conducted both in 

the presence and absence of S9 metabolic activation. The mutant frequency was calculated using 

the ratio of mutant clones per plate/total clones per plate × 200. tert-Butanol did not reliably 

increase the frequency of forward mutations in L5178Y tk+/− mouse lymphoma cells with or 

without metabolic activation, although one experiment without addition of S9 yielded a small 

increase in mutant fraction at the highest tested concentration (5,000 μg/mL) (McGregor et al., 

1988). 

To further determine potential DNA and/or chromosomal damage induced by tert-butanol 

in in vitro systems, (NTP, 1995) studied sister chromatid exchanges (SCEs) and chromosomal 

aberrations (CAs). Chinese hamster ovary (CHO) cells were exposed to tert-butanol both in the 

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1 presence and absence of S9 activation at concentrations of 160–5,000 μg/mL for 26 hours. tert2 

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Butanol did not induce SCEs in any of the concentrations tested, although in one experiment, there 

was a slight increase in percent relative change of SCEs per chromosome scored. The same authors 

also studied the effect of tert-butanol on CA formation. CHO cells were exposed to four 

concentrations (160, 500, 1,600, or 5,000 μg/mL) of tert-butanol both in the presence and absence 

of S9. No significant increase in CAs was observed in any of the concentrations tested. It should be 

noted that due to severe toxicity at the highest concentration (5,000 μg/mL), only 13 metaphase 

cells were scored instead of 100 in the chromosomal aberration assay.

Sgambato et al. (2009) examined the effects of tert-butanol on DNA damage using normal 

diploid rat fibroblast cell line. Cells were treated with 0- to 100-mM tert-butanol for 48 hours to 

determine the half maximal inhibitory concentration (IC50; 0.44 ± 0.2 mM). The 48-hour IC50

concentration was then used to determine DNA content, cell number, and phases of the cell cycle 

after 24 and 48 hours of exposure. Total protein and DNA oxidative damage were also measured. A 

comet assay was used to evaluate DNA fragmentation at time 0 and after 30 minutes, 4 hours, or 12 

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

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

concentrations, as well as with concentrations at 1/10th the IC50. There was no increase in cell 

death, suggesting a reduction in cell number due to reduced replication rather than cytotoxicity.

tert-Butanol caused an accumulation in the G0/G1 phase of replication. These were related to 

different effects on the expression of cyclin D1, p27Kip1, and p53 genes. An initial increase in DNA 

damage as measured by nuclear fragmentation was observed at the 30-minute timepoint. The DNA 

damage declined drastically after 4 hours and disappeared almost entirely after 12 hours of 

exposure to tert-butanol. This reduction in the extent of DNA fragmentation after the initial 

increase is likely the result of an efficient DNA repair mechanism activated by cells following DNA 

damage induced by tert-butanol. 

DNA damage caused by tert-butanol was determined by single-cell gel electrophoresis 

(comet assay) in human promyelocytic leukemia (HL-60) cells. The cells were exposed to 

concentrations ranging from 1 to 30 mmol/L for 1 hour, and a total of 100 cells were evaluated for 

DNA fragmentation. A dose-dependent increase in DNA damage was observed between 1 and 

30 mmol/L. No cytotoxicity was observed at the concentrations tested (Tang et al., 1997). 

B.3.1.3. In Vivo Mammalian Studies

A limited number of in vivo studies are available to understand the role of tert-butanol on 

genotoxicity. The National Toxicology Program studied the effect of tert-butanol in a 13-week 

toxicity study (NTP, 1995). Peripheral blood samples were obtained from male and female B6CF1 

mice that were exposed to tert-butanol in drinking water at doses of 3,000–40,000 ppm. Slides 

were prepared to determine the frequency of micronuclei in 10,000 normochromatic erythrocytes. 

In addition, the percentage of polychromatic erythrocytes among the total erythrocyte population 

was determined. No increase in micronucleus formation in peripheral blood lymphocytes was 

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1 observed either in male or female B6C3F1 mice exposed for 13 weeks to tert-butanol in drinking 

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water at concentrations as high as 40,000 ppm (2,110 mg/kg-day) (NTP, 1995). 

Male Kumming mice (8 per treatment) were administered 0, 0.099, 0.99, 10, 101, or 

997 μg/kg bw 14C-tert-butanol in saline via gavage with specific activity ranging from 1.60 to 

0.00978 mCi/mol (Yuan et al., 2007). Animals were sacrificed 6 hours after exposure, and liver, 

kidney, and lung were collected. Tissues were prepared for DNA isolation with samples from the 

same organs from every two mice combined. DNA adducts were measured using accelerated mass 

spectrometry. The results of this study showed a dose-response increase in DNA adducts in all 

three organs measured, although the methodology used to detect DNA adducts is considered 

sensitive but may be nonspecific. The authors stated that tert-butanol was found, for the first time, 

to form DNA adducts in mouse liver, lung, and kidney. Because this is a single and first-time study, 

further validation of this study will provide certainty in understanding the mechanism of tertbutanol-induced DNA adducts. 

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1 Table B-3. Summary of genotoxicity (both in vitro and in vivo) studies of tert2 butanol. 

Test system Dose/Conc. Resultsa Comments Reference

Bacterial Systems

-S9 +S9

Reverse Mutation Assay

Salmonella typhimurium

(TA98, TA100, TA1535, 

TA1537, TA1538)

100, 333, 1000, 

3333, 10,000 

μg/plate

- - Preincubation procedure was 

followed. This study was part of 

the NTP 1995 testing results.

Zeiger et al. 

(1987);NTP 

(1995)

Reverse Mutation Assay

Salmonella typhimurium

(TA102)

1000–4000

μg/plate

ND + Only tested with S9 activation Williams-Hill et 

al. (1999)

Reverse Mutation Assay

Salmonella typhimurium

(TA98, TA100, TA102, 

TA1535, TA1537)

5, 15, 50, 100, 150, 

200, 500, 1000, 

1500, 2500, 5000

μg/plate

- - Experiments conducted in two 

different laboratories, two 

vehicles – distilled water and 

DMSO were used, different 

concentrations were used in 

experiments from different 

laboratories

Mcgregor et al. 

(2005)

Reverse mutation

Neurospora crassa, ad-3A 

locus (allele 38701)

1.75mol/L - - Eighty four percent cell death 

was observed; note it is a 1949 

study

Dickey et al. 

(1949)

Mitochondrial mutation 

Saccharomyces cerevisiae

(K5-5A, MMY1, D517-4B, 

and DS8)

4.0% (vol/vol) +

b ND Mitochondrial mutations, 

membrane solvent

Jimenez et al. 

(1988)

In vitro Systems

Gene Mutation Assay, 

Mouse lymphoma cells 

L5178Y TK+/–

625, 1000, 1250, 

2000, 3000, 4000, 

5000 μg/mL 

- - Cultures were exposed for 4 h, 

then cultured for 2 days before 

plating in soft agar with or 

without trifluorothymidine, 

3 μg/mL; this study was part of 

the NTP 1995 testing results

McGregor et al. 

(1988);NTP 

(1995)

Sister-chromatid exchange, 

Chinese Hamster Ovary cells

160, 500, 1600, 

2000, 3000, 4000, 

5000 μg/mL

- - 

This study was part of the NTP 

1995 testing results

Galloway, 1987;

NTP (1995)

Chromosomal Aberrations, 

Chinese Hamster Ovary cells

160, 500, 1600, 

2000, 3000, 4000, 

5000 μg/mL

- - This study was part of the NTP 

1995 testing results

Galloway, 1987 

NTP (1995)

DNA damage (comet assay), 

Rat fibroblasts

0.44 mmol/L (IC50) +

c ND Exposure duration – 30 min, 

4 h, 12 h; this study provides 

other information on effect of 

cell cycle control genes and 

mechanism of action for TBA

Sgambato et al. 

(2009)

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Test system Dose/Conc. Resultsa Comments Reference

DNA damage, (comet 

assay), human HL-60 

leukemia cells

1, 5, 10, 30 mmol/L + ND Exposure duration – 1h Tang et al. 

(1997)

In vivo Animal Studies

Micronucleus formation, 

B6C3F1 mouse peripheral 

blood cells

3000, 5000, 

10,000, 20,000, 

40,000 ppm

- 13-week, subchronic, drinking 

water study

NTP (1995)

DNA adducts, male 

Kunming mouse liver, 

kidney and lung cells

0.1–1000 μg/kg 

body weight + 

Gavage, 6-h exposure, DNA 

adduct determined by 

accelerator mass spectrometry

Yuan et al. 

(2007)

a 1 + = positive; − = negative; ND = not determined. 

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b

Effect is predicted to be due to mitochondrial membrane composition. c

DNA damage was completely reversed with increased exposure time. 

B.3.2. Summary

tert-Butanol has been tested for its genotoxic potential using a variety of genotoxicity 

assays. Bacterial assays that detect reverse mutations have been thought to predict carcinogenicity 

with accuracy up to 80%. tert-Butanol did not induce mutations in most bacterial strains; however, 

when tested in TA102, a strain that is sensitive to damage at A-T sites inducible by oxidants, an 

increase in mutants was observed at low concentrations, although conflicting results were reported 

in another study. Furthermore, the solvent (e.g., distilled water or DMSO) used in the genotoxicity 

assay may impact results. In one experiment where tert-butanol was dissolved in distilled water, a 

significant, dose-related increase in the number of mutants was observed, with the maximum value 

reaching almost 2-fold the control value. DMSO is known to be a radical scavenger, and its presence 

in high concentrations might mask a mutagenic response modulated by oxidative damage. Other 

species such as Neurospora crassa did not produce reverse mutations as a result of exposure to tertbutanol. 

tert-Butanol was tested in several human and animal in vitro mammalian systems for 

genotoxicity (gene mutation, sister chromatid exchanges, chromosomal aberrations, and DNA 

damage). No increase in gene mutations was observed in mouse lymphoma cells (L5178Y TK+/–). 

These specific locus mutations in mammalian cells are used to demonstrate and quantify genetic 

damage, thereby confirming or extending the data obtained in the more widely used bacterial cell 

tests. Sister chromatid exchange or chromosomal aberrations were not observed in CHO cells in 

response to tert-butanol treatment. However, DNA damage was detected using comet assay in both 

rat fibroblasts and human HL-60 leukemia cells, with either an increase in DNA fragmentation at 

the beginning of the exposure or dose-dependent increase in DNA damage observed. An initial 

increase in DNA damage was observed at 30 minutes that declined drastically following 4 hours of 

exposure and disappeared almost entirely after 12 hours of exposure to tert-butanol. This 

reduction in the extent of DNA fragmentation after an initial increase is likely the result of an 

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1 efficient DNA repair mechanism activated by cells following DNA damage induced by tert-butanol. A 

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dose-dependent increase in DNA damage was observed in human cells tested; however, because

the exposure occurred for only 1 hour in this study, it is not possible to discern whether DNA-repair 

mechanisms would occur after a longer period of observation. 

Limited in vivo animal studies have been conducted on DNA adduct formation or 

micronucleus formation. A dose-response increase in DNA adducts was observed in mouse liver, 

kidney, and lung cells. The authors used accelerated mass spectrometry to detect DNA adducts, but 

this method may be sensitive and not specific to the adducts in question. The method uses 

14C-labeled chemical for dosing, and the isolated DNA is oxidized to carbon dioxide and reduced to 

filamentous graphite, and the ratios of 14C/12C are measured. The ratio is then converted to DNA 

adducts based on nucleotide content of the DNA, hence the debate for the reliability of the data 

obtained. Confirmation of this data will provide assurance in understanding the mechanism of 

tert-butanol-induced DNA adducts. No increase in micronucleus formation was observed in mouse 

peripheral blood cells in a 13-week drinking water study conducted by the National Toxicology 

Program. 

Overall, there is a limited database to understand the role of tert-butanol-induced 

genotoxicity for mode of action and carcinogenicity. The database is limited either in terms of the 

array of genotoxicity tests conducted or the number of studies within the same type of test. In 

addition, the results are either conflicting or inconsistent. The test strains, solvents, or control for 

volatility used in certain studies are variable and may impact results. Furthermore, in some studies, 

the methodology used has been challenged for its specificity. Given the inconsistencies and 

limitations of the database in terms of the methodology used, number of studies in the overall 

database, coverage of studies across the genotoxicity battery, and the quality of the studies, the 

weight of evidence analysis is inconclusive. The available data do not inform a definitive conclusion

on the genotoxicty of tert-butanol and thus the potential genotoxic effects of tert-butanol cannot be 

discounted. 

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1 APPENDIX C. DOSE-RESPONSE MODELING FOR 

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THE DERIVATION OF REFERENCE VALUES FOR 

EFFECTS OTHER THAN CANCER AND THE 

DERIVATION OF CANCER RISK ESTIMATES

C.1. BENCHMARK DOSE MODELING SUMMARY

This appendix provides technical detail on dose-response evaluation and determination of

points of departure (PODs) for relevant endpoints. The endpoints were modeled using EPA’s 

Benchmark Dose Software (BMDS), version 2.1.2. The preambles for the cancer and noncancer 

parts below describes the common practices used in evaluating the model fit and selecting the 

appropriate model for determining the POD as outlined in the Benchmark Dose Technical Guidance 

Document (U.S. EPA, 2000). In some cases, it may be appropriate to use alternative methods based 

on statistical judgment; exceptions are noted as necessary in the summary of the modeling results. 

C.1.1. Noncancer Endpoints

C.1.1.1. Evaluation of Model Fit

For each dichotomous endpoint, BMDS dichotomous models were fitted to the data using 

the maximum likelihood method. Each model was tested for goodness-of-fit using a chi-square 

goodness-of-fit test (χ2 p-value < 0.10 indicates lack of fit). Other factors were also used to assess 

model fit, such as scaled residuals, visual fit, and adequacy of fit in the low dose region and near the 

benchmark response (BMR). 

For each continuous endpoint, BMDS continuous models were fitted to the data using the 

maximum likelihood method, and model fit was assessed by a series of tests. For each model, first 

the homogeneity of the variances was tested using a likelihood ratio test (BMDS Test 2). If Test 2 

was not rejected (χ2 p-value ≥ 0.10), the model was fitted to the data assuming constant variance. If 

Test 2 was rejected (χ2 p-value < 0.10), the variance was modeled as a power function of the mean, 

and the variance model was tested for adequacy of fit using a likelihood ratio test (BMDS Test 3).

For fitting models using either constant variance or modeled variance, models for the mean 

response were tested for adequacy of fit using a likelihood ratio test (BMDS Test 4, with χ2

p-value < 0.10 indicating inadequate fit). Other factors were also used to assess the model fit, such 

as scaled residuals, visual fit, and adequacy of fit in the low-dose region and near the BMR. 

C.1.1.2. Model Selection

For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as 

estimated by the profile likelihood method) and the Akaike’s information criterion (AIC) value were 

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1 used to select a best-fit model from among the models exhibiting adequate fit. If the BMDL 

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estimates were “sufficiently close,” that is, differed by at most 3-fold, the model selected was the 

one that yielded the lowest AIC value. If the BMDL estimates were not sufficiently close, the lowest 

BMDL was selected as the POD. 

Table C-1. Non-cancer endpoints selected for dose-response modeling for 

tert-butanol

Endpoint/Study

Species / 

Sex Doses and Effect Data

Kidney transitional 

epithelial 

hyperplasia

NTP (1995)

Rat (F344) 

/ Male

Dose (mg/kg-d) 0 90 200 420

Incidence / 

Total 25 / 50 32 / 50 36 / 50 40 / 50

Kidney transitional

epithelial 

hyperplasia

NTP (1995)

Rat (F344) 

/ Female

Dose (mg/kg-d) 0 180 330 650

Incidence / 

Total 0 / 50 0 / 50 3 / 50 17 / 50

Mean relative 

kidney weight

NTP (1995)

Rat (F344) 

/ Male

Dose (mg/kg-d) 0 90 200 420

Mean ± SE (n) 3.68 ± 0.09

(10)

3.96 ± 0.13

(10)

4.22 ± 0.13

(10)

4.42 ± 0.15

(10)

Mean relative 

kidney weight

NTP (1995)

Rat (F344) 

/ Female

Dose (mg/kg-d) 0 180 330 650

Mean ± SE (n) 3.49 ± 0.08 

(10)

3.99 ± 0.07 

(10)

4.21 ± 0.08 

(10)

4.95 ± 0.17 

(10)

Kidney 

inflammation

NTP (1995)

Rat (F344) 

/ Female

Dose (mg/kg-d) 0 180 330 650

Incidence / 

Total 2 / 50 3 / 50 13 / 50 17 / 50

Thyroid follicular 

cell hyperplasia

NTP (1995)

Mouse 

(B6C3F1) / 

Male

Dose (mg/kg-d) 0 540 1,040 2,070

Incidence / 

Total 5 / 60 18 / 59 15 / 59 18 / 57

Thyroid follicular 

cell hyperplasia

NTP (1995)

Mouse 

(B6C3F1) / 

Female

Dose (mg/kg-d) 0 510 1,020 2,110

Incidence / 

Total 19 / 58 28 / 60 33 / 59 47 / 59

Increased absolute 

kidney weight

NTP (1997)

Rat (F344) 

/ Male

Concentration 

(mg/m3) 0 406 825 1643 3274 6369

Mean ± SD (n)

1.21 ± 

0.082 

(10)

1.21 ±

0.096

(9)

1.18 ± 

0.079 

(10)

1.25 ±

0.111 

(10)

1.34 ±

0.054 

(10)

1.32 ±

0.089 

(10)

Increased relative 

kidney weight

NTP (1997)

Rat (F344) 

/ Male

Concentration 

(mg/m3) 0 406 825 1643 3274 6369

Mean ± SD (n)

3.68 ± 

0.253 

(10)

3.71 ±

0.12

(9)

3.64 ±

0.126 

(10)

3.76 ±

0.19

(10)

3.96 ±

0.158

(10)

4 ±

0.158 

(10) 

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Endpoint/Study

Species / 

Sex Doses and Effect Data

Increased absolute 

kidney weight

NTP (1997)

Rat (F344) 

/ Female

Concentration 

(mg/m3) 0 406 825 1643 3274 6369

Mean ± SD (n)

0.817 ±

0.136

(10)

0.782 ±

0.063

(10)

0.821 ±

0.061

(10)

0.853 ±

0.045

(10)

0.831 ±

0.054

(10)

0.849 ±

0.038

(10)

Increased relative 

kidney weight

NTP (1997)

Rat (F344) 

/ Female

Concentration 

(mg/m3) 0 406 825 1643 3274 6369

Mean ± SD (n)

4.00 ± 

0.474

(10)

3.98 ± 

0.190

(10)

4.03 ± 

0.158

(10)

4.14 ± 

0.126

(10)

4.09 ±

0.190

(10)

4.35 ±

0.095

(10)

1 C.1.1.3. Modeling Results

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Below are tables summarizing the modeling results for the noncancer endpoints modeled.

The following parameter restrictions were applied, unless otherwise noted. 

• Dichotomous models: For the log-logistic and dichotomous Hill models, restrict slope ≥ 

1; for the gamma and Weibull models, restrict power ≥ 1; for the multistage models, 

restrict beta values ≥ 0. 

• Continuous models: For the polynomial models, restrict beta values ≥ 0; for the Hill, 

power, and exponential models, restrict power ≥ 1. 

Table C-2. Summary of BMD modeling results for kidney transitional epithelial 

hyperplasia in male F344 rats exposed to tert-butanol in drinking water for 2 

years (NTP, 1995); BMR = 10% extra risk.

Model a

Goodness of fit BMD10

(mg/kg-d)

BMDL10

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

Log-logistic 0.976 248.0 30 16 Log-logistic model selected as 

best-fitting model based on 

lowest AIC with all BMDL values 

sufficiently close (BMDLs 

differed by slightly more than 3-

fold).

Gamma 0.784 248.5 46 29

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

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, 

respectively. 

This document is a draft for review purposes only and does not constitute Agency policy.

C-3 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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Log-Logistic Model with 0.95 Confidence Level

17:16 05/13 2011

BMDL BMD

 

Log-Logistic

This document is a draft for review purposes only and does not constitute Agency policy.

C-4 DRAFT—DO NOT CITE OR QUOTE

Figure C-1. Plot of mean response by dose, with fitted curve for selected model.
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==================================================================== 

 Logistic Model. (Version: 2.13; Date: 10/28/2009) 

 Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\17 NTP 1995b_Kidney 

transitional epithelial hyperplasia, male rats_LogLogistic_10.(d)

 Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\17 NTP 

1995b_Kidney transitional epithelial hyperplasia, male rats_LogLogistic_10.plt

 Fri May 13 17:16:25 2011

==================================================================== 

[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the probability function is: 

 P[response] = background+(1-background)/[1+EXP(-intercept-slope*Log(dose))]

 Dependent variable = Incidence

 Independent variable = Dose

 Slope parameter is restricted as slope >= 1

 Total number of observations = 4

 Total number of records with missing values = 0

 Maximum number of iterations = 250

 Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008

 User has chosen the log transformed model

 Default Initial Parameter Values 

 background = 0.5

 intercept = -5.54788

 slope = 1 

 Asymptotic Correlation Matrix of Parameter Estimates

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user,

 and do not appear in the correlation matrix )

 background intercept

background 1 -0.71

intercept -0.71 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 background 0.505366 * * * 

 intercept -5.58826 * * * 

 slope 1 * * * 

* - Indicates that this value is not calculated.

 Analysis of Deviance Table

 Model Log(likelihood) # Param's Deviance Test d.f. P-value

 Full model -121.996 4 

 Fitted model -122.02 2 0.048148 2 0.9762

Reduced model -127.533 1 11.0732 3 0.01134

This document is a draft for review purposes only and does not constitute Agency policy.

C-5 DRAFT—DO NOT CITE OR QUOTE
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 AIC: 248.04

 Goodness of Fit 

 Scaled

 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

 0.0000 0.5054 25.268 25.000 50 -0.076

 90.0000 0.6300 31.498 32.000 50 0.147

200.0000 0.7171 35.854 36.000 50 0.046

420.0000 0.8076 40.382 40.000 50 -0.137

Chi^2 = 0.05 d.f. = 2 P-value = 0.9762

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk 

Confidence level = 0.95

 BMD = 29.6967

 BMDL = 15.6252

Table C-3. Summary of BMD modeling results for kidney transitional epithelial 

hyperplasia in female F344 rats exposed to tert-butanol in drinking water for 

2 years (NTP, 1995); BMR = 10% extra risk.

Modela

Goodness of fit

BMD10 

(mg/kg-d)

BMDL10

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

Gamma 0.83 91.41 409 334 Multistage 3rd order model 

selected as best-fitting model 

based on lowest AIC with all 

BMDL values sufficiently close 

(BMDLs differed by less than 3-

fold).

Logistic 0.50 92.81 461 393

LogLogistic 0.79 91.57 414 333

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 Error c Error c

a

Scaled residuals for selected model for doses 0, 180, 330, and 650 mg/m3 were 0.0, –0.664, 0.230, and 0.016, 

respectively. b

No available degrees of freedom to estimate a p-value. c

BMD and BMDL computation failed for the Dichotomous-Hill model.

This document is a draft for review purposes only and does not constitute Agency policy.

C-6 DRAFT—DO NOT CITE OR QUOTE
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Multistage Model with 0.95 Confidence Level

17:18 05/13 2011

BMDL BMD

 

Multistage

This document is a draft for review purposes only and does not constitute Agency policy.

C-7 DRAFT—DO NOT CITE OR QUOTE

Figure C-2. Plot of mean response by dose, with fitted curve for selected model. 

==================================================================== 

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

 Input Data File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\20 NTP 

1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.(d)

 Gnuplot Plotting File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\20 NTP 

1995b_Kidney transitional epithelial hyperplasia, female rats_Multi3_10.plt

 Mon May 09 18:31:33 2011

==================================================================== 

[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)]

 The parameter betas are restricted to be positive

Dependent variable = Incidence

Independent variable = Dose

Total number of observations = 4

Total number of records with missing values = 0

Total number of parameters in model = 4

Total number of specified parameters = 0

Degree of polynomial = 3

Maximum number of iterations = 250

Relative Function Convergence has been set to: 1e-008

Parameter Convergence has been set to: 1e-008

 Default Initial Parameter Values 

 Background = 0 

 Beta(1) = 0 

 Beta(2) = 1.51408e-007

 Beta(3) = 1.29813e-009

 Asymptotic Correlation Matrix of Parameter Estimates
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 ( *** The model parameter(s) -Background -Beta(1) -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user,

 and do not appear in the correlation matrix )

 Beta(3)

 Beta(3) 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 Background 0 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0 * * * 

 Beta(3) 1.50711e-009 * * * 

* - Indicates that this value is not calculated.

 Analysis of Deviance Table

 Model Log(likelihood) # Param's Deviance Test d.f. P-value

 Full model -43.4002 4 

 Fitted model -43.8652 1 0.9301 3 0.8182

Reduced model -65.0166 1 43.2329 3 <.0001

 AIC: 89.7304

 Goodness of Fit 

 Scaled

 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

 0.0000 0.0000 0.000 0.000 50 0.000

180.0000 0.0088 0.438 0.000 50 -0.664

330.0000 0.0527 2.636 3.000 50 0.230

650.0000 0.3389 16.946 17.000 50 0.016

Chi^2 = 0.49 d.f. = 3 P-value = 0.9200

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk 

Confidence level = 0.95

 BMD = 411.95

 BMDL = 338.618

 BMDU = 469.73

Taken together, (338.618, 469.73 ) is a 90 % two-sided confidence

interval for the BMD

This document is a draft for review purposes only and does not constitute Agency policy.

C-8 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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Table C-4. Summary of BMD modeling results for relative kidney weights in 

male F344 rats exposed to tert-butanol in drinking water for 15 months (NTP, 

1995); BMR = 10% relative deviation and 1 standard deviation.

Modela

Goodness of fit

BMD10%

(mg/kg-d)

BMDL10%

(mg/kg-d)

BMD1SD

(mg/kg-d)

BMDL1SD

(mg/kg-d)

Basis for model 

p-value AIC selection

Hill NA -27.27 120 39 124 45 Exponential (M4) is 

selected as the 

best-fitting model 

based on visual fit 

at the low-dose 

region.

Exponential 

(M4) 0.854 -29.23 117 48 123 53

Exponential 

(M5) N/A -27.27 121 48 126 54

Linear 0.421 -29.54 222 155 229 161

Polynomial 0.421 -29.54 222 155 229 161

Power 0.421 -29.54 222 155 229 161

Exponential 

(M2) 0.365 -29.25 236 170 243 176

Exponential 

(M3) 0.365 -29.25 236 170 243 176

a

Constant variance case presented (BMDS Test 2 p-value = 0.466), selected model in bold; scaled residuals for 

selected model for doses 0, 90, 200, 420 mg/kg-d were 0.04009, -0.1264, 0.122, and -0.03578, respectively.

This document is a draft for review purposes only and does not constitute Agency policy.

C-9 DRAFT—DO NOT CITE OR QUOTE
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This document is a draft for review purposes only and does not constitute Agency policy.

C-10 DRAFT—DO NOT CITE OR QUOTE

Figure C-3. Plot of mean response by dose, with fitted curve for selected model (10% 

relative deviation). 

==================================================================== 

 Exponential Model. (Version: 1.7; Date: 12/10/2009) 

 Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\21 NTP 

1995b_Mean relative kidney weight, male rats_ExpCV_10RD.(d) 

 Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\21 NTP 

1995b_Mean relative kidney weight, male rats_ExpCV_10RD.plt

 Fri May 13 16:30:21 2011

==================================================================== 

[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the response function by Model: 

 Model 2: Y[dose] = a * exp{sign * b * dose}

 Model 3: Y[dose] = a * exp{sign * (b * dose)^d}

 Model 4: Y[dose] = a * [c-(c-1) * exp{-b * dose}]

 Model 5: Y[dose] = a * [c-(c-1) * exp{-(b * dose)^d}]

 Note: Y[dose] is the median response for exposure = dose;

 sign = +1 for increasing trend in data;

 sign = -1 for decreasing trend.

 Model 2 is nested within Models 3 and 4.

 Model 3 is nested within Model 5.

 Model 4 is nested within Model 5.

 Dependent variable = Response

Independent variable = Dose

Data are assumed to be distributed: normally

Variance Model: exp(lnalpha +rho *ln(Y[dose]))

 rho is set to 0.

A constant variance model is fit.

Total number of dose groups = 4

Total number of records with missing values = 0

Maximum number of iterations = 250

Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008
Supplemental Information―tert Butanol

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 MLE solution provided: Exact

 Initial Parameter Values

 Variable Model 4

 -------- --------

 lnalpha -1.93171

 rho(S) 0 

 a 3.496

 b 0.00417714

 c 1.32752

 d 1

 (S) = Specified

 Parameter Estimates

 Variable Model 4

 -------- -------

 lnalpha -1.93087

 rho 0 

 a 3.67517

 b 0.00469937

 c 1.23673

 d 1 

 Table of Stats From Input Data

 Dose N Obs Mean Obs Std Dev

 ----- --- ---------- -------------

 0 10 3.68 0.2846

 90 10 3.96 0.4111

 200 10 4.22 0.4111

 420 10 4.42 0.4743

 Estimated Values of Interest

 Dose Est Mean Est Std Scaled Residual

 ------ ---------- --------- ----------------

 0 3.675 0.3808 0.04009

 90 3.975 0.3808 -0.1264

 200 4.205 0.3808 0.1221

 420 4.424 0.3808 -0.03578

 Other models for which likelihoods are calculated:

 Model A1: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma^2

 Model A2: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma(i)^2

 Model A3: Yij = Mu(i) + e(ij)

 Var{e(ij)} = exp(lalpha + log(mean(i)) * rho)

 Model R: Yij = Mu + e(i)

 Var{e(ij)} = Sigma^2

 Likelihoods of Interest

 Model Log(likelihood) DF AIC

 ------- ----------------- ---- ------------

This document is a draft for review purposes only and does not constitute Agency policy.

C-11 DRAFT—DO NOT CITE OR QUOTE
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 A1 18.63423 5 -27.26846

 A2 19.91058 8 -23.82116

 A3 18.63423 5 -27.26846

 R 10.08355 2 -16.1671

 4 18.61733 4 -29.23465

Additive constant for all log-likelihoods = -36.76. This constant added to the

above values gives the log-likelihood including the term that does not

depend on the model parameters.

 Explanation of Tests

Test 1: Does response and/or variances differ among Dose levels? (A2 vs. R)

Test 2: Are Variances Homogeneous? (A2 vs. A1)

Test 3: Are variances adequately modeled? (A2 vs. A3)

Test 6a: Does Model 4 fit the data? (A3 vs 4)

 Tests of Interest

Test -2*log(Likelihood Ratio) D. F. p-value

-------- ------------------------ ------ --------------

Test 1 19.65 6 0.00319

Test 2 2.553 3 0.4658

Test 3 2.553 3 0.4658

Test 6a 0.03381 1 0.8541

The p-value for Test 1 is less than .05. There appears to be a

difference between response and/or variances among the dose

levels, it seems appropriate to model the data.

The p-value for Test 2 is greater than .1. A homogeneous

variance model appears to be appropriate here.

The p-value for Test 3 is greater than .1. The modeled

variance appears to be appropriate here.

The p-value for Test 6a is greater than .1. Model 4 seems

to adequately describe the data.

Benchmark Dose Computations:

Specified Effect = 0.100000

 Risk Type = Relative deviation

Confidence Level = 0.950000

 BMD = 116.807

 BMDL = 48.0466

This document is a draft for review purposes only and does not constitute Agency policy.

C-12 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-5. Summary of BMD modeling results for relative kidney weights in 

2 

3 

female F344 rats exposed to tert-butanol in drinking water for 15 months

(NTP, 1995); BMR = 10% relative deviation and 1 standard deviation.

Modela

Goodness of fit BMD10%

(mg/kg-d)

BMDL10%

(mg/kg-d)

BMD1SD

(mg/kg-d)

BMDL1SD

(mg/kg-d)

Basis for model 

p-value AIC selection

Exponential 

(M2)

Exponential 

(M3)

0.48 -49.14 178 154 108 80

The linear model 

was selected on 

the basis of the 

lowest AIC with all 

BMDL values for 

fitting models 

being sufficiently 

close (BMDLs 

differed by less 

than 3-fold). 

Exponential 

(M4)

Exponential 

(M5)

0.33 -47.64 154 107 90 56

Hill 0.33 -47.64 154 105 90 Errorb

Linear

Power 0.62 -49.63 158 133 92 68

Polynomial 

3° 0.33 -47.63 158 133 98 68

a

Modeled variance case presented (BMDS Test 2 p-value = 0.0091), selected model in bold; scaled residuals for 

selected model for doses 0, 180, 330, and 650 mg/kg-d were -0.383, 0.887, -0.411, and -0.105, respectively. b

The BMDL1SD computation failed for the Hill model.

 3.5

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Mean Response

dose

Linear Model with 0.95 Confidence Level

16:36 05/13 2011

BMDL BMD

 

Linear

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Figure C-4. Plot of mean response by dose, with fitted curve for selected model (10% 

relative deviation). 

==================================================================== 

 Polynomial Model. (Version: 2.16; Date: 05/26/2010) 

 Input Data File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\23 NTP 1995b_Mean 

relative kidney weight, female rats_Linear_10RD.(d)

This document is a draft for review purposes only and does not constitute Agency policy.

C-13 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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1995b_Mean relative kidney weight, female rats_Linear_10RD.plt

 Mon May 09 18:34:15 2011

==================================================================== 

 [notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the response function is: 

 Y[dose] = beta_0 + beta_1*dose + beta_2*dose^2 + ...

 Dependent variable = Response

 Independent variable = Dose

 Signs of the polynomial coefficients are not restricted

 The variance is to be modeled as Var(i) = exp(lalpha + log(mean(i)) * rho)

 Total number of dose groups = 4

 Total number of records with missing values = 0

 Maximum number of iterations = 250

 Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008

 Default Initial Parameter Values 

 lalpha = -2.14986

 rho = 0 

 beta_0 = 3.52312

 beta_1 = 0.00219613

 Asymptotic Correlation Matrix of Parameter Estimates

 lalpha rho beta_0 beta_1

 lalpha 1 -1 0.1 -0.14

 rho -1 1 -0.1 0.14

 beta_0 0.1 -0.1 1 -0.66

 beta_1 -0.14 0.14 -0.66 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 lalpha -8.78559 2.23999 -13.1759 -4.39529

 rho 4.47471 1.57167 1.39429 7.55513

 beta_0 3.51492 0.0580177 3.40121 3.62864

 beta_1 0.00223049 0.00022176 0.00179585 0.00266513

 Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Res.

------ --- -------- -------- ----------- ----------- ----------

 0 10 3.49 3.51 0.253 0.206 -0.383

180 10 3.99 3.92 0.221 0.262 0.887

330 10 4.21 4.25 0.253 0.315 -0.411

650 10 4.95 4.96 0.538 0.446 -0.105

This document is a draft for review purposes only and does not constitute Agency policy.

C-14 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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Model Descriptions for likelihoods calculated

Model A1: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma^2

Model A2: Yij = Mu(i) + e(ij)

 Var{e(ij)} = Sigma(i)^2

Model A3: Yij = Mu(i) + e(ij)

 Var{e(ij)} = exp(lalpha + rho*ln(Mu(i)))

 Model A3 uses any fixed variance parameters that

 were specified by the user

Model R: Yi = Mu + e(i)

 Var{e(i)} = Sigma^2

 Likelihoods of Interest

 Model Log(likelihood) # Param's AIC

 A1 25.104490 5 -40.208981

 A2 30.882250 8 -45.764500

 A3 29.295765 6 -46.591531

 fitted 28.815603 4 -49.631206

 R -0.698257 2 5.396514

 Explanation of Tests 

Test 1: Do responses and/or variances differ among Dose levels? 

 (A2 vs. R)

Test 2: Are Variances Homogeneous? (A1 vs A2)

Test 3: Are variances adequately modeled? (A2 vs. A3)

Test 4: Does the Model for the Mean Fit? (A3 vs. fitted)

(Note: When rho=0 the results of Test 3 and Test 2 will be the same.)

 Tests of Interest 

 Test -2*log(Likelihood Ratio) Test df p-value 

 Test 1 63.161 6 <.0001

 Test 2 11.5555 3 0.009072

 Test 3 3.17297 2 0.2046

 Test 4 0.960325 2 0.6187

The p-value for Test 1 is less than .05. There appears to be a

difference between response and/or variances among the dose levels

It seems appropriate to model the data

The p-value for Test 2 is less than .1. A non-homogeneous variance 

model appears to be appropriate

The p-value for Test 3 is greater than .1. The modeled variance appears 

to be appropriate here

The p-value for Test 4 is greater than .1. The model chosen seems 

to adequately describe the data

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Relative risk 

Confidence level = 0.95

 BMD = 157.585

 BMDL = 132.699

This document is a draft for review purposes only and does not constitute Agency policy.

C-15 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-6. Summary of BMD modeling results for kidney inflammation in 

2 

3 

female rats exposed to tert-butanol in drinking water for 2 years (NTP, 1995); 

BMR = 10% extra risk.

Modela

Goodness of fit

BMD10%

(mg/kg-d)

BMDL10%

p-value AIC (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 

BMDL values for fitting models 

being sufficiently close (BMDLs 

differed by less than 3-fold). 

Logistic 0.082 169.7 305 252

LogLogistic 0.092 169.8 228 124

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

a

Selected 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. b

No available degrees of freedom to estimate a p-value.

4 

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6 

7 

8 

9 

10 

11 

12 

13 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 100 200 300 400 500 600

Fraction Affected

dose

LogProbit Model with 0.95 Confidence Level

17:17 05/13 2011

BMDL BMD

 

LogProbit

This document is a draft for review purposes only and does not constitute Agency policy.

C-16 DRAFT—DO NOT CITE OR QUOTE

Figure C-5. Plot of mean response by dose, with fitted curve for selected model.

==================================================================== 

 Probit Model. (Version: 3.2; Date: 10/28/2009) 

 Input Data File: M:/NCEA tert-butanol/BMD modeling/BMDS Output/19 NTP 

1995b_Kidney inflammation, female rats_LogProbit_10.(d) 

 Gnuplot Plotting File: M:/NCEA tert-butanol/BMD modeling/BMDS Output/19 NTP 

1995b_Kidney inflammation, female rats_LogProbit_10.plt

 Fri May 13 17:17:59 2011

==================================================================== 
Supplemental Information―tert Butanol

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[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the probability function is: 

P[response] = Background

 + (1-Background) * CumNorm(Intercept+Slope*Log(Dose)),

 where CumNorm(.) is the cumulative normal distribution function

Dependent variable = Incidence

Independent variable = Dose

Slope parameter is restricted as slope >= 1

Total number of observations = 4

Total number of records with missing values = 0

Maximum number of iterations = 250

Relative Function Convergence has been set to: 1e-008

 Parameter Convergence has been set to: 1e-008

 User has chosen the log transformed model

 Default Initial (and Specified) Parameter Values

 background = 0.04

 intercept = -8.01425

 slope = 1.18928

 Asymptotic Correlation Matrix of Parameter Estimates

 ( *** The model parameter(s) -slope 

 have been estimated at a boundary point, or have been specified by the user,

 and do not appear in the correlation matrix )

 background intercept

background 1 -0.51

intercept -0.51 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 background 0.0381743 0.0246892 -0.0102155 0.0865642

 intercept -6.82025 0.161407 -7.1366 -6.5039

 slope 1 NA

NA - Indicates that this parameter has hit a bound

 implied by some inequality constraint and thus

 has no standard error.

 Analysis of Deviance Table

 Model Log(likelihood) # Param's Deviance Test d.f. P-value

 Full model -80.4502 4 

 Fitted model -81.8218 2 2.7432 2 0.2537

Reduced model -92.7453 1 24.5902 3 <.0001

 AIC: 167.644

This document is a draft for review purposes only and does not constitute Agency policy.

C-17 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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 Goodness of Fit 

 Scaled

 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

 0.0000 0.0382 1.909 2.000 50 0.067

180.0000 0.0880 4.402 3.000 50 -0.700

330.0000 0.1859 9.295 13.000 50 1.347

650.0000 0.3899 19.495 17.000 50 -0.724

Chi^2 = 2.83 d.f. = 2 P-value = 0.2427

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk 

Confidence level = 0.95

 BMD = 254.347

 BMDL = 199.789

This document is a draft for review purposes only and does not constitute Agency policy.

C-18 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-7. Summary of BMD modeling results for thyroid follicular cell 

2 

3 

hyperplasia in male B6C3F1 mice exposed to tert-butanol in drinking water 

for 2 years (NTP, 1995); BMR = 10% extra risk.

Modela

Goodness of fit

BMD10%

(mg/kg-d)

BMDL10%

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

Gamma 0.052 254.7 702 430 No model was selected as a 

best-fitting model as models 

did not fit the overall 

goodness-of-fit criterion.

Logistic 0.031 256.1 1,064 751

LogLogistic 0.069 254.1 586 340

LogProbit 0.012 258.2 1,320 810

Multistage 3°

Weibull 0.052 254.7 702 430

Probit 0.032 255.9 1,020 713

Dichotomous-Hill N/Ab 253.6 0.19 Errorc

a

No model was selected as a best-fitting model. b

No available degrees of freedom to estimate a p-value. c BMDL computation failed for the Dichotomous-Hill model.

4 

This document is a draft for review purposes only and does not constitute Agency policy.

C-19 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

Table C-8. Summary of BMD modeling results for thyroid follicular cell 

hyperplasia in female B6C3F1 mice exposed to tert-butanol in drinking water 

for 2 years (NTP, 1995); BMR = 10% extra risk.

1 

2 

3 

Modela

Goodness of fit

BMD10

(mg/kg-d)

BMDL10

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

Gamma 0.63 303.1 327 154 The probit model was selected 

on the basis of the lowest AIC 

with all BMDL values for fitting 

models being sufficiently close

(BMDLs differed by less than 3-

fold). 

Logistic 0.94 301.0 297 243

LogLogistic 0.52 303.2 375 115

LogProbit 0.48 303.3 388 277

Multistage 3° 0.81 302.9 269 155

Probit 0.95 300.9 298 246

Weibull 0.66 303.0 321 154

Dichotomous-Hill 0.66 27,226 b Error b Error

a

Selected model in bold; scaled residuals for selected model for doses 0, 510, 1,020, and 2,110 mg/kg-d were -

0.110, 0.255, -0.174, and 0.025, respectively. b

The BMD and BMDL computations failed for the Dichotomous-Hill model.

 0.2

 0.3

 0.4

 0.5

 0.6

 0.7

 0.8

 0.9

 0 500 1000 1500 2000

Fraction Affected

dose

Probit Model with 0.95 Confidence Level

18:36 05/09 2011

BMDL BMD

 

Probit

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8 

9 

10 

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Figure C-6. Plot of mean response by dose, with fitted curve for selected model.

==================================================================== 

 Probit Model. (Version: 3.2; Date: 10/28/2009) 

 Input Data File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\27 NTP 

1995b_Thyroid follicular cell hyperplasia, female mice_Probit_10.(d)

 Gnuplot Plotting File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\27 NTP 

1995b_Thyroid follicular cell hyperplasia, female mice_Probit_10.plt

 Mon May 09 18:36:50 2011

This document is a draft for review purposes only and does not constitute Agency policy.

C-20 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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==================================================================== 

[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

 

 The form of the probability function is: 

P[response] = CumNorm(Intercept+Slope*Dose),

where CumNorm(.) is the cumulative normal distribution function

Dependent variable = Incidence

Independent variable = Dose

Slope parameter is not restricted

Total number of observations = 4

Total number of records with missing values = 0

Maximum number of iterations = 250

Relative Function Convergence has been set to: 1e-008

Parameter Convergence has been set to: 1e-008

 Default Initial (and Specified) Parameter Values 

 background = 0 Specified

 intercept = -0.425261

 slope = 0.000589168

 Asymptotic Correlation Matrix of Parameter Estimates

 ( *** The model parameter(s) -background 

 have been estimated at a boundary point, or have been specified by the user,

 and do not appear in the correlation matrix )

 intercept slope

intercept 1 -0.76

 slope -0.76 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 intercept -0.427828 0.129459 -0.681563 -0.174092

 slope 0.000593756 0.00011419 0.000369947 0.000817564

 Analysis of Deviance Table

 Model Log(likelihood) # Param's Deviance Test d.f. P-value

 Full model -148.416 4 

 Fitted model -148.47 2 0.108205 2 0.9473

Reduced model -162.896 1 28.9589 3 <.0001

 AIC: 300.941

 Goodness of Fit 

 Scaled

 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

 0.0000 0.3344 19.395 19.000 58 -0.110

510.0000 0.4503 27.015 28.000 60 0.255

1020.0000 0.5706 33.663 33.000 59 -0.174

2110.0000 0.7953 46.923 47.000 59 0.025

This document is a draft for review purposes only and does not constitute Agency policy.

C-21 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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Chi^2 = 0.11 d.f. = 2 P-value = 0.9473

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk 

Confidence level = 0.95

 BMD = 297.997

 BMDL = 246.075

This document is a draft for review purposes only and does not constitute Agency policy.

C-22 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

Table C-9. Summary of BMD modeling results for absolute kidney weight in 

male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 

weeks (NTP, 1997); BMR = 10% relative deviation from the mean.

1 

2 

3 

4 

Modela Goodness of fit BMC10RD

3 (mg/m )

BMCL10RD

3 (mg/m )

Basis for model selection

p-value AIC

Exponential (M2) <0.0001 -205.06 b error b error The Hill model was selected as 

the only adequately-fitting 

model. Exponential (M3) <0.0001 -203.06 9.2E+07 7094

Exponential (M4) <0.0001 -203.06 b error 0

Exponential (M5) <0.0001 -201.06 b error 0

Hill 0.763 -226.82 1931 1705

c Power 0.0607 -220.97 5364 3800

Linear

Polynomial 5°d

Polynomial 4°e

Polynomial 3°

1.44E04-207.06 -9999 f error

Polynomial 2° 1.44E04-207.06 -9999 18436

a Constant variance case presented (BMDS Test 2 p-value = 0.390), selected model in bold; scaled residuals for 

selected model for doses 0, 406, 825, 1643, 3274, and 6369 mg/m3 were 0.395, 0.374, -0.75, -1.96e-006, 0.381, 

and -0.381, respectively. b BMC or BMCL computation failed for this model.

c For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear 

model.

d For the Polynomial 5° model, the b5 and b4 coefficient estimates were 0 (boundary of parameters space). The 

models in this row reduced to the Polynomial 3° model.

e For the Polynomial 4° model, the b4 coefficient estimate was 0 (boundary of parameters space). The models in 

this row reduced to the Polynomial 3° model.

f

BMC or BMCL computation failed for this model

5 

This document is a draft for review purposes only and does not constitute Agency policy.

C-23 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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 1.1

 1.15

 1.2

 1.25

 1.3

 1.35

 1.4

 0 1000 2000 3000 4000 5000 6000

Mean Response

dose

Hill Model with 0.95 Confidence Level

10:15 04/30 2014

BMDL BMD

 

Hill

This document is a draft for review purposes only and does not constitute Agency policy.

C-24 DRAFT—DO NOT CITE OR QUOTE

Figure C-7. Plot of mean response by dose, with fitted curve for selected 

model; dose shown in mg/m3. 

Hill Model. (Version: 2.15; Date: 10/28/2009)

The form of the response function is: Y[dose] = intercept + v*dose^n/(k^n + dose^n)

A constant variance model is fit

Benchmark Dose Computation.

BMR = 10% Relative risk

BMD = 1931.35

BMDL at the 95% confidence level = 1704.82

Parameter Estimates

Variable Estimate Default Initial 

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
Supplemental Information―tert Butanol

1 Table of Data and Estimated Values of Interest

2 

3 

4 

5 

6 

7 

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

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

Tests of Interest

Test -

2*log(Likelihoo

d Ratio)

Test df p-value

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

This document is a draft for review purposes only and does not constitute Agency policy.

C-25 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

Table C-10. Summary of BMD modeling results for relative kidney weight in 

male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13 

weeks (NTP, 1997); BMR = 10% relative deviation from the mean.

1 

2 

3 

4 

Modela Goodness of fit BMC10RD

3 (mg/m )

BMCL10RD

3 (mg/m )

Basis for model selection

p-value AIC

Exponential (M2)

Exponential (M3)b

0.168 -141.06 6356 4923 The linear model is selected 

on the basis of lowest AIC.

Exponential (M4) 0.169 -140.46 5973 3386

Exponential (M5) 0.560 -142.35 c error 0

Hill 0.612 -142.53 c error c error

d Power

Polynomial 5°e

Polynomial 4°f

Polynomial 3°g

Polynomial 2°h

Linear

0.181 -141.25 6309 4821

a Constant variance case presented (BMCS Test 2 p-value = 0.165), selected model in bold; scaled residuals for 

selected model for doses 0, 406, 825, 1643, 3274, and 6369 mg/m3 were 0.181, 0.282, -1.42, -0.102, 1.81, and -

0.736, respectively.

b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the 

Exponential (M2) model.

c BMC or BMCL computation failed for this model.

d For the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear 

model.

e For the Polynomial 5° model, the b5, b4, and b3 coefficient estimates were 0 (boundary of parameters space).

The models in this row reduced to the Polynomial 2° model. For the Polynomial 5° model, the beta coefficient 

estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear model. f

For the Polynomial 4° model, the b4 and b3 coefficient estimates were 0 (boundary of parameters space). The 

models in this row reduced to the Polynomial 2° model. For the Polynomial 4° model, the b4, b3, and b2 

coefficient estimates were 0 (boundary of parameters space). The models in this row reduced to the Linear 

model.

g For the Polynomial 3° model, the b3 coefficient estimates was 0 (boundary of parameters space). The models in 

this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates 

were 0 (boundary of parameters space). The models in this row reduced to the Linear model. h For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in 

this row reduced to the Linear model.

5 

This document is a draft for review purposes only and does not constitute Agency policy.

C-26 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

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 3.5

 3.6

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Mean Response

dose

Linear Model with 0.95 Confidence Level

10:24 04/30 2014

BMDL BMD

 

Linear

This document is a draft for review purposes only and does not constitute Agency policy.

C-27 DRAFT—DO NOT CITE OR QUOTE

Figure C-8. Plot of mean response by dose, with fitted curve for selected model; dose 

shown in mg/m3. 

Polynomial Model. (Version: 2.16; Date: 05/26/2010)

The form of the response function is: Y[dose] = beta_0 + beta_1*dose

A constant variance model is fit

Benchmark Dose Computation.

BMR = 10% Relative risk

BMD = 6308.98

BMDL at the 95% confidence level = 4820.9

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

alpha 0.0303258 0.0303618

rho n/a 0

beta_0 3.67004 3.67051

beta_1 0.0000581717 0.000058076

Table of Data and Estimated Values of Interest

Dose N Obs Mean Est Mean Obs Std Dev Est Std Dev Scaled Resid

0 10 3.68 3.67 0.253 0.174 0.181

406 9 3.71 3.69 0.12 0.174 0.282

825 10 3.64 3.72 0.126 0.174 -1.42

1643 10 3.76 3.77 0.19 0.174 -0.102
Supplemental Information―tert Butanol

3274 10 3.96 3.86 0.158 0.174 1.81

6369 10 4 4.04 0.158 0.174 -0.736

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Likelihoods of Interest

Model Log(likelihood) # Param's AIC

A1 76.753535 7 -139.507071

A2 80.677068 12 -137.354137

A3 76.753535 7 -139.507071

fitted 73.624808 3 -141.249616

R 60.931962 2 -117.863925

Tests of Interest

Test -

2*log(Likelihoo

d Ratio)

Test df p-value

Test 1 39.4902 10 <0.0001

Test 2 7.84707 5 0.1649

Test 3 7.84707 5 0.1649

Test 4 6.25745 4 0.1807

This document is a draft for review purposes only and does not constitute Agency policy.

C-28 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-11. Summary of BMD modeling results for absolute kidney weight in 

2 

3 

female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 

13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean.

Modela Goodness of fit BMC10RD

(mg/m3)

BMCL10RD

(mg/m3)

Basis for model selection

p-value AIC

Exponential (M2)

Exponential (M3)b

0.0378 -261.52 14500 7713 No model adequately fit the 

data.

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

Polynomial 2°e

Linear

0.0274 -261.61 14673 7678

Polynomial 5° 0.0274 -261.61 14673 7569

Polynomial 4° 0.0274 -261.61 14673 7674

a Modeled variance case presented (BMDS Test 2 p-value = 1.90E-04, BMDS Test 3 p-value = 0.374), no model was 

selected as a best-fitting model. b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the 

Exponential (M2) model.

c BMC or BMCL computation failed for this model. d For the Polynomial 3° model, the b3 coefficient estimates was 0 (boundary of parameters space). The models in 

this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates 

were 0 (boundary of parameters space). The models in this row reduced to the Linear model. e For the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in 

this row reduced to the Linear model.

4 

5 

This document is a draft for review purposes only and does not constitute Agency policy.

C-29 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-12. Summary of BMD modeling results for relative kidney weight in 

2 

3 

female F344 rats exposed to tert-butanol via inhalation for 6 hrs/d, 5d/wk for 

13 weeks (NTP, 1997); BMR = 10% relative deviation from the mean.

Modela Goodness of fit BMC10RD

(mg/m3)

BMCL10RD

(mg/m3)

Basis for model selection

p-value AIC

Exponential (M2)

Exponential (M3)b

0.813 -125.14 6859 5476 No model adequately fit the 

data.

Exponential (M4)c 0.660 -123.12 6846 4832

Exponential (M5)d 0.660 -123.12 6846 4832

Hill 0.00189 -123.12 6845 5380

Power 0.809 -125.12 6846 5389

Polynomial 3° 0.00210 -123.34 6853 5439

Polynomial 2° 0.00191 -123.14 6865 5393

Linear 0.00488 -125.12 6846 5389

Polynomial 5° 0.00238 -123.61 6762 5504

Polynomial 4° 0.00228 -123.51 6807 5480

a Modeled variance case presented (BMDS Test 2 p-value = <0.0001, BMDS Test 3 p-value = 0.00105), no model 

was selected as a best-fitting model. b For the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the 

Exponential (M2) model. c The Exponential (M4) model may appear equivalent to the Exponential (M5) model, however differences exist in 

digits not displayed in the table.

d The Exponential (M5) model may appear equivalent to the Exponential (M4) model, however differences exist 

in digits not displayed in the table.

4 

5 C.1.2. Cancer Endpoints

6 

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For each endpoint, multistage models were fitted to the data using the maximum likelihood 

method. Each model was tested for goodness-of-fit using a chi-square goodness-of-fit test (χ2

p-value < 0.051 indicates lack of fit). Other factors were used to assess model fit, such as scaled 

residuals, visual fit, and adequacy of fit in the low dose region and near the BMR. 

For each endpoint, the BMDL estimate (95% lower confidence limit on the BMD, as 

estimated by the profile likelihood method) and AIC value were used to select a best-fit model from 

among the models exhibiting adequate fit. If the BMDL estimates were “sufficiently close,” that is, 

differed by more than 3-fold, the model selected was the one that yielded the lowest AIC value. If 

the BMDL estimates were not sufficiently close, the lowest BMDL was selected as the POD. For the 

1

A significance level of 0.05 is used for selecting cancer models because the model family (multistage) is 

selected a priori (U.S. EPA, 2000). 

This document is a draft for review purposes only and does not constitute Agency policy.

C-30 DRAFT—DO NOT CITE OR QUOTE

 
Supplemental Information―tert Butanol

1 NTP (1995) and Hard et al. (2011) data, models were run with all doses included, as well as with 

2 

3 

4 

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11 

the high dose dropped. Dropping the high dose resulted in a better fit to the data. Including the high 

dose caused the model to overestimate the control.

Table C-13. Cancer endpoints selected for dose-response modeling for tertbutanol

Endpoint/Study Species / Sex Doses and Effect Data

Renal tubule adenoma or 

carcinoma

NTP (1995)

Rat (F344) / 

Male

Dose (mg/kg-d) 0 90 200 420

Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or 

carcinoma

NTP (1995)

Rat (F344) / 

Male

Dose (PBPK, mg/L) 0 4.6945 12.6177 40.7135

Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or 

carcinoma

NTP (1995)

Rat (F344) / 

Male

Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712

Incidence / Total 8 / 50 13 / 50 19 / 50 13 / 50

Renal tubule adenoma or 

carcinoma; Hard reanalysis

NTP (1995);Hard et al. (2011)

Rat (F344) / 

Male

Dose (mg/kg-d) 0 90 200 420

Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Renal tubule adenoma or 

carcinoma; Hard reanalysis

NTP (1995);Hard et al. (2011)

Rat (F344) / 

Male

Dose (PBPK, mg/L) 0 4.6945 12.6177 40.7135

Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Renal tubule adenoma or 

carcinoma; Hard reanalysis

NTP (1995);Hard et al. (2011)

Rat (F344) / 

Male

Dose (PBPK, mg/hr) 0 0.7992 1.7462 3.4712

Incidence / Total 4 / 50 13 / 50 18 / 50 12 / 50

Thyroid follicular cell 

adenoma

NTP (1995)

B6C3F1 mice / 

female

Dose (mg/kg-d) 0 510 1,020 2,110

Incidence / Total 2 / 58 3 / 60 2 / 59 9 / 59

C.1.2.1. Modeling Results

Below are tables summarizing the modeling results for the cancer endpoints that were 

modeled. For the multistage models, the coefficients were restricted to be non-negative (beta

values ≥ 0). 

This document is a draft for review purposes only and does not constitute Agency policy.

C-31 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-14. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with administered dose units and including all dose groups

(NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/kgd)BMDL10Pct

(mg/kg-d)

Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

0.080

6

-0.989, 0.288, 

1.719, and -1.010

233.9

4

294 118 Multistage 2° is 

selected as the 

most 

parsimonious 

model of 

adequate fit.

One 0.080

6

-0.989, 0.288, 

1.719, and -1.010

233.9

4

294 errorb

a Selected model in bold.

b BMD or BMDL computation failed for this model.

6 

7 

8 

9 

10 

11 

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200 250 300 350 400

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

10:57 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-9. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/kg-d.

This document is a draft for review purposes only and does not constitute Agency policy.

C-32 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 293.978

BMDL at the 95% confidence level = 117.584

BMDU at the 95% confidence level = 543384000

Taken together, (117.584, 543384000) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.000850453

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.217704 0.2335

Beta(1) 0.000358397 0.000268894

Beta(2) 0 0

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 

model

-115.644 1 6.30404 3 0.09772

AIC: = 233.94

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

Chi^2 = 5.04 d.f = 2 P-value = 0.0806

This document is a draft for review purposes only and does not constitute Agency policy.

C-33 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-15. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with administered dose units and excluding high-dose group 

(NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct

(mg/kg-d)

Basis for model 

selection

pvalueScaled residuals AIC

Two N/Ab 0.000, -0.000, and -

0.000

173.6

8

75.6 41.6 Multistage 1° was 

selected as the 

only adequatelyfitting model 

available

One 0.924 0.031, -0.078, and 

0.045

171.6

9

70.1 41.6

a Selected model in bold.

b No available degrees of freedom to calculate a goodness of fit value.

6 

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:02 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

7 

8 

9 

10 

11 

Figure C-10. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/kg-d.

This document is a draft for review purposes only and does not constitute Agency policy.

C-34 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 70.1068

BMDL at the 95% confidence level = 41.5902

BMDU at the 95% confidence level = 203.311

Taken together, (41.5902, 203.311) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.00240441

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.158399 0.156954

Beta(1) 0.00150286 0.0015217

Analysis of Deviance Table

Model Log(likelihoo

d)

# Param's Deviance Test d.f. p-value

Full model -83.8395 3

Fitted model -83.8441 2 0.00913685 1 0.9238

Reduced 

model

-86.9873 1 6.29546 2 0.04295

AIC: = 171.688

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

Chi^2 = 0.01 d.f = 1 P-value = 0.9239

This document is a draft for review purposes only and does not constitute Agency policy.

C-35 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-16. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (tert-butanol, mg/L) dose units and including all 

dose groups (NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

One

0.051

8

-1.373, 0.155, 

1.889, and -0.668

234.8

3

51.8 13.9 Multistage 1° was 

selected as the 

most 

parsimonious 

model of 

adequate fit.

a Selected model in bold.

6 

 0.1

 0.2

 0.3

 0.4

 0.5

 0 10 20 30 40 50

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:19 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

7 

8 

9 

10 

11 

Figure C-11. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/L.

This document is a draft for review purposes only and does not constitute Agency policy.

C-36 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 51.8357

BMDL at the 95% confidence level = 13.9404

BMDU at the 95% confidence level = error

Taken together, (13.9404, error) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = error

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.243327 0.253053

Beta(1) 0.00203259 0.00150893

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -112.492 4

Fitted model -115.417 2 5.84883 2 0.0537

Reduced 

model

-115.644 1 6.30404 3 0.09772

AIC: = 234.834

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.2433 12.166 8 50 -1.373

4.6945 0.2505 12.526 13 50 0.155

12.6177 0.2625 13.124 19 50 1.889

40.7135 0.3034 15.171 13 50 -0.668

Chi^2 = 5.92 d.f = 2 P-value = 0.0518

This document is a draft for review purposes only and does not constitute Agency policy.

C-37 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-17. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

6 

7 

8 

9 

10 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (tert-butanol, mg/L) dose units and excluding highdose group (NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model 

selection

pvalueScaled residuals AIC

Two

One

0.891 -0.054, 0.113, and -

0.057

171.7

0

4.33 2.54 Multistage 1° was 

selected as the 

most 

parsimonious 

model of 

adequate fit.

a Selected model in bold.

 0.1

 0.2

 0.3

 0.4

 0.5

 0 2 4 6 8 10 12

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:20 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-12. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/L.

This document is a draft for review purposes only and does not constitute Agency policy.

C-38 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 4.33496

BMDL at the 95% confidence level = 2.53714

BMDU at the 95% confidence level = 12.8097

Taken together, (2.53714, 12.8097) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0394144

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.162798 0.164724

Beta(1) 0.0243048 0.0238858

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -83.8395 3

Fitted model -83.8489 2 0.0187339 1 0.8911

Reduced 

model

-86.9873 1 6.29546 2 0.04295

AIC: = 171.698

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.1628 8.14 8 50 -0.054

4.6945 0.2531 12.654 13 50 0.113

12.6177 0.3839 19.195 19 50 -0.057

Chi^2 = 0.02 d.f = 1 P-value = 0.891

This document is a draft for review purposes only and does not constitute Agency policy.

C-39 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-18. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (metabolized, mg/hr) dose units and including all 

dose groups (NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/hr) BMDL10Pct

(mg/hr)

Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

One

0.088

5

-0.920, 0.301, 

1.677, and -1.049

233.7

6

2.28 0.954 Multistage 1° was

selected as the 

most 

parsimonious 

model of 

adequate fit.

a Selected model in bold.

Data from NTP1995

 0.1

 0.2

 0.3

 0.4

 0.5

 0 0.5 1 1.5 2 2.5 3 3.5

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:22 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-13. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/hr.

This document is a draft for review purposes only and does not constitute Agency policy.

C-40 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

24 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 2.28299

BMDL at the 95% confidence level = 0.95436

BMDU at the 95% confidence level = error

Taken together, (0.95436, error) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = error

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.21328 0.229822

Beta(1) 0.0461502 0.0349139

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -112.492 4

Fitted model -114.879 2 4.77309 2 0.09195

Reduced 

model

-115.644 1 6.30404 3 0.09772

AIC: = 233.758

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.2133 10.664 8 50 -0.92

0.7992 0.2418 12.088 13 50 0.301

1.7462 0.2742 13.71 19 50 1.677

3.4712 0.3297 16.487 13 50 -1.049

Chi^2 = 4.85 d.f = 2 P-value = 0.0885

This document is a draft for review purposes only and does not constitute Agency policy.

C-41 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-19. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (metabolized, mg/hr) dose units and excluding 

high-dose group (NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/hr) BMDL10Pct

(mg/hr)

Basis for model 

selection

pvalueScaled residuals AIC

Two N/Ab -0.000, -0.000, and 

-0.000

173.6

8

0.673 0.365 Multistage 1° was 

selected on the 

basis of lowest 

AIC. One 0.906 0.037, -0.096, and 

0.057

171.6

9

0.614 0.364

a Selected model in bold.

b No available degrees of freedom to calculate a goodness of fit value.

Data from NTP1995

 0.1

 0.2

 0.3

 0.4

 0.5

 0 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:24 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-14. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/hr.

This document is a draft for review purposes only and does not constitute Agency policy.

C-42 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

21 

22 

23 

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 0.613798

BMDL at the 95% confidence level = 0.364494

BMDU at the 95% confidence level = 1.77845

Taken together, (0.364494, 1.77845) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.274353

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.158068 0.156284

Beta(1) 0.171653 0.174305

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -83.8395 3

Fitted model -83.8465 2 0.0138544 1 0.9063

Reduced 

model

-86.9873 1 6.29546 2 0.04295

AIC: = 171.693

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.1581 7.903 8 50 0.037

0.7992 0.266 13.3 13 50 -0.096

1.7462 0.3761 18.806 19 50 0.057

Chi^2 = 0.01 d.f = 1 P-value = 0.9064

This document is a draft for review purposes only and does not constitute Agency policy.

C-43 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-20. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

6 

7 

8 

9 

10 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with administered dose units and including all dose groups; 

reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk.

Modela Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct

(mg/kg-d)

Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

One

0.011

7

-1.476, 1.100, 

1.855, and -1.435

218.6

8

184 94.8 No model fit the 

data.

a No model was selected as a best-fitting model.

Table C-21. Summary of BMD modeling results for renal tubule adenoma or 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with administered dose units and excluding high-dose group; 

re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra risk. 

Modela Goodness of fit BMD10Pct (mg/kg-d) BMDL10Pct

(mg/kg-d)

Basis for model 

selection

pvalueScaled residuals AIC

Two

One

0.572 -0.141, 0.461, and -

0.296

154.8

4

54.2 36.3 Multistage 1° was 

selected as the 

most 

parsimonious 

model of 

adequate fit.

a Selected model in bold.

This document is a draft for review purposes only and does not constitute Agency policy.

C-44 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 50 100 150 200

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:05 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-15. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/kg-d.

Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 54.1642

BMDL at the 95% confidence level = 36.3321

BMDU at the 95% confidence level = 101.125

Taken together, (36.3321, 101.125) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.00275239

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.0855815 0.0981146

Beta(1) 0.00194521 0.00179645

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -75.2622 3

Fitted model -75.4201 2 0.315716 1 0.5742

Reduced 

model

-81.4909 1 12.4574 2 0.001972

This document is a draft for review purposes only and does not constitute Agency policy.

C-45 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 

2 

3 

4 

5 

6 

7 

8 

AIC: = 154.84

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

Chi^2 = 0.32 d.f = 1 P-value = 0.5715

This document is a draft for review purposes only and does not constitute Agency policy.

C-46 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 Table C-22. Summary of BMD modeling results for renal tubule adenoma or 

2 

3 

4 

5 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (tert-butanol, mg/L) dose units and including all 

dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 

risk.

Modela Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

One

0.004

8

-2.089, 0.864, 

2.165, and -0.929

220.8

2

31.4 11.7 No model fit the 

data.

a No model was selected as a best-fitting model.

6 Table C-23. Summary of BMD modeling results for renal tubule adenoma or 

7 

8 

9 

10 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (tert-butanol, mg/L) dose units and excluding highdose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 

risk.

Modela Goodness of fit BMD10Pct (mg/L) BMDL10Pct (mg/L) Basis for model 

selection

pvalueScaled residuals AIC

Two

One

0.364 -0.285, 0.750, and -

0.424

155.3

3

3.35 2.21 Multistage 1° was 

selected as the 

most 

parsimonious 

model of 

adequate fit.

a Selected model in bold.

This document is a draft for review purposes only and does not constitute Agency policy.

C-47 DRAFT—DO NOT CITE OR QUOTE
Supplemental Information―tert Butanol

1 

2 

3 

4 

5 

6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

18 

19 

20 

 0

 0.1

 0.2

 0.3

 0.4

 0.5

 0 2 4 6 8 10 12

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:30 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

Figure C-16. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/L.

Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 3.34903

BMDL at the 95% confidence level = 2.20865

BMDU at the 95% confidence level = 6.49702

Taken together, (2.20865, 6.49702) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.0452765

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.0916116 0.110649

Beta(1) 0.03146 0.0276674

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -75.2622 3

Fitted model -75.664 2 0.803466 1 0.3701

Reduced 

model

-81.4909 1 12.4574 2 0.001972

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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AIC: = 155.328

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.0916 4.581 4 50 -0.285

4.6945 0.2163 10.817 13 50 0.75

12.6177 0.3892 19.462 18 50 -0.424

Chi^2 = 0.82 d.f = 1 P-value = 0.3643

Table C-24. Summary of BMD modeling results for renal tubule adenoma or 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (metabolized, mg/hr) dose units and including all 

dose groups; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% extra 

risk.

Modela Goodness of fit BMD10Pct (mg/hr) BMDL10Pct

(mg/hr)

Basis for model 

selection

pvalueScaled residuals AIC

Three

Two

One

0.014

2

-1.367, 1.119, 

1.783, and -1.484

218.2

6

1.44 0.770 No model fit the 

data.

a No model was selected as a best-fitting model.

Table C-25. Summary of BMD modeling results for renal tubule adenoma or 

carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2 

years modeled with PBPK (metabolized, mg/hr) dose units and excluding 

high-dose group; reanalyzed data (Hard et al., 2011; NTP, 1995); BMR = 10% 

extra risk.

Modela Goodness of fit BMD10Pct

(mg/hr)

BMDL10Pct

(mg/hr)

Basis for model 

selection

p-value Scaled residuals AIC

Two

One

0.593 -0.130, 0.435, and 

-0.281

154.81 0.474 0.319 Multistage 1° was 

selected as the most 

parsimonious model 

of adequate fit.

a Selected model in bold.

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 

 0

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Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

11:33 04/30 2014

BMDL BMD

 

Multistage Cancer

Linear extrapolation

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Figure C-17. Plot of incidence rate by dose, with fitted curve for selected model; dose 

shown in mg/hr.

Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)

The form of the probability function is: P[response] = background + (1-background)*[1-EXP(-

beta1*dose^1-beta2*dose^2...)]

The parameter betas are restricted to be positive

Benchmark Dose Computation.

BMR = 10% Extra risk

BMD = 0.474241

BMDL at the 95% confidence level = 0.318504

BMDU at the 95% confidence level = 0.882859

Taken together, (0.318504, 0.882859) is a 90% two-sided confidence interval for the BMD

Multistage Cancer Slope Factor = 0.313968

Parameter Estimates

Variable Estimate Default Initial 

Parameter Values

Background 0.0851364 0.0969736

Beta(1) 0.222167 0.206161

Analysis of Deviance Table

Model Log(likelihood) # Param's Deviance Test d.f. p-value

Full model -75.2622 3

Fitted model -75.4029 2 0.281435 1 0.5958

Reduced 

model

-81.4909 1 12.4574 2 0.001972

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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7 

8 

AIC: = 154.806

Goodness of Fit Table

Dose Est. Prob. Expected Observed Size Scaled Resid

0 0.0851 4.257 4 50 -0.13

0.7992 0.234 11.699 13 50 0.435

1.7462 0.3793 18.966 18 50 -0.281

Chi^2 = 0.29 d.f = 1 P-value = 0.5933

This document is a draft for review purposes only and does not constitute Agency policy.

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2 

3 

Table C-26. Summary of BMD modeling results for thyroid follicular cell 

adenomas in female B6C3F1 mice exposed to tert-butanol in drinking water 

for 2 years (NTP, 1995); BMR = 10% extra risk.

Model a

Goodness of fit BMD10%c

(mg/kg-d)

BMDL10%c

p-value AIC (mg/kg-d) Basis for model selection b

Three 0.75 113.665 2002 1437 Multistage 3° was selected on the basis 

of the lowest AIC with all BMDL values 

for fitting models being sufficiently 

close (BMDLs differed by less than 3-

fold). 

Two 0.36 115.402 2186 1217

One 0.63 114.115 1987 1378

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

4 

 0

 0.05

 0.1

 0.15

 0.2

 0.25

 0.3

 0 50 100 150 200 250 300 350

Fraction Affected

dose

Multistage Cancer Model with 0.95 Confidence Level

15:51 05/13 2011

BMDL BMD

 

Multistage Cancer

Linear extrapolation

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6 

7 

8 

9 

10 

11 

12 

13 

14 

15 

16 

17 

Figure C-18. Plot of mean response by dose, with fitted curve for selected model.

==================================================================== 

 Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010) 

 Input Data File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\29 NTP 

1995b_Thyroid folluclar cell andenoma, female mice (HEC)_MultiCanc3_10.(d)

 Gnuplot Plotting File: M:\NCEA tert-butanol\BMD modeling\BMDS Output\29 NTP 

1995b_Thyroid folluclar cell andenoma, female mice (HEC)_MultiCanc3_10.plt

 Fri May 13 15:51:46 2011

==================================================================== 

[notes] 

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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 The form of the probability function is: 

P[response] = background + (1-background)*[1-EXP(

 -beta1*dose^1-beta2*dose^2-beta3*dose^3)] 

 The parameter betas are restricted to be positive

Dependent variable = Incidence

Independent variable = Dose

Total number of observations = 4

Total number of records with missing values = 0

Total number of parameters in model = 4

Total number of specified parameters = 0

Degree of polynomial = 3

Maximum number of iterations = 250

Relative Function Convergence has been set to: 1e-008

Parameter Convergence has been set to: 1e-008

 Default Initial Parameter Values 

 Background = 0.0344951

 Beta(1) = 0 

 Beta(2) = 0 

 Beta(3) = 3.4555e-009

 Asymptotic Correlation Matrix of Parameter Estimates

 ( *** The model parameter(s) -Beta(1) -Beta(2) 

 have been estimated at a boundary point, or have been specified by the user,

 and do not appear in the correlation matrix )

 Background Beta(3)

Background 1 -0.54

 Beta(3) -0.54 1 

 Parameter Estimates

 95.0% Wald Confidence Interval

 Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit

 Background 0.0359685 * * * 

 Beta(1) 0 * * * 

 Beta(2) 0 * * * 

 Beta(3) 3.30537e-009 * * * 

* - Indicates that this value is not calculated.

 Analysis of Deviance Table

 Model Log(likelihood) # Param's Deviance Test d.f. P-value

 Full model -54.5437 4 

 Fitted model -54.8422 2 0.597063 2 0.7419

Reduced model -58.5048 1 7.92235 3 0.04764

 AIC: 113.684

 Goodness of Fit 

 Scaled

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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 Dose Est._Prob. Expected Observed Size Residual

------------------------------------------------------------------------

 0.0000 0.0360 2.086 2.000 58 -0.061

 83.0000 0.0378 2.267 3.000 60 0.496

164.0000 0.0499 2.945 2.000 59 -0.565

334.0000 0.1477 8.713 9.000 59 0.105

Chi^2 = 0.58 d.f. = 2 P-value = 0.7482

 Benchmark Dose Computation

Specified effect = 0.1

Risk Type = Extra risk 

Confidence level = 0.95

 BMD = 317.068

 BMDL = 228.888

 BMDU = 600.031

Taken together, (228.888, 600.031) is a 90 % two-sided confidence

interval for the BMD

Multistage Cancer Slope Factor = 0.000436894

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

1 APPENDIX D. SUMMARY OF EXTERNAL PEER 

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12 

REVIEW AND PUBLIC COMMENTS AND EPA’S 

DISPOSITION

[placeholder]

Additional Appendices:

[appendices can be used to supplement the HI and D-R analysis – the information 

presented by the appendices will be chemical-specific]

Examples:

• PBPK Modeling of [chemical] and metabolites – detailed methods and results

• Meta-analysis of ________ results from epidemiological studies

• Lifetable analysis and weighted linear regression based on results from 

[reference]

This document is a draft for review purposes only and does not constitute Agency policy.

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Supplemental Information―tert Butanol

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REFERENCES FOR APPENDICES

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for methyl tertiary-butyl ether; comparison of selected dose metrics following various 

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Supplemental Information―tert Butanol

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This document is a draft for review purposes only and does not constitute Agency policy.

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1 Licata, AC; Dekant, W; Smith, CE; Borghoff, SJ. (2001). A physiologically based pharmacokinetic 

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This document is a draft for review purposes only and does not constitute Agency policy.

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1 Rao, HV; Ginsberg, GL. (1997). A physiologically-based pharmacokinetic model assessment of 

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methyl t-butyl ether in groundwater for a bathing and showering determination. Risk 

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mutagenicity tests: III. Results from the testing of 255 chemicals. Environ Mutagen 9: 1-

60. http://dx.doi.org/10.1002/em.2860090602

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