g—Qm
WCT7\
EPA/635/R-20/105b
Final Agency and Interagency Draft
www.epa.gov/iris
Toxicological Review of tert-Butyl Alcohol (tert-Butanol)
(CASRN 75-65-0]
Supplemental Information
July 2020
NOTICE
This document is a Final Agency and Interagency Draft. 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
Center for Public Health and Environmental Assessment
Office of Research and Development
U.S. Environmental Protection Agency
Washington, DC
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Supplemental Information—tert-Butyl Alcohol
1 DISCLAIMER
2 This document is a preliminary draft for review purposes only. This information is
3 distributed solely for the purpose of predissemination peer review under applicable information
4 quality guidelines. It has not been formally disseminated by EPA. It does not represent and should
5 not be construed to represent any Agency determination or policy. Mention of trade names or
6 commercial products does not constitute endorsement or recommendation for use.
7
This document is a draft for review purposes only and does not constitute Agency policy.
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1
2 CONTENTS
3 APPENDIX A. ASSESSMENTS BY OTHER NATIONAL AND INTERNATIONAL HEALTH AGENCIES A-l
4 APPENDIX B. INFORMATION IN SUPPORT OF HAZARD IDENTIFICATION AND DOSE-RESPONSE
5 ANALYSIS 1
6 B.l. TOXICOKINETICS 1
7 B.l.l. Absorption 1
8 B.l.2. Distribution 2
9 B.l.3. Metabolism 2
10 B.1.4. Excretion 5
11 B.l.5. Physiologically Based Pharmacokinetic Models 7
12 B.1.6. PBPK Model Code 10
13 B.l.7. PK/PBPK Model Evaluation 10
14 B.2. OTHER PERTINENT TOXICITY INFORMATION B-32
15 B.2.1. Other Toxicological Effects B-32
16 B.2.2. Genotoxicity B-46
17 B.2.3. Summary B-50
18 APPENDIX C. DOSE-RESPONSE MODELING FOR THE DERIVATION OF REFERENCE VALUES FOR
19 EFFECTS OTHER THAN CANCER AND THE DERIVATION OF CANCER RISK
20 ESTIMATES C-l
21 C.l.l. Noncancer Endpoints C-l
22 C.1.2. Cancer Endpoints C-23
23 APPENDIX D. PATHOLOGY CONSULT FOR ETBE AND 7"£/?7"-BUTANOL D-l
24 APPENDIX E. SUMMARY OF SCIENCE ADVISORY BOARD (SAB) PEER REVIEW COMMENTS AND
25 EPA'S DISPOSITION E-l
26 APPENDIX F. QUALITY ASSURANCE (QA) FOR THE IRIS TOXICOLOGICAL REVIEW OF TfRT-BUTYL
27 ALCOHOL (TfRT-BUTANOL) F-l
28 REFERENCES R-l
29
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TABLES
Table A-l. Health assessments and regulatory limits by other national and international
health agencies A-l
Table B-l. Changes in kidney weight in animals following exposure to ferf-butanol B-35
Table B-2. Changes in liver weight in animals following exposure to ferf-butanol B-38
Table B-3. Changes in liver histopathology in animals following exposure to ferf-butanol B-40
Table B-4. Changes in urinary bladder histopathology in animals following oral exposure to
ferf-butanol B-42
Table B-5. Summary of genotoxicity (both in vitro and in vivo) studies of ferf-butanol B-49
Table C-l. Noncancer endpoints selected for dose-response modeling for ferf-butanol C-2
Table C-2. Summary of BMD modeling results for kidney transitional epithelial hyperplasia in
male F344 rats exposed to ferf-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 ferf-butanol in drinking water for 2 years (NTP,
1995); BMR = 10% extra risk C-6
Table C-4. Summary of BMD modeling results for absolute kidney weight in male F344 rats
exposed to ferf-butanol in drinking water for 15 months (NTP, 1995); BMR =
10% rel. dev. from control mean C-9
Table C-5. Summary of BMD modeling results for absolute kidney weight in female F344 rats
exposed to ferf-butanol in drinking water for 15 months (NTP, 1995); BMR =
10% rel. dev. from control mean C-12
Table C-6. Summary of BMD modeling results for kidney inflammation in female rats
exposed to ferf-butanol in drinking water for 2 years (NTP, 1995); BMR = 10%
extra risk C-15
Table C-7. Summary of BMD modeling results for absolute kidney weight in male F344 rats
exposed to ferf-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP,
1997); BMR = 10% relative deviation from the mean C-18
Table C-8. Summary of BMD modeling results for absolute kidney weight in female F344 rats
exposed to ferf-butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP,
1997); BMR = 10% relative deviation from the mean C-21
Table C-9. Cancer endpoints selected for dose-response modeling for ferf-butanol C-24
Table C-10. Summary of the oral slope factor derivations C-25
Table C-ll. Summary of BMD modeling results for thyroid follicular cell adenomas in female
B6C3F1 mice exposed to ferf-butanol in drinking water for 2 years (NTP, 1995);
BMR = 10% extra risk C-26
Table C-12. Summary of BMD modeling results for thyroid follicular cell adenomas or
carcinomas in male B6C3F1 mice exposed to ferf-butanol in drinking water for
2 years (NTP, 1995); BMR = 5% extra risk C-29
Table C-13. Summary of BMD modeling results for thyroid follicular cell adenomas or
carcinomas in male B6C3F1 mice exposed to ferf-butanol in drinking water for
2 years, high dose omitted (NTP, 1995); BMR = 5% extra risk C-32
Table C-14. Summary of BMD modeling results for renal tubule adenoma or carcinoma in
male F344 rats exposed to tert-butanol in drinking water for 2 years modeled
with administered dose units and including all dose groups (NTP, 1995); BMR
= 10% extra risk C-35
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Table C-15. Summary of BMD modeling results for renal tubule adenoma or carcinoma in
male F344 rats exposed to ferf-butanol in drinking water for 2 years modeled
with administered dose units and excluding high-dose group (NTP, 1995); BMR
= 10% extra risk C-37
Table C-16. Summary of BMD modeling results for renal tubule adenoma or carcinoma in
male F344 rats exposed to ferf-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-39
Table C-17. Summary of BMD modeling results for renal tubule adenoma or carcinoma in
male F344 rats exposed to ferf-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-39
FIGURES
Figure B-l. Biotransformation of ferf-butanol in rats and humans 4
Figure B-2. Example oral ingestion pattern for rats exposed via drinking water 8
Figure B-3. Exposure-response array of other effects following oral exposure to ferf-butanol B-44
Figure B-4. Exposure-response array of other effects following inhalation exposure to ferf-
butanol B-45
Figure C-l. Plot of incidence by dose, with fitted curve for LogLogistic model for kidney
transitional epithelial hyperplasia in male F344 rats exposed to ferf-butanol in
drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in
mg/kg-d C-4
Figure C-2. Plot of incidence by dose, with fitted curve for Multistage 3° model for kidney
transitional epithelial hyperplasia in female F344 rats exposed to ferf-butanol
in drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in
mg/kg-d C-6
Figure C-3. Plot of mean response by dose, with fitted curve for Linear model with constant
variance for absolute kidney weight in male F344 rats exposed to ferf-butanol
in drinking water for 15 months (NTP, 1995); BMR = 10% rel. dev. from control
mean; dose shown in mg/kg-d C-10
Figure C-4. Plot of mean response by dose, with fitted curve for Exponential (M4) model
with constant variance for absolute kidney weight in female F344 rats exposed
to ferf-butanol in drinking water for 15 months (NTP, 1995); BMR = 10% rel.
dev. from control mean; dose shown in mg/kg-d C-13
Figure C-5. Plot of incidence by dose, with fitted curve for LogpPobit model for kidney
inflammation in female rats exposed to ferf-butanol in drinking water for 2
years (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d C-15
Figure C-6. Plot of mean response by concentration, with fitted curve for Hill model for
absolute kidney weight in male F344 rats exposed to ferf-butanol via inhalation
for 6 hr/d, 5d/wkfor 13 weeks (NTP, 1997); BMR = 10% relative deviation from
the mean; concentration shown in mg/m3 C-19
Figure C-7. Plot of mean response by concentration, with fitted curve for Hill model for
absolute kidney weight in female F344 rats exposed to ferf-butanol via
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inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative
deviation from the mean; concentration shown in mg/m3 C-22
Figure C-8. Plot of mean response by concentration, with fitted curve for Power model for
absolute kidney weight in female F344 rats exposed to ferf-butanol via
inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP, 1997); BMR = 10% relative
deviation from the mean; concentration shown in mg/m3 C-22
Figure C-9. Plot of incidence by dose, with fitted curve for Multistage 3° model for thyroid
follicular cell adenomas in female B6C3F1 mice exposed to ferf-butanol in
drinking water for 2 years (NTP, 1995); BMR = 10% extra risk; dose shown in
mg/kg-d C-26
Figure C-10. Plot of incidence by dose, with fitted curve for Multistage 1° model for thyroid
follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to ferf-
butanol in drinking water for 2 years (NTP, 1995); BMR = 5% extra risk; dose
shown in mg/kg-d C-29
Figure C-ll. Plot of incidence by dose, with fitted curve for Multistage 2° model for thyroid
follicular cell adenomas or carcinomas in male B6C3F1 mice exposed to ferf-
butanol in drinking water for 2 years, high dose omitted (NTP, 1995); BMR = 5%
extra risk; dose shown in mg/kg-d C-32
Figure C-12. Plot of incidence by dose, with fitted curve for Multistage 2° model for renal
tubule adenoma or carcinoma in male F344 rats exposed to ferf-butanol in
drinking water for 2 years modeled with administered dose units and including
all dose groups (NTP, 1995); BMR = 10% extra risk; dose shown in mg/kg-d C-35
Figure C-13. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal
tubule adenoma or carcinoma in male F344 rats exposed to ferf-butanol in
drinking water for 2 years modeled with administered dose units and excluding
high-dose group (NTP, 1995); BMR = 10% extra risk.; dose shown in mg/kg-d C-37
Figure C-14. Plot of incidence by dose, with fitted curve for Multistage 1° model for renal
tubule adenoma or carcinoma in male F344 rats exposed to tert-butanol in
drinking water for 2 years modeled with administered dose units and excluding
high-dose group; re-analyzed data (Hard et al., 2011; NTP, 1995); BMR = 10%
extra risk; dose shown in mg/kg-d C-40
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i ABBREVIATIONS
AIC Akaike's information criterion
ARCO ARCO Chemical Company
BMD benchmark dose
BMDL benchmark dose lower confidence limit
BMDS Benchmark Dose Software
BMDU benchmark dose upper confidence limit
BMR benchmark response
BW body weight
CFR Code of Federal Regulations
CHO Chinese hamster ovary
CYP450 cytochrome P450
DMSO dimethyl sulfoxide
DNA deoxyribonucleic acid
EDTA ethylenediaminetetraacetic acid
EPA U.S. Environmental Protection Agency
ETBE ethyl tert-butyl ether
HBA 2-hydroxyisobutyrate
HL human leukemia
IC50 half-maximal inhibitory concentration
i.p. intraperitoneal
i.v. intravenous
MFO mixed function oxidase
MPD 2-methyl-l, 2 -propanediol
MTBE methyl tert-butyl ether
NADPH nicotinamide adenine dinucleotide
phosphate
NTP National Toxicology Program
•OH hydroxyl radical
PBPK physiologically based pharmacokinetic
POD point of departure
SD standard deviation
TWA time-weighted average
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2 APPENDIX A. ASSESSMENTS BY OTHER NATIONAL
3 AND INTERNATIONAL HEALTH AGENCIES
4 Table A-l. Health assessments and regulatory limits by other national and
5 international health agencies
Organization
Toxicity value
National Institute of Occupational
Safety and Health (NIOSH, 2007)
Recommended Exposure Limit - 100 ppm (300 mg/m3) time-weighted
average (TWA) for up to a 10-hour workday and a 40-hour workweek.
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)
te/t-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
(21CFR 176.200).
6
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APPENDIX B. INFORMATION IN SUPPORT OF
HAZARD IDENTIFICATION AND DOSE-RESPONSE
ANALYSIS
B.l. TOXICOKINETICS
Little information is available on the absorption, distribution, metabolism, or excretion of
tert-butyl alcohol (tert-butanol) in humans. The studies identified for this Toxicological Assessment
were conducted in conjunction with methyl tert-butyl ether (MTBE) or ethyl tert-butyl ether
(ETBE), as tert-butanol is a metabolite of both compounds. Several studies examining some aspect
of the toxicokinetic behavior of tert-butanol in animals have been identified. Many of these
toxicokinetic studies were carried out in conjunction with other specific endpoints (e.g.,
developmental). ARCO (19831 did not observe differences in the pharmacokinetics of tert-butanol
following either oral (i.e., gavage) or inhalation exposure. Although some information is available
for both oral and inhalation exposures, many studies administered tert-butanol via intraperitoneal
(i.p.) or intravenous (i.v.) injection. While these studies do not inform the absorption of tert-
butanol, they can provide information on its distribution, metabolism, and excretion.
B.l.l. Absorption
Toxicity data on tert-butanol 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) or inhalation (6,060 mg/m3 for 6 hours) exposure in male Sprague-Dawley
rats (ARCO. 1983): the absorption rate after inhalation exposure could not be determined, however,
because the blood was saturated with radioactivity after 6 hours of exposure to 6,060 mg/m3. In
another study fFaulkner et al.. 19891. blood concentrations indicated that absorption was complete
at 1.5 hours following the last of six oral gavage doses of 10.5 mmoles tert-butanol/kg (twice daily)
in female C57BL/6J mice. There was an apparent zero-order decline in tert-butanol concentration
for most of the elimination phase, and no differences in absorption or elimination rates were
observed between mice on a repeated dosing regimen and mice administered equivalent volumes
of tap water every 12 hours before administration of a single dose of 10.5 mmoles tert-butanol/kg.
The study therefore concluded that previous exposures did not affect the absorption or elimination
of tert-butanol fFaulkner etal.. 19891.
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B.1.2. Distribution
The available animal data suggest that tert-butanol is distributed throughout the body
following oral, inhalation, and i.v. exposures fPoetetal.. 1997: Faulkner etal.. 1989: ARCO. 19831.
Nihlen etal. (1995) calculated partition coefficients for tert-butanol using blood from human
volunteers and available information about the relative content of water and fat in each tissue. The
calculated tissue:blood partition coefficients for tert-butanol were slightly above 1 (from 1.02 to
1.06) for most tissues, except for fat:blood, which had a partition coefficient of 0.646. The same
study evaluated the partition coefficients of three oxygenated ethers, including MTBE and ETBE,
which are metabolized to tert-butanol (see Section B.1.4). The study concluded that, although tert-
butanol preferentially distributes in body water, the ethers distribute uniformly throughout the
body with a preference for fatty tissues (Nihlen et al.. 1995).
In a study aimed at determining whether tert-butanol (or metabolites) can bind to
a2u-globulin, Williams and Borghoff (2001) exposed F-344 rats to a single gavage dose of 500
mg/kg 14C-tert-butanol and evaluated tissue levels at 12 hours. They found the radiolabel in three
tissues (kidney, liver, and blood) in both sexes, but male rats retained more of the tert-butanol
equivalents than females fWilliams and Borghoff. 20011. Radioactivity was found in the low-
molecular-weight protein fraction isolated from the kidney cytosol in male rats but not in female
rats, indicating that tert-butanol or one of its metabolites was bound to a2U-globulin. Further
analysis determined that tert-butanol, and not its metabolite acetone, was bound. Most tert-butanol
in the kidney cytosol was eluted as the free compound in both males and females, but a small
amount was associated with the high-molecular-weight protein fraction in both males and females.
In another study on a2U-globulin nephropathy, Borghoff et al. f20011 found similar results after F-
344 rats were exposed to 0, 250, 450, or 1750 ppm tert-butanol by inhalation for 8 consecutive
days (with tissue levels measured at 2, 4, 6, 8, and 16 hours postexposure). Male rat tert-butanol
kidney-to-blood ratios were significantly elevated over ratios in females 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 of tert-butanol 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-l. Urinary metabolites of tert-butanol in a human male volunteer who
ingested a gelatin capsule containing 5 mg/kg [13C]-tert-butanol were reported to be 2-methyl-l,2-
propanediol (MPD) and 2-hydroxyisobutyrate (HBA) fBernauer et al.. 19981. 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, but no information regarding
informed consent was reported. In the same study, HBA, MPD, and tert-butanol sulfate were
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identified as major metabolites in rats, while acetone, tert-butanol, and tert-butanol glucuronides
were identified as minor metabolites fBernauer et al.. 19981. Baker etal. f!9821 found that tert-
butanol was a source of acetone, but acetone production might have been stimulated from other
sources.
No studies identified specific enzymes responsible for biotransforming tert-butanol. Using a
purified enzyme from Sprague-Dawley rats or whole-liver cytosol from Wistar rats, alcohol
dehydrogenase had negligible or no activity toward tert- butanol fVidela etal.. 1982: Arslanian etal..
19711. Other in vitro studies have implicated the liver microsomal mixed function oxidase (MFO)
system, namely cytochrome P450 (CYP450) fCederbaum etal.. 1983: Cederbaum and Cohen. 19801.
In the 1983 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
formaldehyde production at a rate of approximately 25 nmoles/mg protein/30 min. According to
study authors, the amount of formaldehyde generated by tert-butanol was approximately 30% of
the amount of formaldehyde formed during the metabolism of 10 mM aminopyrene in a similar
microsomal system. The rate of formaldehyde generation from tert-butanol 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 in the same study,
formaldehyde formation was greatly reduced 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 depended 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 Haber-Weiss iron-catalyzed reaction involving CYP450, which
might serve as the iron chelate fCederbaum and Cohen. 19801.
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CH,
glucuronide-O-
-CH,
CH,
t-butyl glucuronide
rats, humans
CH,
HO-
-CH,
CH3
t-butanol
CYP450
I
rats,
humans
OH
A
ch3 oh
2-methyl-1,2-propanediol
r^
-OH
CH,
rats
V° CH,
.S
O^ \
-CH,
CH,
t-butyl sulfate
HO.
HO-
-CH,
[O]
CH,
2-hydroxyisobutyric acid
formaldehyde
CH,
h3c
acetone
Sources: NSF International (2003), ATSDR (1996), Bernauer et al. (1998), Ambers et al. (1999), and
Cederbaum and Cohen (1980).
Figure B-l. Biotransformation of tert-butanol in rats and humans.
In a follow-up study, tert-butanol was oxidized to formaldehyde and acetone by various
systems known to generate -OH radical, including rat liver microsomes or other nonmicrosomal
•OH-generating systems fCederbaum et al.. 19831. The nonmicrosomal tests included two chemical
systems: (1) the iron-catalyzed oxidation of ascorbic acid (ascorbate-Fe-EDTA
[ethylenediaminetetraacetic acid]) and (2) the Fenton system of chelated ferrous iron and H2O2. In
both Fenton-type systems, H202 served as a precursor for -OH. Additionally, a Haber-Weiss
enzymatic system involving xanthine oxidation 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 (02--).
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 when -OH-scavenging agents (e.g., benzoate, mannitol) were added. Some experiments in
this study of the oxidation of tert-butanol by the microsomal metabolizing system of the liver were
similar to those in the previous study fCederbaum and Cohen. 19801 except that, in addition to
formaldehyde, acetone formation was 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)
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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 tert-
butanol. Finally, typical inducers of CYP450 and its MFO metabolizing activities, such as
phenobarbital or 3-methylcholanthrene, had no effect on microsomal metabolism of tert-butanol to
formaldehyde and acetone. According to the study authors, the oxidation of tert-butanol 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 02-_ might be involved fCederbaum etal.. 19831.
B.1.4. Excretion
Human data on the excretion of tert-butanol derives from studies of MTBE and ETBE
fNihlen et al.. 1998a: 1998b). Eight or 10 male human volunteers were exposed to 5, 25, or 50 ppm
MTBE (18.0, 90.1, and 757 mg/m3) or ETBE (20.9,104, and 210 mg/m3) 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). In both studies, the
urinary excretion of tert-butanol was less than 1% of the uptake or absorption of MTBE or ETBE.
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).
Ambergetal. f20001 exposed six volunteers (three males and three females, 28 ± 2 years
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, 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
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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 exposure to both concentrations.
Ambergetal. f20001 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 atthe 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 generally constant fraction of the administered radioactivity (23-33%) was
recovered in the urine at 24 hours postdosing. Only 9% of a 1500-mg/kg administered dose was
recovered in urine, however, suggesting that the urinary route of elimination is saturated following
this dose fARCO. 19831. Among all tested doses, most of the urinary radiolabel was attributed to a
polar fraction that was not characterized, while only 0.3-5.5% of the administered dose was
considered tert-butanol. The saturation in urinary elimination of radioactivity with the increased
dose was considered a manifestation of saturated metabolic capacity; however, no further
information was provided on the fate or balance of the administered radiolabel at any of the tested
tert-butanol doses fARCO. 19831.
Borghoff and Asgharian T19961 evaluated the disposition of 14C radiolabel in F344 rats and
CD-I mice after nose-only inhalation exposure to 500,1750, or 5,000 ppm 14C-ETBE for six hours.
Besides recovery of total radioactivity in urine, feces, and expired air, air and urine samples were
analyzed for ETBE and tert-butanol. Urine samples were also analyzed for tert-butanol metabolites
HBA and MPD, and 14C02 was measured in exhaled air. Results were also obtained in rats after 13
days of exposure to 500 or 5,000 ppm ETBE. Total ETBE equivalents in exhaled air and excreted
urine were found to increase linearly with exposure level, with over 90% eliminated by 48 hours
(with the majority of exhalation occurring by 8 hours postexposure). Elimination shifted from being
primarily in the urine at 500 ppm to occurring primarily by exhalation at 5,000 ppm in naive rats,
indicating a saturation of metabolism of ETBE to tert-butanol; this shift was greater in female rats
than males. In rats pre-exposed to 5,000 ppm ETBE for 13 days, most of the excretion was in urine
even at 5,000 ppm. For rats pre-exposed to 500 ppm ETBE, there also was a shift from exhalation to
urinary excretion compared with naive rats, but to a lesser degree than that elicited by the 5,000-
ppm pre-exposure group.
Like rats, the fraction of radiolabel in exhaled volatiles increased with exposure level in
mice while the fraction excreted in urine decreased. The exhalation pattern observed in rats
showed levels of ETBE falling approximately 90% in the first 8 hours postexposure, while levels of
tert-butanol exhaled rose between 0 and 3 hours postexposure and then fell more slowly between 3
and 16 hours, particularly at 5,000 ppm ETBE. The increase in tert-butanol between 0 and 3 hours
postexposure can be explained by the continued metabolism of ETBE during that period. The
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slower decline after 3 hours likely results from a generally slower clearance of tert-butanol, which
is saturated by the higher ETBE exposure levels.
B.1.5. Physiologically Based Pharmacokinetic Models (PBPK)
While no models of tert-butanol have been created independently of other chemicals from
which it arises as a metabolite (e.g., MTBE, ETBE), tert-butanol sub-models have been adapted
specifically to estimate internal doses for administration of tert-butanol. tert-Butanol models are
parameterized using pharmacokinetic studies with tert-butanol exposures. Three physiologically
based pharmacokinetic (PBPK) models have been developed specifically for administration of tert-
butanol in rats Leavens and Borghoff f20091: Salazar etal. f20151. and Borghoff et al. f20161: other
models have incorporated tert-butanol as a submodel following MTBE administration. In Leavens
and Borghoff (2009). tert- butanol is incorporated as a metabolite of MTBE; in Salazar etal. (2015)
and Borghoff et al. (2016). it is incorporated as a metabolite of ETBE. In all three models, inhalation
and oral exposure to tert-butanol can be simulated in rats. A detailed summary of these
toxicokinetic models is provided in a separate report evaluating the PK/PBPK modeling of ETBE
and tert-butanol (U.S. EPA. 2017).
The PBPK model described in Borghoff et al. f20161. with parameters modified as described
by U.S. EPA f20171. was applied to conduct oral-to-inhalation route extrapolation based on an
equivalent internal dose (the average concentration of tert-butanol in the blood). The time to reach
a consistent periodic pattern of tert-butanol blood concentrations ("periodicity"), given the
drinking water ingestion pattern described below, was much shorter than the duration of the oral
bioassay studies. To allow for possible metabolic induction, computational scripts used a simulated
time of 7 weeks, although periodicity was achieved in only a few days without metabolic induction.
The average blood concentration was calculated over the last week of the simulation and was
considered representative of the bioassays. To calculate steady state values for continuous
inhalation exposure, the simulations were run until the blood concentration had a <1% change
between consecutive days. The continuous inhalation exposure equivalent to a given oral exposure
was then selected by identifying the inhalation concentration for which the final (steady-state)
blood concentration of tert-butanol matched the average concentration from water ingestion, as
described above.
For simulating exposure to drinking water, the consumption was modeled as episodic,
based on the pattern of drinking observed in rats fSpiteri. 19821. In particular, rats were assumed
to ingest water in pulses or "bouts," which were treated as continuous ingestion, interspersed with
periods of no ingestion. During the active dark period (12 hours/day), it was assumed that 80% of
total daily ingestion occurs (45-minute bouts with alternating 45-minute periods of other activity).
During the relatively inactive light period (12 hours/day), it was assumed that the remaining 20%
of daily ingestion occurs; during this time, bouts were assumed to last 30 minutes with 2.5 hours in
between. This resulting pattern of drinking water ingestion is thought to be more realistic than
assuming continuous 24 hours/day ingestion (see Figure B-2).
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o IIII IIII II—u—U—U—IIIII1111IIII111II—u—u—U—
0 6 12 18 24 30 36 42 48
Time (h)
Figure B-2. Example oral ingestion pattern for rats exposed via drinking
water.
PBPK modeling was also used to evaluate a variety of internal dose metrics (daily average
tert-butanol blood concentration, daily amount of tert-butanol metabolized in liver, daily average of
ETBE blood concentration, and daily amount of ETBE metabolized in liver) to assess their
correlation with different endpoints following exposure to ETBE or tert-butanol fSalazar etal..
20151. Administering ETBE either orally or via inhalation achieved similar or higher levels of tert-
butanol blood concentrations or tert-butanol metabolic rates as those induced by direct tert-
butanol administration (Figure B-3). Altogether, the PBPK model-based analysis by Salazar et al.
(2015) [which applied a model structurally similar to Borghoff et al. (2016)] indicates that kidney
weight, urothelial hyperplasia, and chronic progressive nephropathy (CPN) yield consistent dose-
response relationships using tert-butanol blood concentration as the dose metric for both ETBE and
tert-butanol studies. For kidney and liver tumors, however, a consistent dose-response pattern was
not obtained using any dose metric. These data are consistent with tert-butanol mediating the
noncancer kidney effects following ETBE administration, but additional factors besides internal
dose are necessary to explain the induction of liver and kidney tumors.
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B.1.6. PBPK Model Code
The PBPK acslX model code is available electronically through EPA's Health and Environmental
Research Online (HERO) database. All model files may be downloaded in a zipped workspace from
HERO (TJ.S. EPA. 20161.
B.1.7. PK/PBPK Model Evaluation
PBPK models can be used to perform route-to-route extrapolation of toxicological data. For
tert-butanol, oral-to-inhalation extrapolation was performed using the concentration of tert-
butanol in blood as the internal dose metric. An overview of tert-butanol toxicokinetics, as well as
the scientific rationale for selecting the internal dose metric, is available in the Toxicological
Review. Because the existing human PBPK model was not considered adequate (see below), default
methodologies were applied to extrapolate toxicologically equivalent exposures from adult
laboratory animals to adult humans. For inhalation exposures, the interspecies conversion was the
ratio of animal/human blood:air partition coefficients (La/Lh), according to RfC guidelines for
Category 3 gasses fU.S. EPA. 19941. For oral exposures, extrapolation is performed by body-weight
scaling to the % power (BW3/4) fU.S. EPA. 20111.
All available PBPK models of ETBE and its principal metabolite tert-butanol were evaluated
for potential use in the assessments. A PBPK model of ETBE and its principal metabolite
tert-butanol has been developed for humans exposed while performing physical work fNihlen and
Tohanson. 19991. The Nihlen and Johanson model is based on measurements of blood
concentrations of eight individuals exposed to 5, 25, and 50 ppm ETBE for 2 hours while physically
active. This model differs from conventional PBPK models in that the tissue volumes and blood
flows were calculated from individual data on body weight and height. Additionally, to account for
physical activity, blood flows to tissues were expressed as a function of the workload. These
differences from typical PBPK models preclude allometric scaling of this model to other species for
cross-species extrapolation. As there are no oral exposure toxicokinetic data in humans, this model
does not have a mechanism for simulating oral exposures, which prevents use of the model in
animal-to-human extrapolation for that route.
A number of PBPK models were developed previously for the related compound, methyl
tertiary butyl ether (MTBE) and the metabolite tert-butanol that is common to both MTBE and
ETBE (Borghoffetal.. 2010: Leavens and Borghoff. 2009: Blancato etal.. 2007: Kim etal.. 2007: Rao
and Ginsberg. 1997: Borghoff et al.. 1996). A PBPK model for ETBE and tert-butanol in rats was
then developed by the U.S. EPA (Salazar et al.. 20151 by integrating information from across these
earlier models. Another model for ETBE and tert- butanol was published by Borghoffetal. f 20161.
adapted with modest structural differences from the Leavens and Borghoff (2009) MTBE/tert-
butanol model. Brief descriptions below highlight the similarities and differences between the
MTBE/tert-butanol models of Blancato etal. f20071 and Leavens and Borghoff f20091. and the
ETBE/tert-butanol models of Salazar etal. (2015). and Borghoffetal. (2016).
This document is a draft for review purposes only and does not constitute Agency policy.
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The models of Blancato etal. (2007) and Leavens and Borghoff(2009)
The Blancato etal. f20071 model is an update of the earlier Rao and Ginsberg f!9971 model,
and the Leavens and Borghoff f20091 model is an update of the Borghoff et al. f 19961 model. Both
the Blancato etal. f20071 and Leavens and Borghoff f20091 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. 19911. The parent (MTBE) and metabolite
(tert-butanol) models are linked by the metabolism of MTBE to tert-butanol in the liver. Oral and
inhalation routes of exposure are included in the models for MTBE; Leavens and Borghoff f20091
also included oral and inhalation exposure to tert-butanol. Oral doses are assumed 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 enter the
systemic blood supply directly, and the respiratory tract is assumed to be at 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 2-methyl-l,2-
propanediol (MPD) and hydroxyisobutyric acid (HBA); the total metabolic clearance of tert-butanol
by both processes is described by a single Michaelis-Menten equation in the models. All model
assumptions are considered valid for MTBE and tert-butanol.
In addition to differences in fixed parameter values between the two models and the
addition of exposure routes for ter-butanol, the Leavens and Borghoff (20091 model has three
features not included in the Blancato etal. f20071: (1) the alveolar ventilation was reduced during
exposure, (2) the rate of tert-butanol metabolism increased over time due to account for induction
of CYP enzymes, and (3) binding of MTBE and tert-butanol to a2U-globulin was simulated in the
kidney of male rats. The Blancato etal. (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 below.
MTBE and tert-butanol binding to a2U-globulin in the kidneys of male rats were
incorporated in the PBPK model of MTBE by Leavens and Borghoff f20091. Binding to a2U-globulin
is one hypothesized mode of action for the observed kidney effects in MTBE-exposed animals. For a
detailed description of the role of a2U-globulin and other modes of action in kidney effects, see the
kidney mode of action section of the Toxicological Review (Section 1.2.1). In the Leavens and
Borghoff (2009) model, binding of MTBE to a2u-globulin was applied to describe sex differences in
kidney concentrations of MTBE and tert-butanol, but acceptable estimates of MTBE and tert-
butanol pharmacokinetics in the blood are predicted in other models that did not consider
This document is a draft for review purposes only and does not constitute Agency policy.
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a2u-globulin binding. Moreover, as discussed below, the U.S. EPA's implementation of the Leavens
and Borghoff f2 0091 model did not adequately fit the available tert-butanol i.v. dosing data, adding
uncertainty to the parameters they estimated.
The Blancato etal. f20071 and Leavens and Borghoff f20091 PBPK models for MTBE were
specifically evaluated by comparing predictions from the tert-butanol portions of the models with
the tert- butanol i.v. data of Poet etal. (1997) (see Figure 1). 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.
300 mg/kg
~
male
o
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75 mg/kg
•
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o
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A
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— 150 mg/kg ¦ male ° female
75 mg/kg • male o female
37.5 mg/kg * male a female
1000
0.1-1 , T , 'r v-
0 2 4 6 8 10 12 14 16 18 20 22 24
time (hours)
4 6 8 10 12 14 16 18 20 22 24
time (hours)
Figure 1. Comparison of the tert-butanol portions of existing MTBE models
with tert-butanol blood concentrations from i.v. exposure hv Poet etal.
(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 model ofSalazar et al. (2015)
To better account for the tert-butanol blood concentrations after intravenous tert-butanol
exposure, the model by Leavens and Borghoff f20091 was modified by adding a pathway for
reversible sequestration of tert-butanol in the blood (Salazar et al.. 2015). Sequestration of tert-
butanol was modeled using an additional blood compartment, which tert-butanol can enter
reversibly, represented by a differential mass balance (see Figure 2). Other differences in model
structure are that the brain was included in the other richly perfused tissues compartment and
binding to a2U-globulin was not included. Binding to a2U-globulin was neglected since it was
assumed to not significantly affect the blood concentration or metabolic rate of ETBE of tert-
butanol, the two dose metrics being used for route-to-route extrapolation. This model improved the
fit to tert- butanol blood concentrations after tert-butanol i.v. exposures (see Salazar etal. (2015)).
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Additionally, the model adequately estimated the tert-butanol blood concentrations after inhalation
and oral gavage exposures. The ETBE sub-model was based on the MTBE component of the
Leavens and Borghoff f20091 model. The model assumed two-pathways for metabolism of ETBE to
tert-butanol, and the metabolic parameters were optimized to fit toxicokinetic data. Partition
coefficients of ETBE were based on data of Nihlen and Tohanson f 19991.
ETBE TBA
Inhalation Exhalation Inhalation Exhalation
Dose
Figure 2. Schematic of the Salazar et al. (2015) PBPK model for ETBE and its
major metabolite tert-butanol in rats. Exposure can be via multiple routes
including inhalation, oral, or i.v. dosing. Metabolism of ETBE and tert-butanol occur
in the liver and are described by Michaelis-Menten equations with two pathways for
ETBE and one for tert-butanol. ETBE and tert-butanol are cleared via exhalation,
and tert-butanol is additionally cleared via urinary excretion.
The model ofBorghoffet al. (2016)
The Borghoff et al. (2016) models for ETBE and tert-butanol were based on Leavens and
Borghoff (20091. including binding of ETBE and tert-butanol to a2u-globulin and induction of tert-
butanol metabolism, with some structural changes. The revised model lumped gastrointestinal
tract tissue and brain tissue into the richly perfused compartment (Leavens and Borghoff (20091
modeled these compartments separately). Borghoff et al. f 20161 assumed that urinary clearance
was a function of central venous blood concentration and effectively occurs from that compartment,
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as opposed to clearance from the kidney venous blood assumed by Leavens and Borghoff ("2009").
Using the new structure, urinary clearance was re-parameterized to fit the intravenous data by Poet
etal. ("19971. The model assumed a single oxidative metabolic pathway for metabolism of ETBE to
tert- butanol using parameters from Rao and Ginsberg ("19971, instead of the two-pathway models
assumed by Leavens and Borghoff ("20091 (for MTBE) and Salazar etal. ("20151. The model did not
incorporate the tert-butanol blood sequestration kinetics included in the tert-butanol model. It did,
however, incorporate the oral absorption rate of tert- butanol estimated by Salazar etal. ("20151.
Partition coefficients for ETBE were obtained from ("Kaneko etal.. 20001. and metabolic parameters.
Rate constants for binding of ETBE to a2u-globulin and its dissociation were assumed to be the same
as estimated for MTBE by Leavens and Borghoff ("2009"). Finally, unlike the Leavens and Borghoff
("20091 model. Borghoff et al. ("20161 assumed a lower-bound alveolar ventilation for all times and
exposures, not just during periods of inhalation exposure.
To simulate induction of tert-butanol metabolism, the default metabolic rate of tert-butanol
clearance is multiplied by an exponential function of the form [1 + Afl-e^)], where A is the
maximum fold increase above baseline metabolism, and k is the rate constant for the ascent to
maximum induction. Because metabolic induction does not occur instantaneously, but involves a
delay for induction of RNA transcription and translation, Borghoff et al. f20161 assumed that
induction did not begin until 24 hour after the beginning of exposure. But the computational
implementation then treated the effect as if the enzyme activity suddenly jumped each 24 h to the
level indicated by the time-dependent equation shown in the paper. This step-wise increase in
activity was not considered realistic. Therefore, in evaluating the impact of induction, the U.S. EPA
treated the induction as occurring continuously with time but beginning at 12 h after the start of
exposure. This change would not impact long-term steady-state or periodic simulations, in
particular those used to characterize bioassay conditions, but has a modest effect on simulations
between 12 h and 24 h, which are compared to experimental data below for the purpose of model
validation. However, with further review of the existing data on liver histology, which would also
reflect metabolic induction if it occurs, as detailed below, the U.S. EPA determined that it is likely to
only occur at the very highest exposure levels and hence not at levels where the model is applied
for route-to-route extrapolation. Therefore, the maximal induction was set to zero unless
otherwise noted.
The form of the equations for hepatic metabolism in the Borghoff et al. f20161 model was
revised to be a function of the free liver concentration, specifically the concentration in the venous
blood leaving the liver or "CVL", rather than the concentration in the liver tissue or "CL". In order to
maintain the integrity of all prior model simulations and parameter estimations, EPA updated the
Michaelis-Menten constants ("Km's") for ETBE and tert-butanol by scaling them by the liver:blood
partition coefficients. As a result, the model produces identical results as before without re-
estimating a fitted parameter.
This document is a draft for review purposes only and does not constitute Agency policy.
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Finally, a discrepancy between the pulmonary ventilation value as described by Borghoff et
al. f20161. in particular as the lower limit of values reported by Brown etal. fl997I should be
noted. Borghoff et al. f 20161 claim that an allometric coefficient of 18.9 L/h/kg0-75 (allometric
coefficient provided here reflects actual use in model code) is the lower limit For a 0.25 kg rat, this
value yields an absolute ventilation rate of 6.6822 L/h or 111.37 ml/min. In Table 31 of Brown et
al. (1997) the mean and range of values given for the rat are 52.9 and 31.5-137.6 ml/min/(100g
BW). From the text immediately following this table, it is clear that these mean and range are not
scaled to BW0-75, but exactly as indicated. Hence for a 250 g rat they correspond to 132.25 and
78.75-344 ml/min. Hence use of 18.9 L/h/kg0-75 corresponds to a ventilation rate 61% of the way
between the lower limit and the mean for a 0.25 kg rat It can be noted that 31.5 ml/min/(100g
BW), the actual lower limit, equals 18.9 L/h/kg10; i.e., the respiration per kg BW, not per (kg
BW)075. Thus, the discrepancy appears due to a mistaken translation in allometric scaling.
The fact that Borghoff et al. (2016). and Leavens and Borghoff (2009). used a ventilation
rate closer to the mean than the lower limit may explain why it was also necessary to incorporate a
fraction of tert-butanol available for alveolar absorption of 0.6. From considering the plots of
model simulations vs. data below, it appears that model fits to the data would be improved by
further decreasing ventilation, which could now be justified. But the U.S. EPA has chosen to keep
the value of QPC and absorption fraction as published by Borghoff et al. (2016).
ETBE TBA
Inhalation Exhalation Inhalation Exhalation
Dose
Figure 3.
Schematic of the Borghoff et al. (2016) PBPK model for ETBE and its major metabolite
tert-butanol in rats.
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Supplemental Information—tert-Butyl Alcohol
Table 1. PBPK model physiologic parameters and partition coefficients*
Body weight and organ volumes as fraction of body weight
Body Weight (kg)
0.25
Brown et al. (1997)
Liver
0.037
Brown et al. (1997)
Kidney
0.0073
Brown et al. (1997)
Fat
0.35xBW + 0.00205
Brown et al. (1997)
Richly perfused (total)
0.136
Brown et al. (1997)
Richly perfused
0.0177
a
Poorly perfused (total)
0.757
Brown et al. (1997)
Poorly perfused
0.75495-0.35xBW
Blood
0.074
Brown et al. (1997)
Rest of body (not perfused)
0.107
Brown et al. (1997)
Cardiac output and organ blood flows as fraction of cardiac output
Cardiac output (L/hr-kg)
18.9
Brown et al. (1997)b
Alveolar ventilation (L/hr-kg)
18.9
Brown et al. (1997)b
Liver
0.174
Brown et al. (1997)°
Kidney
0.141
Brown et al. (1997)
Fat
0.07
Brown et al. (1997)
Richly perfused (total)
0.47
d
Richly perfused
0.155
e
Poorly perfused (total)
0.53
Brown et al. (1997)
Poorly perfused
0.46
f
Partition coefficients for ETBE
Blood:air
11.6
Kaneko et al. (2000)
Liver:blood
2.9
Kaneko et al. (2000)
Fat:blood
11.7
Kaneko et al. (2000)
Richly perfused:blood
2.9
Kaneko et al. (2000)
Poorly perfused:blood
1.9
g
Kidney:blood
2.9
h
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)
Richly perfused:blood
0.83
Borghoff et al. (1996)
Poorly perfused:blood
1.0
Borghoff et al. (1996)
Kidney:blood
0.83
Borghoff et al. (2001)
*Values have been updated to incorporate corrections from a QA review and to include values to the number of
digits used in the model code.
a0.165 - Z(kidney,liver.blood)
bLower limit of alveolar ventilation for rat reported in Brown et al. (1997); alveolar ventilation is set equal to
cardiac output
csum of liver and gastrointestinal (Gl) blood flows.
i Brown et al. (1997) only accounts for 94% of the blood flow. This assumes unaccounted 6% is richly perfused.
'0.47- Z(kidney, liver)
f0.53- fat
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Supplemental Information—tert-Butyl Alcohol
1 Table 2. PBPK model rate constants
Parameter
Value
Source or Reference
te/t-butanol rate constants
TBA first order absorption constant (1/h)
5.0
Salazar et al. (2015)
Fraction of TBA absorbed in alveolar region
0.6
Medinsky et al. (1993)
Urinary clearance of TBA (L/h/kg075)
0.015
Borghoff et al. (2016)
Scaled maximum metabolic rate of TBA (nmol/h/kg)
54
Borghoff et al. (1996), Rao and Ginsberg (1997)
Michelis-Menten constant (nmol/L)
4571
Borghoff et al. (1996), Rao and Ginsberg (1997)
Maximum percentage increase in metabolic rate
0.0
124.9 used by Leavens and Borghoff (2009)
Rate constant for ascent to maximum (1/day)2
0.3977
Leavens and Borghoff (2009)
ETBE rate constants
ETBE first order absorption constant (1/h)
1.6
Leavens and Borghoff (2009)
Scaled maximum metabolic rate of ETBE (nmol/h/kg075)
499
Rao and Ginsberg (1997)
Michelis-Menten constant for ETBE (nmol/L)
4301
Rao and Ginsberg (1997)
a2u-globulin binding parameters
Steady-state free kidney a2u-globulin (nmol/L)
5503
Leavens and Borghoff (2009)
First order constant for hydrolysis of free a2u (1/h)
0.31
Leavens and Borghoff (2009)
First order constant for hydrolysis of bound a2u (1/h)
0.11
Leavens and Borghoff (2009)
Second order binding constant for TBA to a2u (L/nmol/h)
1.3
Leavens and Borghoff (2009)
a2u dissociation constant for TBA (nmol/L)
120
Leavens and Borghoff (2009)
First order constant for unbinding of TBA from a2u (1/h)
Calculated4
Second order binding constant for ETBE to a2u (L/nmol/h)
0.15
Leavens and Borghoff (2009)
a2u dissociation constant for ETBE (nmol/L)
1
Leavens and Borghoff (2009)
First order constant for unbinding of ETBE from a2u (1/h)
Calculated5
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
1Based on dividing the original values in Borghoff et al. (1996) and Rao and Ginsberg (1997) (used by Borghoff et
al. (20161) by the corresponding liver partition coefficients: 379/0.83 = 457 for te/t-butanol kinetics, and 1248/2.9
= 430 for ETBE kinetic pathway 1.
2Note: model revised from a daily stepwise induction change to a continuous change (with a 12-hour time lag),
while still maintaining the default parameters.
3Based on values ranging from ~160 to 1000 nmol/L (Carruthers et al., 1987; Charbonneau et al., 1987; Olson et al.,
1987; Stonard et al., 1986).
4Product of a2u dissociation constant for te/t-butanol and second order binding constant for te/t-butanol to a2u.
5Product of a2u dissociation constant for ETBE and second order binding constant for ETBE to a2u.
Toxicokinetic data extraction and selected model outputs
Data extraction and adjustments
The ARCO T19831 study reported tert-butanol blood levels after oral gavage exposure,
primarily as tert-butanol equivalents based on total 14C activity, which does not distinguish
between tert-butanol and its metabolites. However, for oral doses of 1 and 500 mg/kg, the fraction
of activity identifiable as tert-butanol were also reported, although not at identical time-points.
Therefore, empirical bi-exponential curves (Figure 3) were used to interpolate between the time-
points when total tert-butanol equivalents were measured to estimate total equivalents at other
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
times. The total equivalents calculated this way were then multiplied by the fraction of tert-butanol
reported at 0.5, 3, 6, and 12 h for 1 mg/kg fARCO f!9831. Table 24) and 500 mg/kg fARCO f!9831.
Table 25) to obtain the data used for PBPK modeling (Table 4).
2 n
T3
§ 1.6 -
¦Q
—I
E
>1.2 -
c
Q)
(O
>
O"
CD
<
CO
H
tuo
3.
0.8 -
0.4 -
1 mg/kg
> ARCO (1983) data
^—bi-exponential model
- ARCO (1983) regression
2 4 6
Time (h)
8
10
500
T3
o 400
500 mg/kg
ARCO (1983) data
-ARCO (1983) regression
8 12 16
Time (h)
20 24
Time-course data and empirical regressions for tert-butanol equivalents in rats following oral
exposure to 1 or 500 mg/kg 14C-TBA fARCO. 1983). For 1 mg/kg, the single exponential regression
reported by ARCO (1983) was 1.73*exp(-0.0946*t) (dashed line), but it did not appear to adequately
fit the data. A bi-exponential regression (solid line) was found by minimizing the sum of square
errors between the regression and data in Excel: 0.4874*exp(-0.7055*t) + 1.404*exp(-0.06983*t).
For 500 mg/kg the bi-exponential regression reported by ARCO Q9831 appeared sufficient:
554*exp(-0.0748*t) - 426*exp(-3.51*t).
Figure 4. tert-Butanol PK Data for 1 and 500 mg/kg Oral Exposures from ARCO
T19R3V
The single-dose data from TPEC (2008b) were taken from Appendix Table 12 of that report
The values for the P-5 component were converted from ETBE equivalents to mg/L tert-butanol. For
example, at 5 mg/kg/d, 416 ng ETBE-eq/mL is reported for P-5 in animal # 17. The corresponding
concentration in mg/L for tert-butanol are then calculated as (416 ng ETBE-eq/mL)*(1000
mL/L)*(10"6 mg/ng)*(74.12 [MW tert-butanol])/(102.17 [MWETBE]) = 0.302 mg tert-butanol-
eq/L. Likewise the data for the repeated dose study TPEC (2008a). days 7 and 14, were converted
from the P-5 values in Appendix Table 7, p. 53 of that report (The data from the single-dose study
were combined with the day 7 and 14 data from the multiple dose study for comparison with model
simulations of 14-day dosing.)
The JPEC (2008a,b) studies measured tert-butanol in plasma only, unlike the Poet et al.
f!9971 and Leavens and Borghoff f20091 studies, which measured tert-butanol in whole blood.
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Supplemental Information—tert-Butyl Alcohol
1 Based on the measurements of plasma and whole blood by JPEC (2008a,b), the concentration of
2 tert-butanol in plasma is approximately 130% of the concentration in whole blood (Table 5). The
3 tert-butanol plasma concentrations measured by JPEC were therefore divided by 1.3 to obtain the
4 expected concentration in whole blood for comparison with the PBPK model.
5
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Supplemental Information—tert-Butyl Alcohol
1 Table 3. Summary of pharmacokinetic data used for model calibration and evaluation
Exposure
Measured
Data source
Fig. # in
Salazar et
al. (2015)
Conversion
Notes
Chemic
al
Route
Chemi
cal
Mediu
m
TBA
iv
TBA
blood
Poet et al. (1997) Fig.
1 & 2
3A
HM to mg/L
digitized from the figure
inhala
tion
TBA
blood
Leavens and Borghoff
(2009) Fig. 8A-B
3B
HM to mg/L
digitized from the figure,
showing only 1 day of
exposure
oral
gavag
e
TBA
blood
ARCO (1983), % total
TBA, Tables 24-25;
TBA equivalents, Fig
6
3C
TBA
equivalents to
TBA
concentration
ETBE
oral
gavag
e
TBA
blood
JPEC (2008b)
Appendix 12 (JPEC,
2008b)
4A
ETBE
equivalents to
mg/L TBA
"P5" is TBA
TBA
urine
JPEC (2008b)
Appendix 13
4B
ETBE
equivalents to
mg/L TBA
"P5" is TBA
ETBE
inhala
tion
ETBE
blood
Amberg et al. (2000)
Table 5
4C
HM to mg/L
TBA
blood
Amberg et al.
(2000)Table 5
4D
HM to mg/L
TBA
urine
Amberg et al. (2000)
Table 6 and Fig 4
4E
HM to mg/L
ETBE
exhale
d air
Borghoff (1996)
4F
Hmoles to mg
cumulative mass
TBA
exhale
d air
Borghoff (1996)
4G
Hmoles to mg
cumulative mass
TBA
inhala
tion
TBA
blood
Leavens and Borghoff
(2009) Fig 8B
5A-B
HM to mg/L
digitized from the figure
TBA
blood
Leavens and Borghoff
(2009) Fig 8A
5C-D
HM to mg/L
digitized from the figure
ETBE
oral
gavag
e
TBA
blood
JPEC (2008b)
Appendix 12
5E
ETBE
equivalents to
mg/L TBA
"P5" is TBA
2
3
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Supplemental Information—tert-Butyl Alcohol
1 Table 4. Conversion of ABCO (1983) total tert-butanol equivalents and serum fraction data to tert-
2 butanolconcentrations
Time
(h)
% TBA1
Total TBA equivalents
interpolated (ng/ml)2
TBA concentration using interpolated
equivalents (|jg/mL = mg/L)3
Total TBA equivalents measured at
nearest time-point (time measured)'
1 mg/kg data
0.5
57.3
1.6982
0.9731
1.69 (0.5 h)
3
25
1.1972
0.2993
1.26 (2.67 h)
6
18.1
0.9304
0.1684
0.97 (5.33 h)
12
1
0.6074
0.006074
0.68 (10.67 h)
500 mg/kg data
0.5
22.9
460.0
105.34
445 (0.5 h)
3
20.4
442.6
90.30
438 (2.67 h)
6
18.7
353.7
66.14
393 (5.33 h)
12
18.5
225.8
41.77
269 (10.67 h)
3 1 From Table 24, p. 48 of ARCO (1983) (1 mg/kg) and Table 25, p. 49 of ARCO (1983) (500 mg/kg)
4 2 Using bi-exponential functions given in the legend of Figure B-new
5 3 Values used in PBPK modeling; %TBA x total TBA equivalents interpolated
6 4 From Table 14, p. 32 of ARCO (1983) (1 mg/kg) and Table 11, p. 27 of ARCO (1983) (500 mg/kg)
7 5 %TBA x total TBA equivalents at nearest time-point
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Supplemental Information—tert-Butyl Alcohol
1 Table 5. Ratio of 14C activity in blood vs. plasma after 14C-ETBE exposures in rats (JPEC 2008a,b)
Time (h)
Animal #
Plasma
(ng 14C-eq/mL)
Blood
(ng 14C-eq/mL)
Plasma/Blood (%)
Single dose, JPEC (2008b) AppendixTable 5, d. 94
8
97
78133
40667
192.1%
98
95533
80000
119.4%
99
89367
64667
138.2%
100
72400
62333
116.2%
24
37
10900
8800
123.9%
38
19133
14433
132.6%
39
19433
15400
126.2%
40
30767
22967
134.0%
72
41
2133
1600
133.3%
42
2833
3033
93.4%
43
4033
3200
126.0%
44
3167
2333
135.7%
Mean ± SD
130.9 ± 22.8%
Single dose, JPEC (2008b) AppendixTable 3, p. 91
8
17
2853
1784
159.9%
18
2850
1802
158.2%
19
2629
1568
167.7%
20
3918
2718
144.2%
24
21
1692
1255
134.8%
22
846.7
642.9
131.7%
23
1048
785
133.5%
24
761.7
591.3
128.8%
72
25
49.6
40
124.0%
26
34.2
29.2
117.1%
27
79.2
60.8
130.3%
28
107.9
84.6
127.5%
168
29
12.9
13.3
97.0%
30
17.5
13.8
126.8%
31
26.7
24.2
110.3%
32
40
35.8
111.7%
Mean ± SD
131.5 ± 18.9%
Repeated dose, JPEC (2008a), AppendixTable 3, p. 49
8 (7 days dosing)
3789
3029
125.1%
5041
3988
126.4%
4914
3938
124.8%
5608
4638
120.9%
24 (7 days dosing)
2740
1908
143.6%
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Supplemental Information—tert-Butyl Alcohol
3433
2575
133.3%
2488
1888
131.8%
963.3
812.5
118.6%
8 (14 days dosing)
5665
4546
124.6%
5175
4075
127.0%
3889
3058
127.2%
5090
3858
131.9%
24 (14 days dosing)
2003
1508
132.8%
2121
1692
125.4%
1948
1354
143.9%
1037
804.2
128.9%
72 (14 days dosing)
1378
1138
121.1%
301.3
245.8
122.6%
110
N.D.
421.3
337.5
124.8%
Mean ± SD
128.1 ±6.85%
Selected model comparisons applying the Borghoffet al. (2016) model
The modeling code was obtained by the authors ofBorghoffetal. f20161. The modeling
language and platforms is acslX (Advanced Continuous Simulation Language, Aegis, Inc., Huntsville,
Alabama).
The following modifications were made:
1- Periodic drinking water pathway was incorporated into the CSL file, and the continuous oral
dose rate function was modified slightly to improve flexibility of the model.
2- For simulations showing the effect of including enzyme induction, the code was modified
slightly in the CSL file to improve continuity. Daily step functions in metabolic chances were
replaced with a continuous function but delayed by 12 h.
3- Otherwise enzyme induction was not used (set to zero).
4- In the PBPK model code, the changes to the Michaelis-Menten constants described as
footnotes in Table 2 above were not made in the PBPK parameter script (MTBEparam.m).
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Instead, parameters were re-defined in the core model *CSL file as scaling calculations in
the parameters section of the INITIAL bloc;
Kmlvetbe = Kmletbe/Pletbe
Km2vetbe = Km2etbe/Pletbe
Kmvtba = Kmtba/Pltba
5- Tissue volumes and the rate of hydrolysis of free a2u-globulin were corrected (slightly] to
values shown in Table 1.
6- All model scripts previously used to evaluate model fits of the Salazar etal. f20151 model
were adapted to run the Borghoff etal. (2016) model. Model parameters were set to
uniform values for all simulations highlighted in this section, unless otherwise noted.
7- Digitized data from Ambergetal. (20001 were updated subsequent to a QA review.
8- Tabulated data from Borghoff and Asgharian T19961 were updated subsequent to a QA
review.
The PBPK acslX model code is available electronically through EPA's Health and
Environmental Research Online (HERO) database. All model files may be downloaded in a zipped
workspace from HERO fU.S. EPA. 20161. The model contains workspaces for the EPA
implementation of Salazar et al. f20151 model, the un-changed version of the of Borghoff et al.
(2016) model, and the EPA implementation of the of Borghoff etal. (2016) model
Selected model outputs compared to experimental datasets are provided below.
(A) (B)
(C)
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1,000 -
en
£
C
o
100-
10-
TBA gavage exposures
o
_o
_Q
<
CD
0.1 -
0.01 -
500 mg/kg
1 mg/kg
A 500 mg/kg data
# 1 mg/kg data
—I—
10
—r
12
Time (h)
Source: (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).
Figure 5. Comparison of the Borghoff et al. (2016) model predictions with measured tert-
butanol blood concentrations for i.v., inhalation, and oral gavage exposure to te/f-butanol.
The model results for the i.v. data are significantly improved from the Blancato et al. f20071
and Leavens and Borghoff f2009) model results presented previously. As evident here and
in the Borghoff etal. f20161 study the Borghoff et al. f20161 model generally over-predicts
tert-butanol blood and urine concentrations. Some attempts were made to improve model
fit in the EPA model implementation (such as adjusting inhalation, urinary, and induction
parameter values), however the default values were maintained in the final model.
Figure 6. Comparison of Borghoff et al. (20161 model predictions with
measured amounts of tert-butanol after oral gavage of ETBE.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
The data points show the measurements from the four individual rats in the IPEC f2008b1 study. The
concentrations of tert-butanol in blood are shown in A). The amount of tert-butanol in urine is shown in B],
Note that the over-prediction of tert-butanol in urine (B) is by a factor 3-10-fold.
The predictions of the model are compared with amounts measured by Amberg etal. (2000) after
ETBE inhalation in Figure 6-A. The prediction of the tert-butanol blood concentrations are slightly
higher than was measured. The tert-butanol blood concentration would be reduced if exposed
animals were reducing their breathing rate or other breathing parameters but the exposure
concentration of ETBE exposure are unlikely to be high enough to cause a change in breathing
parameters because at the much higher ETBE concentration in the ARCO T19831 study (5,000 ppm),
changes in breathing were not noted, the model already uses a lower bound estimate of respiration
rate and cardiac output for all simulations, and the model predictions fit most measured
concentrations well. However, the urinary elimination of tert-butanol is significantly overestimated
(~ 3-10-fold) by the tert-butanol submodel (Figure 6-B)
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
® 0,07 -
~ 0.06-
v
c 0,05-
= 0,04-
¦- 0.03-
4
£ 0.02-
0.01 -
3 Figure 7. Comparison of Borehoff et al, f2016) model predictions with
4 measured amounts after a 4-hour inhalation exposure to 4 and 40 ppm ETBE.
5 Concentrations in blood are shown in A] for ETBE, B] for tert-butanol. The amount of tert-butanol in urine is
6 shown in C] for the 40 ppm exposure. The data are from Amberg et al. (20001.
7
0 2 4 6 8 10 12
Time (h)
0.09 -
0.08 -
t 1 1 1 1 1 r
0 2 4 6 8 10 12
Time (h)
i i =i i ; t r
0 6 12 18 24 30 36
Time (h)
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
500 ppm, model
1750 ppm, model
5000 ppm, model
• 500 ppm, data
¦ 1750 ppm, data
, A 5000 ppm, data ^
1,000 4
800 ¦
600 -
400 -
"5 200 -
E
3
U
0 -
C 375
O
E
^ 300
¦o
X 225
J2 75
3
E
3 o
150 -
*i 1 1 1 r
0 4 8 12 16
Time after exposure (h)
"i 1 1 1 r
0 4 8 12 16
Time after exposure (h)
B. ETBE exhaled; male rats
D. TBA exhaled; male rats
A. ETBE exhaled; female rats
C. TBA exhaled; female rats
Figure 8. Comparison of Borghoff et al. (2016) model predictions with measured amounts
of A) ETBE and B} te/t-butanol in exhaled breath after a 6-hour inhalation exposure to 500,
1750, and 5,000 ppm ETBE.
The data points are from the Borghoff and Asgharian (1996)) study. The model significantly over predicted
exhaled breath of both ETBE and tert-butanol following ETBE inhalation exposure for male rats and the exhaled
tert-butanol for female rats. The model currently assumes that 100% of inhaled ETBE, though only 60% of
inhaled tert-butanol, is available for alveolar absorption. The inhalation availability may have a significant
impact on estimated exhaled breath amounts, but was not adjusted to fit this data set.
This document is a draft for review purposes only and does not constitute Agency policy.
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— 500 H
E
*w»
C
O
400
Male rats, no induction
I
300
c
V
u
c
o
(J
-Q
O
o
<
cfl
I-
200 -
100
T
96 144
Time (h)
Female rats, no induction
Male rats with induction
c 400
o
0 48 96 144 192
Time (h)
Female rats with induction
-r-
48
—r~
96
—P_
144 192
Time (h)
Time (h)
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 fBorghoff et al.. 20011. 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).
Figure 9. Comparison of the Borghoff et al. f2016) model predictions with
measured amounts of tert-butanol in blood after repeated inhalation
exposure to tert-butanol.
The increased tert-butanol metabolism better estimates the measured tert-butanol blood
concentrations as shown in a comparison of the model predictions and experimental
measurements in Figure 9. The male rats have lower tert-butanol blood concentrations after
repeated exposures than female rats and this difference could indicate greater induction of
tert-butanol metabolism in males or other physiologic changes such as ventilation, or urinary
excretion.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Time (h)
Figure 10. Comparison of EPA model predictions with measured amounts of
tert-butanol in blood after 5 mg/kg-day ETBE oral gavage for up to 14 days in
male rats.
The data show the individual measurements of the four rats in the IPEC f2008a. 2008bl study. Adding
enzyme induction to the model has a small effect on the predicted tert-butanol blood concentrations and the
model predictions are closer to measured data when induction is not included.
References
Amber g. A: Rosner. E: Dekant. W. (2000). Biotransformation and kinetics of excretion of ethyl tert-
butyl ether in rats and humans. Toxicol Sci 53: 194-201.
http: / /dx. doi. or g/10.109 3 /toxsci/5 3.2.194
Andersen. ME. (1991). Physiological modelling of organic compounds. Ann Occup Hyg 35: 309-321.
http: //dx. doi. or g/10.109 3 /annhyg/3 5.3.309
ARCO (ARCO Chemical Company). (1983). Toxicologist's report on metabolism and
pharmacokinetics of radiolabeled TBA 534 tertiary butyl alcohol with cover letter dated
03/24/1994. (8EHQ86940000263). Newton Square, PA.
Blancato. IN: Evans. MY: Power. FW: Caldwell. TC. (2007). Development and use of PBPK modeling
and the impact of metabolism on variability in dose metrics for the risk assessment of
methyl tertiary butyl ether (MTBE). J Environ Prot Sci 1: 29-51.
Borghoff. ST. (1996). Ethyl tertiary-butyl ether: Pilot/methods development pharmacokinetic study
in male F-344 rats & male cd-1 mice after single nose-only inhalation exposure, w/cvr ltr
dated 7/29/96. (TSCATS/444664). Chemical Industry Institute of Toxicology (CUT).
Borghoff. ST: Asgharian. B. (1996). Ethyl tertiary-butyl ether (ETBE): Pharmacokinetic study in male
and female CD-I mice after single inhalation exposure and male and female F-344 rats after
single and repeated inhalation exposure. (CUT Protocol 95026). La Palma, CA: ARCO
Chemical Company.
Borghoff. ST: Murphy. TE: Medinskv. MA. (1996). Development of physiologically based
pharmacokinetic model for methyl tertiary-butyl ether and tertiary-butanol in male Fisher-
344 rats. Fundam Appl Toxicol 30: 264-275. http: / /dx. doi. or g/10.10 0 6 /faat. 1996.0064
Borghoff. ST: Parkinson. H: Leavens. TL. (2010). Physiologically based pharmacokinetic rat model
for methyl tertiary-butyl ether; comparison of selected dose metrics following various
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
MTBE exposure scenarios used for toxicity and carcinogenicity evaluation. Toxicology 275:
79-91. :.doi.org/l 0.1016/i.tox.2 010.06.003
Borgfaoff. SIi Prescott. IS: lanszen. DB: Wong. BAi Everitt. II. (2001). alpha2u-Globulin nephropathy,
renal cell proliferation, and dosimetry of inhaled tert-butyl alcohol in male and female F-
344 rats. Toxicol Sci 61: 176-186. http://dx.doi.org/10.1093/toxsciy
Borgfaoff. SI: Ring. C: Banton. MI: Leavens. TL. (2016). Physiologically based pharmacokinetic model
for ethyl tertiary-butyl ether and tertiary-butyl alcohol in rats: Contribution of binding to
a2u-globulin in male rats and high-exposure nonlinear kinetics to toxicity and cancer
outcomes. J Appl Toxicol, fattp: / /dx. doi.org/10.10 0 2/ i at 3 412
Brown. RP: Delo. MP: Lindstedt SL: Rhomberg. LR: Beliles. RP. (1997). Physiological parameter
values for physiologically based pharmacokinetic models [Review], Toxicol Ind Health 13:
407-484. fatt doi.org/10.1177/074823379701300401
Carrutfaers. L: Reeves. K: Paul. M: Searle. A: Templeton. W: Paine. Al (1987). The role of "alpha"2u
globulin synthesis in the production of renal hyaline droplets by iso-octane. Biochem
Pharmacol 36: 2577-2580.
Cfaarbonneau. M: Lock. EA: Strasser. 1: Cox. MG: Turner. Ml: Bus. IS. (1987). 2,2,4-trimethylpentane-
induced nephrotoxicity: I metabolic disposition of TMP in male and female Fischer 344 rats.
Toxicol Appl Pharmacol 91: 171-181.
1PEC (Japan Petroleum Energy Center). (2008a). Pharmacokinetic study in rats treated with [14c]
ETBE repeatedly for 14 days. (P070497). Japan: Kumamoto Laboratory, Mitsubishi
Chemical Safety Institute Ltd.
1PEC (Japan Petroleum Energy Center). (2008b). Pharmacokinetic study in rats treated with single
dose of [14C] ETBE. (P070496). Japan: Kumamoto Laboratory, Mitsubishi Chemical Safety
Institute Ltd.
Kaneko. T: Wang. P. -Y: Sato. A. (2000). Partition coefficients for gasoline additives and their
metabolites. J Occup Health 42: 86-87. fattp://dx.doi.org/10.1539/joh.42.86
Kim. D: Andersen. ME: Pleil, ID: Nvlander-French, LA: Prah. ID. (2007). Refined PBPK model of
aggregate exposure to methyl tertiary-butyl ether. Toxicol Lett 169: 222-235.
fattp ://dx. doi. or g/10.1016/i.toxlet. 2007.01.008
Leavens. TL: Borgfaoff. SI. (2009). Physiologically based pharmacokinetic model of methyl tertiary
butyl ether and tertiary butyl alcohol dosimetry in male rats based on binding to alpha2u-
globulin. Toxicol Sci 109: 321-335. http://dx.doi.org/10.1093/toxsci/kfb049
Medinskv. MA: Kimbell. IS: Morris. IB: Gere rerton. IH. (1993). Advances in biologically based
models for respiratory tract uptake of inhaled volatiles [Review], Toxicol Sci 20: 265-272.
Nifalen. A: lofaanson. G. (1999). Physiologically based toxicokinetic modeling of inhaled ethyl
tertiary-butyl ether in humans. Toxicol Sci 51: 184-194.
http://dx.doi.Org/10.1093/toxsci/51.2.184
Olson. MI: Garg. BP: Murtv, CV: Rov. AK. (1987). Accumulation of alpha 2u-globulin in the renal
proximal tubules of male rats exposed to unleaded gasoline. Toxicol Appl Pharmacol 90: 43-
51. http: //dx.doi.org/10.1016/0041-008Xf87190304-8
Poet. TS: Valentine. IL: Borghoff. SI. (1997). Pharmacokinetics of tertiary butyl alcohol in male and
female Fischer 344 rats. Toxicol Lett 92: 179-186. fatt doi.org/10.1016/SQ378-
4274f97100056-8
Rao. HV: Ginsberg. GL. (1997). A physiologically-based pharmacokinetic model assessment of
methyl t-butyl ether in groundwater for a bathing and showering determination. Risk Anal
17: 583-598. http://dx.doi.Org/10.llll/i.1539-6924.1997.tb00899.x
Salazar. KD: Brinkerhoff, Cf: Lee. IS: Chin. WA. (2015). Development and application of a rat PBPK
model to elucidate kidney and liver effects induced by ETBE and tert-butanol. Toxicol Appl
Pharmacol 288: 439-452. http://dx.doi.Org/10.1016/j.taap.2015.08.015
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Stonard, MP: Phillips, PGN: Foster, 1R: Simpson, MG: Lock, EA. (1986). alpha2u-Globulin:
2 Measurementin ratkidney and relationship to hyaline droplets. Clin Chim Acta 160: 197-
3 203. http://dx.do 39-8981186190142-7
4 U.S. EPA (U.S. Environmental Protection Agency). (1994). Methods for derivation of inhalation
5 reference concentrations and application of inhalation dosimetry [EPA Report] (pp. 1-409).
6 (EPA/600/8-90/066F). Research Triangle Park, NC: U.S. Environmental Protection Agency,
7 Office of Research and Development, Office of Health and Environmental Assessment,
8 Environmental Criteria and Assessment Office.
9 https://cfpub.epa.gov/ncea/risk/recordisplay.cfm?deid=71993&CFID=51174829&CFTOKE
10 N=25006317
11 U.S. EPA (U.S. Environmental Protection Agency). (2011). Recommended use of body weight 3/4 as
12 the default method in derivation of the oral reference dose (pp. 1-50).
13 (EPA/100/R11/0001). Washington, DC: U.S. Environmental Protection Agency, Risk
14 Assessment Forum, Office of the Science Advisor.
15 https://www.epa.gov/risk/recommended-use-body-weight-34-default-method-derivation-
16 oral-reference-dose
17 U.S. EPA (U.S. Environmental Protection Agency). (2016). Model files for tert-butanol and ETBE.
18
19
20 B.2. OTHER PERTINENT TOXICITY INFORMATION
21 B.2.1. Other Toxicological Effects
22 B.2.1.1. Synthesis of Other Effects
23 Effects other than those related to kidney, thyroid, reproductive, developmental, and
24 neurodevelopmental effects were observed in some of the available rodent studies. These include
25 liver and urinary bladder effects. As previously mentioned in the Study Selection section of the
26 Toxicological Review, all studies discussed employed inhalation, oral gavage, or drinking water
27 exposures for >30 days. Studies are arranged in evidence tables by effect, species, duration, and
28 design. The design, conduct, and reporting of each study was reviewed, and each study was
29 considered adequate to provide information pertinent to this assessment.
30 Central nervous system effects similar to those of ethanol (i.e., animals appearing
31 intoxicated and having withdrawal symptoms after cessation of oral or inhalation exposure) were
32 observed with tert-butanol. Severity of central nervous system symptoms increased with dose and
33 duration of exposure. Study quality and utility concerns associated with these studies (e.g.,
34 inappropriate exposure durations, lack of data reporting, small number of animals per treatment
35 group) fGrantand Samson. 1981: Snell. 1980: Thurman et al.. 1980: McComb and Goldstein. 1979a.
36 b; Wood and Lavertv. 19791. preclude an understanding of potential neurotoxicity following tert-
37 butanol exposure; therefore, central nervous system studies are not discussed further.
38 Exposure-response arrays of liver and urinary bladder effects are provided in Figure B-3
39 and Figure B-4 for oral and inhalation studies, respectively.
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Supplemental Information—tert-Butyl Alcohol
Kidney effects
Absolute and relative kidney weight numerical data are presented in Table B-l.
Liver effects
Liver weight and body weight were demonstrated to be proportional, and liver weight
normalized to body weight was concluded optimal for data analysis fBailev etal.. 20041: thus, only
relative liver weight is presented and considered in the determination of hazard. Although some
rodent studies observed liver effects (organ weight changes and histopathologic lesions), the effects
were not consistent across the evidence base . Increases in relative liver weight with tert-butanol
exposure were observed, but the results pertaining to histopathologic changes were inconsistent
(Table B-2 and Table B-3). The NTP (19951 oral subchronic and chronic studies did not observe
treatment-related effects on liver histopathology in either sex of F344 rats. In a 10-week study in
Wistar rats, several liver lesions (including necrosis) and increased liver glycogen were observed in
male rats (no females were included in the study) with the only dose used fAcharva et al.. 1997:
Acharva et al.. 1995). The study provided no incidence or severity data. The dose used in this rat
study was in the range of the lower doses used in the NTP (1995) subchronic rat study. An
increased incidence of fatty liver was observed in the male mice of the highest dose group in the 2-
year mouse bioassay, but no histopathological changes were seen in the subchronic mouse study
(NTP. 1995). No treatment-related effects in liver histopathology were observed in rats or mice of
the NTP T19971 subchronic inhalation study.
Urinary bladder effects
Subchronic studies reported effects in the urinary bladder (Table B-4), although the chronic
studies indicated little progression in incidence with increased exposure. Transitional epithelial
hyperplasia of the urinary bladder was observed in male rats and male mice after 13 weeks of
exposure at doses of 3,610 mg/kg-day (male rats) and >3,940 mg/kg-day (male mice). In rats, the
increase in transitional epithelial hyperplasia of the urinary bladder was not observed in the 2-year
study. Male mice exposed at the high dose (2,070 mg/kg-day) for 2 years exhibited minimal
transitional epithelial hyperplasia of the urinary bladder. Neither female rats nor female mice
showed increased incidences of this lesion. Both sexes of mice demonstrated incidence of minimal
to mild inflammation in the urinary bladder after both subchronic and chronic exposures, with a
greater incidence in males compared with females.
B.2.1.2. Mechanistic Evidence
No mechanistic evidence is available for liver and urinary bladder effects.
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Supplemental Information—tert-Butyl Alcohol
1 B.2.1.3. Summary of Other Toxicity Data
2 Based on lack of consistency and lack of progression, the available evidence does not
3 support liver and urinary bladder effects, respectively, as potential human hazards of tert-butanol
4 exposure.
5
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Supplemental Information—tert-Butyl Alcohol
Table B-l. Changes in kidney weight in animals following exposure to
tert- butanol
Reference and study design
Results
Kidney weight (percent change as compared to control)
Lvondell Chemical Co. (2004)
Males
Sprague-Dawley rat;
12/sex/treatment
Dose
Left absolute Left relative Right absolute
Right relative
Gavage 0, 64,160, 400, or
(mg/kg-d)
weight
weight
weight
weight
1,000 mg/kg-d
0
0
0
0
0
Males: 9 weeks beginning
64
8
8
4 weeks prior to mating
6
6
Females: = 10 weeks (4 weeks
160
9
14*
6
11*
prior to mating through PND21)
400
12*
14*
14*
17*
1,000
18*
28*
20*
31*
Females
Dose
Left absolute Left relative Right absolute
Right relative
(mg/kg-d)
weight
weight
weight
weight
0
0
0
0
0
64
-1
-2
2
0
160
0
0
1
0
400
3
2
4
2
1,000
4
0
7
2
NTP (1995)
Males
Females
F344/N rat; 10/sex/treatment
Dose
Absolute
Relative Dose
Absolute
Relative
40 mg/mL
(mg/kg-d)
weight
weight (mg/kg-d)
weight
weight
M: 0, 230, 490, 840, 1,520,
0
0
0 0
0
0
3,610a mg/kg-d
F: 0, 290, 590, 850, 1,560,
230
12*
19* 290
19*
17*
3,620a mg/kg-d
490
17*
26* 590
16*
15*
13 weeks
840
16*
32* 850
29*
28*
1,520
26*
54* 1,560
39*
40*
3,610
All dead
All dead 3,620
36*
81*
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Supplemental Information—tert-Butyl Alcohol
Reference and study design
Results
NTP (1995)
B6C3Fi mouse; 10/sex/treatment
Drinking water (0, 2.5, 5,10, 20,
40 mg/mL)
M: 0, 350, 640, 1,590, 3,940,
8,210a mg/kg-d
F: 0, 500, 820, 1,660, 6,430,
11,620a mg/kg-d
13 weeks
Males
Females
Dose
Absolute
Relative
Dose
Absolute
Relative
(mg/kg-d)
weight
weight
(mg/kg-d)
weight
weight
0
0
0
0
0
0
350
1
1
500
0
-3
640
3
2
820
-3
-1
1,590
2
8
1,660
1
0
3,940
6
22*
6,430
6
15*
8,210
0
48*
11,620
12*
35*
Males
Females
Dose
Absolute
Relative
Dose
Absolute
Relative
(mg/kg-d)
weight
weight
(mg/kg-d)
weight
weight
0
0
0
0
0
0
90
4
8
180
8*
14*
200
11
15*
330
18*
21*
420
7
20*
650
22*
42*
NTP (1995)
F344/N rat; 60/sex/treatment
(10/sex/treatment evaluated at
15 months)
Drinking water (0,1.25, 2.5, 5, or
10 mg/mL)
M: 0, 90, 200, or 420a mg/kg-d
F: 0,180, 330, or 650a mg/kg-d
2 years
Only rats sacrificed at 15 months were evaluated for organ weights.
Males
Females
Concentration
Absolute
Relative
Absolute
Relative
(mg/m3)
weight
weight
weight
weight
0
0
0
0
0
406
1
1
-4
-1
824
-2
-1
0
1
1,643
3
2
4
4
3,273
11*
8*
2
2
6,368
9.8*
9*
4
9*
NTP (1997)
F344/N rat; 10/sex/treatment
Inhalation analytical
concentration: 0,134, 272, 542,
1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3)
(dynamic whole-body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist
Ultrasonic spray nozzle
nebulizer), analytical
concentration and method were
reported
Right kidney weights measured
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Reference and study design
Results
NTP (1997)
B6C3Fi mouse; 10/sex/treatment
Inhalation analytical
concentration: 0,134, 272, 542,
1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3)
(dynamic whole-body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist
Ultrasonic spray nozzle
nebulizer), analytical
concentration and method were
reported
Right kidney weights measured
Males
Females
Concentration
Absolute
Relative
Absolute
Relative
(mg/m3)
weight
weight
weight
weight
0
0
0
0
0
406
-6
-4
1
-3
824
-1
3
5
9
1,643
4
3
1
-2
3,273
-10
-3
0
7
6,368
3
6
3
15*
1
2 aThe high-dose group had an increase in mortality.
3 * Statistically significant p < 0.05 as determined by the study authors.
4 Percentage change compared to control = (treated value - control value) -f control value x 100.
5 Conversions from drinking water concentrations to mg/kg-d performed by study authors.
6 Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3.
7
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Table B-2. Changes in liver weight in animals following exposure to
tert- butanol
Reference and study design
Results
Acharva et al. (1995)
No significant treatment-related effects (results were only provided in a figure)
Wistar rat; 5-6 males/treatment
Drinking water (0 or 0.5%), 0 or
575 mg/kg-d
10 weeks
Lvondell Chemical Co. (2004)
Percent change compared to control
Sprague-Dawley rat; 12/sex/treatment
Gavage 0, 64,160, 400, or 1,000 mg/kg-d
Males
Females
Males: 9 weeks beginning 4 weeks prior to
Dose
Absolute
Relative
Dose
Absolute
mating
(mg/kg-d)
weight
weight
(mg/kg-d)
weight
Relative weight
Females: 4 weeks prior to mating through
PND21
0
-
-
0
-
-
64
-1
0
64
-4
-4
160
-3
1
160
-7
-5
400
-2
-1
400
2
1
1,000
8
16*
1,000
8
3
NTP (1995)
Percent change compared to control
F344/N rat; 10/sex/treatment
Males
Females
Drinking water (0, 2.5, 5,10, 20, or
40 mg/mL)
Dose
Absolute
Relative
Dose
Absolute
Relative
M: 0, 230, 490, 840, 1,520, 3,610a mg/kg-d
(mg/kg-d)
weight
weight
(mg/kg-d)
weight
weight
F: 0, 290, 590, 850,1,560, 3,620a mg/kg-d
13 weeks
0
-
-
0
-
-
230
-2
4
290
11*
9*
490
1
8*
590
10*
9*
840
5
20*
850
12*
ii*
1,520
8
31*
1,560
15*
16*
3,610
All dead
All dead
3,620
9*
41*
NTP (1995)
Percent change compared to control
B6C3Fi mouse; 10/sex/treatment
Males
Females
Drinking water (0, 2.5, 5,10, 20, or
40 mg/mL)
Dose
Absolute
Relative
Dose
Absolute
Relative
M: 0, 350, 640, 1,590, 3,940,
(mg/kg-d)
weight
weight
(mg/kg-d)
weight
weight
8,210a mg/kg-d
F: 0, 500, 820,1,660, 6,430,
0
-
-
0
-
-
ll,620a mg/kg-d
350
2
3
500
-1
-4
13 weeks
640
-1
-2
820
-5
-3
1,590
-1
5
1,660
-8
3,940
0
14*
6,430
-2
6
8,210
-16
22*
11,620
-6
13*
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
NTP (1995)
F344/N rat; 60/sex/treatment
(10/sex/treatment evaluated at 15 months)
Drinking water (0,1.25, 2.5, 5 or 10 mg/mL)
M: 0, 90, 200, or 420a mg/kg-d
F: 0,180, 330, or 650a mg/kg-d
2 years
Percent change compared to control:
Males Females
Dose Absolute Relative Dose Absolute Relative
(mg/kg-d) weight weight (mg/kg-d) weight weight
0 0
90 2 7 180 -14* -8
200 8 11 330 -3 -1
420 1 14* 650 -6 9*
Only animals sacrificed at 15 months were evaluated for organ weights. Organ
weights were not measured in the 2-year mouse study
NTP (1997)
F344/N rat; 10/sex/treatment
Inhalation analytical concentration: 0,134,
272, 542,1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3) (dynamic
whole body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist Ultrasonic
spray nozzle nebulizer), analytical
concentration and method were reported
Percent change compared to control:
Males Females
Concentration Absolute Relative Absolute Relative
(mg/m3) weight weight weight weight
0 ....
406 -8 -8 0 3
824 -2 -1 0 0
1,643 1 -1 3 2
3,273 10 7 9 9*
6,368 5 5 4 8*
NTP (1997)
B6C3Fi mouse; 10/sex/treatment
Inhalation analytical concentration: 0,134,
272, 542,1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3) (dynamic
whole body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist Ultrasonic
spray nozzle nebulizer), analytical
concentration and method were reported
Percent change compared to control:
Males Females
Concentration Absolute Relative Absolute Relative
(mg/m3) weight weight weight weight
0 ....
406 -1 0 1 -4
824 4 9 1 5
1,643 7 5 5 1
3,273 -8 -2 2 9*
6,368 5 7 8 21*
aThe high-dose group had an increase in mortality.
* Statistically significant p < 0.05 as determined by study authors.
Conversions from drinking water concentrations to mg/kg-d performed by study authors.
Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3.
Percentage change compared to control = (treated value - control value) 4- control value x 100.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Table B-3. Changes in liver histopathology in animals following exposure to
tert- butanol
Reference and study design
Results
Acharva et al. (1997)
Acharva et al. (1995)
Wistar rat; 5-6 males/treatment
Drinking water (0, 0.5%), 0, 575 mg/kg-d
10 weeks
'T* liver glycogen (~ 7 fold)*
^incidence of centrilobular necrosis, vacuolation of hepatocytes, loss of
hepatocyte architecture, peripheral proliferation, and lymphocyte
infiltration (incidences and results of statistical tests not reported)
NTP (1995)
F344/N rat; 10/sex/treatment
Drinking water (0, 2.5, 5,10, 20, or 40 mg/mL)
M: 0, 230, 490, 840,1,520, 3,610a mg/kg-d
F: 0, 290, 590, 850, 1,560, 3,620a mg/kg-d
13 weeks
No treatment-related effects observed.
NTP (1995)
B6C3Fi mouse; 10/sex/treatment
Drinking water (0, 2.5, 5,10, 20, 40 mg/mL)
M: 0, 350, 640, 1,590, 3,940, 8,210a mg/kg-d
F: 0, 500, 820, 1,660, 6,430, ll,620a mg/kg-d
13 weeks
No treatment-related effects observed.
NTP (1995)
F344/N rat; 60/sex/treatment
(10/sex/treatment evaluated at 15 months)
Drinking water (0,1.25, 2.5, 5,10 mg/mL)
M: 0, 90, 200, or 420a mg/kg-d
F: 0,180, 330, or 650a mg/kg-d
2 years
No treatment-related effects observed.
NTP (1995)
B6C3Fi mouse; 60/sex/treatment
Drinking water (0, 5,10, 20 mg/mL)
M: 0, 540,1,040, or 2,070a mg/kg-d
F: 0, 510,1,020, or 2,110 mg/kg-d
2 years
Males
Dose
(mg/kg-d)
0
540
1,040
2,070
Incidence of fatty
change
12/59
5/60
8/59
29/59*
Females
Dose
(mg/kg-d)
0
510
1,020
2,110
Incidence of fatty
change
11/60
8/60
8/60
6/60
NTP (1997)
F344/N rat; 10/sex/treatment
Inhalation analytical concentration: 0,134,
272, 542, 1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3) (dynamic whole
body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist Ultrasonic spray
nozzle nebulizer), analytical concentration and
method were reported
No treatment-related effects observed in the high dose group (only
treatment group with liver endpoints evaluated).
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Reference and study design
Results
NTP (1997)
B6C3Fi mouse; 10/sex/treatment
Inhalation analytical concentration: 0,134,
272, 542, 1,080, or 2,101 ppm (0, 406, 824,
1,643, 3,273 or 6,368 mg/m3) (dynamic whole
body chamber)
6 hr/d, 5 d/wk
13 weeks
Generation method (Sonimist Ultrasonic spray
nozzle nebulizer), analytical concentration and
method were reported
Authors stated that there were no treatment-related microscopic changes,
but data were not provided.
aThe high-dose group had an increase in mortality.
* Statistically significant p < 0.05 as determined by study authors.
Conversions from drinking water concentrations to mg/kg-d performed by study authors.
Conversion from ppm to mg/m3 is 1 ppm = 3.031 mg/m3.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table B-4. Changes in urinary bladder histopathology in animals following
2 oral exposure to tert-butanol
Reference and study design
Results
NTP (1995)
Incidence (severity):
F344/N rat; 10/sex/treatment
Drinking water (0, 2.5, 5,10, 20,
Males
Females
40 mg/mL)
Transitional
M: 0, 230, 490, 840, 1,520,
Dose epithelial
Dose
Transitional epithelial
3,610a mg/kg-d
(mg/kg-d) hyperplasia
(mg/kg-d)
hyperplasia
F: 0, 290, 590, 850, 1,560,
3,620a mg/kg-d
0 0/10
0
0/10
13 weeks
230 not evaluated
290
not evaluated
490 not evaluated
590
not evaluated
840 0/10
850
not evaluated
1,520 1/10 (3.0)
1,560
0/10
3,610 7/10* (2.9)
3,620
3/10 (2.0)
Severity: 1 = minimal, 2 = mild, 3 = moderate, 4
= marked
NTP (1995)
Incidence (severity):
B6C3Fi mouse; 10/sex/treatment
Drinking water (0, 2.5, 5,10, 20,
Males
Females
40 mg/mL)
Transitional
Transitional
M: 0, 350, 640, 1,590, 3,940,
Dose epithelial Inflam-
Dose
epithelial Inflam-
8,210a mg/kg-d
(mg/kg-d) hyperplasia mation (mg/kg-d)
hyperplasia mation
F: 0, 500, 820, 1,660, 6,430,
ll,620a mg/kg-d
0 0/10 0/10
0
0/10 0/10
13 weeks
350 not evaluated
500
0/10 0/10
640 not evaluated
820
not evaluated
1,590 0/10 0/10
1,660
not evaluated
3,940 6/10* (1.3) 6/10* (1.3)
6,430
0/10 0/10
8,210 10/10* (2.0) 10/10*
11,620
3/9(2.0) 6/9* (1.2)
(2.3)
Severity: 1 = minimal, 2 = mild, 3 = moderate, 4
= marked
NTP (1995)
No treatment-related effects observed
F344/N rat; 60/sex/treatment
(10/sex/treatment evaluated at
15 months)
Drinking water (0,1.25, 2.5, 5, or
10 mg/mL)
M: 0, 90, 200, 420a mg/kg-d
F: 0,180, 330, 650a mg/kg-d
2 years
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Supplemental Information—tert-Butyl Alcohol
Reference and study design
Results
NTP (1995)
Incidence (severity):
B6C3Fi mouse; 60/sex/treatment
Drinking water (0, 5,10, or
Males
Females
20 mg/mL)
Transitional
Transitional
M: 0, 540,1,040, 2,070a mg/kg-d
Dose
epithelial
Inflam-
Dose
epithelial
Inflam-
F: 0, 510,1,020, 2,110 mg/kg-d
(mg/kg-d)
hvoerolasia
mation
(mg/kg-d)
hvoerolasia
mation
2 years
0
1/59 (2.0)
0/59
0
0/59
0/59
540
3/59(1.7)
3/59 (1.7)
510
0/60
0/60
1,040
1/58(1.0)
1/58 (1.0)
1,020
0/59
0/59
2,070
17/59*
(1.8)
37/59* (2.0)
2,110
3/57 (1.0)
4/57*
(2.0)
Severity: 1 =
minimal, 2 = mild, 3 = moderate, 4
= marked
1
2 aThe high-dose group had an increase in mortality.
3 * Statistically significant p < 0.05 as determined by study authors.
4 Conversions from drinking water concentrations to mg/kg-d performed by study authors.
This document is a draft for review purposes only and does not constitute Agency policy.
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¦ = exposures at which the endpoint was reported statistically significant by study authors
~ = exposures at which the endpoint was reported not statistically significant by study authors
x = exposures at which all animals died and were unable to be examined for the endpoint
URINARY Transitional epithelium hyperplasia; M rat(C)
BLADDER
EFFECTS
Transitional epithelium hyperplasia; F rat(C)
Subchronic
Transitional epithelium hyperplasia; M mouse (C)
Inflammation; M mouse (C)
Inflammation; F mouse (C)
Transitional epithelium hyperplasia; F mouse (C)
Transitional epithelium hyperplasia; M mouse (C)
Inflammation; M mouse (C)
Chronic Inflammation; Fmouse (C)
Transitional epithelium hyperplasia; F mouse (C)
B-B-
~—0
~ ¦
-B-B
B—B
B—B
LIVER
EFFECTS
Subchronic
Chronic
Reproductive
Increased glycogen; M rat(A)
Relative weight; M rat (A)
Relative weight; M rat(C)
Absolute weight; F rat(C)
Relative weight; F rat(C)
Absolute weight; M rat(C)
Relative weight M mouse (C)
Relative weight; F mouse (C)
Absolute weight; M mouse (C)
Absolute weight; F mouse (C)
Relative weight M rat(C)
Relative weight F rat(C)
Absolute weight; M rat(C)
Absolute weight; F rat(C)
Fatty tissue; M mouse (C)
Fatty tissue; F mouse (D)
Relative weight; M rat(B)
Absolute weight; M rat(B)
Absolute weight F rat(B)
Relative weight F rat(B)
~ ~ ~
B-B-
-B B
B~B
B-B-
-B—B
B-B—B-
-B-B
B—B-
¦ B B
B—B—B
B-B—B
B—B-
B—B—B
10
100
1,000
10,000
100,000
Dose (mg/kg-day)
Sources: (A) Acharva et al. (1997); Acharva et al. (19951; (B) Lvondell Chemical Co. (2004); (C) NTP (1995)
Figure B-3. Exposure-response array of other effects following oral exposure
to tert-butanol.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
¦ = exposures at which the endpoint was reported statistically significant by study authors
~ = exposures at which the endpoint was reported not statistically significant by study authors
LIVER EFFECTS
Absolute liver weight; M rat (A)
Relative liver weight; M rat (A)
Absolute liver weight; F rat (A)
Relative liver weight; F rat (A)
Absolute liver weight; M mouse (A)
Relative liver weight; M mouse (A)
Absolute liver weight; F mouse (A)
Relative liver weight; F mouse (A)
Liver histopathology; M rat (A)
Liver histopathology; Frat(A)
Liver histopathology; M mouse (A)
Liver histopathology; F mouse (A)
100 1,000 10,000
Concentration (mg/m;!)
Source: (A) NTP (1997)
Figure B-4. Exposure-response array of other effects following inhalation
exposure to tert-butanol.
This document is a draft for review purposes only and does not constitute Agency policy.
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~ B B B B
~ B B B B
~ B B ¦ ¦
B B B B B
B B B B B
B B B B B
B B B ¦ ¦
B B B B B
B B B B B
B B B B B
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B.2.2. 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 induction, and deoxyribonucleic acid (DNA)
strand breaks and adducts. The available genotoxicity data for tert-butanol are discussed below,
and the data summary is provided in Table B-5.
B.2.2.1. Bacterial Systems
The mutagenic potential of tert-butanol has been tested by Zeiger etal. f!9871 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 [ig/plate) and tested in triplicate. No mutations were observed in any of the strains tested,
in either the presence or absence of S9 metabolic activation.
Conflicting results have been obtained with tert-butanol-induced mutagenicity in
Salmonella 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 etal. (1999).
tert-butanol induced an increase in the number of revertants in the first three concentrations with
S9 activation in a dose-response manner. The number of revertants decreased in the last two
concentrations. No discussion was provided on why the revertants decreased at higher
concentrations. The results of this study indicated that test strain TA102 might be a more sensitive
strain for monitoring tert- butanol levels fWilliams-Hill etal.. 19991. In another study by Mcgregor
etal. (20051. however, experiments were conducted on TA102 at two different laboratories using
similar protocols, tert-Butanol was dissolved in dimethyl sulfoxide (DMSO) or distilled water and
tested in both the presence and absence of S9 metabolic activation. No statistically significant
increase in mutants was observed in either solvent medium.
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 etal.. 1949). tert- Butanol without exogenous metabolic activation, however, significantly
increased the frequency of petite mutations (the mitochondrial DNA deletion rho-) in
Saccharomyces cerevisiae laboratory strains K5-A5, MMY1, D517-4B, and DS8 (Timenez 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 flimenez etal..
1988).
This document is a draft for review purposes only and does not constitute Agency policy.
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B.2.2.2. In Vitro Mammalian Studies
To understand the role of tert-butanol-induced ge no toxicity 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 in both
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 x 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
(1.7-fold) increase in mutant fraction at the highest tested concentration (5,000 [ig/mL) (McGregor
etal.. 19881.
To further determine potential DNA or chromosomal damage induced by tert-butanol in in
vitro systems, NTP (19951 studied sister chromatid exchanges and chromosomal aberrations.
Chinese hamster ovary (CHO) cells were exposed to tert-butanol in both the presence and absence
of S9 activation at concentrations of 160-5,000 |J.g/mL for 26 hours, tert-Butanol did not induce
sister chromatid exchanges at any concentration tested, although in one experiment, percent
relative change of sister chromatid exchanges per chromosome scored slightly increased. The same
authors also studied the effect of tert-butanol on chromosomal aberration formation. CHO cells
were exposed to four concentrations (160, 500,1,600, or 5,000 [ig/mL) of tert-butanol in both the
presence and absence of S9. No significant increase in chromosomal aberration was observed at
any concentration tested. Of note is that, due to severe toxicity at the highest concentration
(5,000 [ig/mL), only 13 metaphase cells were scored instead of 100 in the chromosomal aberration
assay.
Sgambato etal. f20091 examined the effects of tert- butanol on DNA damage using a 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 then was 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 also were 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 as measured by
the number of cells after 24 and 48 hours of exposure at IC50 concentrations and with
concentrations at l/10th the IC50. Cell death did not increase, suggesting a reduction in cell number
due to reduced replication rather than to cytotoxicity, tert-Butanol caused an accumulation in the
G0/G1 phase of replication, related to different effects on the expression of the cyclin Dl, p27Kipl,
and p53 genes. An initial increase in DNA damage as measured by nuclear fragmentation was
observed at 30 minutes. 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
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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 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 etal.. 19971.
B.2.2.3. In Vivo Mammalian Studies
Few 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 fNTP.
1995). Peripheral blood samples were obtained from male and female B6CF1 mice 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 induction in peripheral blood lymphocytes was observed either in male or female
B6C3Fi mice exposed for 13 weeks to tert-butanol in drinking water at concentrations as high as
40,000 ppm (2,110 mg/kg-day) fNTP. 1997.19951. Furthermore, no induction of micronuclei in
polychromatic erythrocytes was observed in bone marrow cells of male rats receiving
intraperitoneal injections (NTP. 1997).
Male Kunming mice (8 per treatment) were administered 0, 0.099, 0.99,10,101, or
997 |ig/kg BW 14C-tert-butanol in saline via gavage with specific activity ranging from 1.60 to
0.00978 mCi/mol (Yuan etal.. 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 could 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 tert-
butanol-induced DNA adducts.
This document is a draft for review purposes only and does not constitute Agency policy.
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Table B-5. Summary of genotoxicity (both in vitro and in vivo) studies of tert-
butanol
Test system
Dose/ Cone.
Results3
Comments
Reference
Bacterial Systems
-S9
+S9
Reverse Mutation Assay
Salmonella typhimurium
(TA98, TA100, TA1535,
TA1537, TA1538)
100, 333, 1,000,
3333,
10,000 ng/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 ng/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, 1,000,
1,500, 2,500,
5,000 ng/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
L5178YTK+/"
625, 1,000, 1,250,
2,000, 3,000,
4,000, 5,000 |Jg/m L
Cultures were exposed for 4 h,
then cultured for 2 days before
plating in soft agar with or
without trifluorothymidine,
3 |Jg/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, 1,600,
2,000, 3,000,
4,000, 5,000 |Jg/m L
-
-
This study was part of the NTP
1995 testing results
Gallowav et al.
(1987); NTP
(1995)
Chromosomal Aberrations,
Chinese Hamster Ovary cells
160, 500, 1,600,
2,000, 3,000,
4,000, 5,000 |Jg/m L
This study was part of the NTP
1995 testing results
Gallowav et al.
(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/ Cone.
Results3
Comments
Reference
DNA damage, (comet
assay), HL-60 leukemia cells
1, 5,10, 30 mmol/L
+ ND
Exposure duration - lh
Tang et al.
(1997)
In vivo Animal Studies
Micronucleus induction,
B6C3F1 mouse peripheral
blood cells
3,000, 5,000,
10,000, 20,000,
40,000 ppm
13-week, subchronic, drinking
water study
NTP (1995)
Micronucleus induction,
male rats, bone marrow
cells
39, 78, 156, 312,
625, 1250
i.p injections - 3 times at 24 h
intervals
NTP (1997)
DNA adducts, male
Kunming mouse liver,
kidney, and lung cells
0.1-1,000 ng/kg
body weight
+
Gavage, 6-h exposure, DNA
adduct determined by
accelerator mass spectrometry
Yuan et al.
(2007)
a+ = positive; - = negative; ND = not determined.
bEffect is predicted to be due to mitochondrial membrane composition.
CDNA damage was completely reversed with increased exposure time.
B.2.3. Summary
tert-Butanol has been tested for its genotoxic potential using a variety of genotoxicity
assays. In general, a positive result in the Ames assay is 73-77% predictive of a positive result in the
rodent carcinogenicity assay fKirkland etal.. 20051. 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 could influence 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 twice 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 due to exposure to tert-butanol.
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 exchanges or chromosomal aberrations were not observed in CHO cells in
response to tert-butanol treatment. DNA damage was detected using a comet assay, however, in
both rat fibroblasts and 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
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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 efficient DNA repair
mechanism activated by cells following DNA damage induced by tert-butanol. A dose-dependent
increase in DNA damage was observed in human cells tested; however, because the exposure
occurred for only 1 hour in this study, whether DNA-repair mechanisms would occur after a longer
period of observation cannot be discerned.
Limited in vivo animal studies have been conducted on DNA adduct formation and
micronucleus induction. 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
the identity of these adducts was not determined. The method uses 14C-labeled chemical for dosing,
isolated DNA is oxidized to carbon dioxide and reduced to filamentous graphite, and the ratios of
14C/12C are measured. The ratio then is converted to DNA adducts based on nucleotide content of
the DNA. Confirmation of these data will further the understanding of the mechanism of
tert-butanol-induced DNA adducts. No increase in micronucleus induction was observed in mouse
peripheral blood cells in a 13-week drinking water study conducted by the National Toxicology
Program.
Overall, a limited evidence base is available for understanding the role of tert-butanol-
induced genotoxicity for mode of action and carcinogenicity. The evidence base is limited in terms
of either 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 could influence results. Furthermore,
in some studies, the specificity of the methodology used has been challenged. Given the
inconsistencies and limitations of the evidence base in terms of the methodology used, number of
studies in the overall evidence base, 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 genotoxicity of tert-butanol and thus the potential genotoxic
effects of tert-butanol cannot be discounted.
This document is a draft for review purposes only and does not constitute Agency policy.
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APPENDIX C. DOSE-RESPONSE MODELING FOR
THE DERIVATION OF REFERENCE VALUES FOR
EFFECTS OTHER THAN CANCER AND THE
DERIVATION OF CANCER RISK ESTIMATES
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 noncancer and cancer
sections below describe 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, using alternative methods based on statistical judgment
might be appropriate; exceptions are noted as necessary in the summary of the modeling results.
C.l.l. Noncancer Endpoints
C.1.1.1. Data Sets
Data sets selected for dose-response modeling are provided in Table C-l. In all cases,
administered exposure was used in modeling the response data.
C.l.l.2. Model Fit
All models were fit to the data using the maximum likelihood method. The following
procedures were used, depending on whether data were dichotomous or continuous.
• For dichotomous models, the following parameter restrictions were applied: for log-logistic
model, restrict slope >1; for gamma and Weibull models, restrict power >1; and for
multistage models, restrict beta values >0. Each model was tested for goodness-of-fit using
a chi-square goodness-of-fit test (x2 p-value < 0.10 indicates lack of fit). Other factors also
were 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 continuous models, the following parameter restrictions were applied: for polynomial
models, restrict beta values >0; and for Hill, power, and exponential models, restrict power
>1. 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
(X2 p-value > 0.10), the model was fit to the data assuming constant variance. If Test 2 was
rejected (x2 p-value < 0.10), the variance was modeled as a power function of the mean, and
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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 x2 p-value < 0.10 indicating inadequate fit). Other factors also were 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.l.1.3. 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
used to select a best-fit model among the models exhibiting adequate fit. If the BMDL estimates
were "sufficiently close," that is, differed by no more than three-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-l. Noncancer 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
Increased absolute
kidney weight
NTP (1995)
Rat (F344)/Male
Dose (mg/kg-d)
0
90
200
420
Mean ± SD (n)
1.78 ±0.18
(10)
1.85 ±0.17
(10)
1.99 ±0.18
(10)
1.9 ±0.23
(10)
Increased absolute
kidney weight
NTP (1995)
Rat
(F344)/Female
Dose (mg/kg-d)
0
180
330
650
Mean ± SD (n)
1.07 ± 0.09
(10)
1.16 ±0.10
(10)
1.27 ±0.08
(10)
1.31 ±0.09
(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
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 absolute
kidney weight
Rat
(F344)/Female
Concentration
(mg/m3)
0
406
825
1643
3274
6369
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Endpoint/Study
Species/
Sex
Doses and effect data
NTP (1997)
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)
1 C.1.1.4. Modeling Results
2 Below are tables summarizing the modeling results for the noncancer endpoints modeled.
3 Table C-2. Summary of BMD modeling results for kidney transitional epithelial
4 hyperplasia in male F344 rats exposed to tert-butanol in drinking water for 2
5 years (NTP. 1995): BMR = 10% extra risk
Model3
Goodness of fit
BMDio
(mg/kg-d)
BMDLio
(mg/kg-d)
Basis for model selection
p-value
AIC
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
6 aScaled residuals for selected model for doses 0, 90, 200, and 420 mg/kg-d were -0.076, 0.147,0.046, and -0.137,
7 respectively.
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Log-Logistic Model with 0.95 Confidence Level
dose
17:16 05/13 2011
Figure C-l. Plot of incidence by dose, with fitted curve for LogLogistic model
for kidney transitional epithelial hyperplasia in male F344 rats exposed to
tert-butanol in drinking water for 2 years (NTP. 1995): BMR = 10% extra risk;
dose shown in mg/kg-d.
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_l0.(d)
Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\17 NTP
1995b_Kidney transitional epithelial hyperplasia, male rats_LogLogistic_l0.pit
_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: le-008
Parameter Convergence has been set to: le-008
User has chosen the log transformed model
Default Initial Parameter Values
background = 0.5
intercept = -5.54788
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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
AIC: 248.04
Goodness of Fit
Scaled
Dose Est. Prob. Expected Observed Size Residual
0.0000
0.5054
90.0000 0.6300
200.0000 0.7171
420.0000 0.8076
25. 2i
31.498
35.854
40.382
25.000
32.000
36.000
40.000
50
50
50
50
-0.076
0.147
0. 046
-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 = 2 9.6967
BMDL = 15.6252
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-3. Summary of BMD modeling results for kidney transitional epithelial
2 hyperplasia in female F344 rats exposed to tert-butanol in drinking water for
3 2 years (NTP. 1995): BMR = 10% extra risk
Goodness of fit
Model3
p-value
AIC
BMDio
(mg/kg-d)
BMDLio
(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
Logistic
0.50
92.81
461
393
LogLogistic
0.79
91.57
414
333
differed by less than 3-fold).
LogProbit
0.89
91.19
400
327
Multistage 3°
0.92
89.73
412
339
Probit
0.62
92.20
439
372
Weibull
0.76
91.67
421
337
Dichotomous-Hill
N/Ab
117.89
Errorc
Error0
aScaled residuals for selected model for doses 0,180, 330, and 650 mg/m3 were 0.0, -0.664, 0.230, and 0.016,
respectively.
bNo available degrees of freedom to estimate a p-value.
CBMD and BMDL computation failed for the Dichotomous-Hill model.
Multistage Model with 0.95 Confidence Level
4 17:18 05/13 201 1
5 Figure C-2. Plot of incidence by dose, with fitted curve for Multistage 3° model
6 for kidney transitional epithelial hyperplasia in female F344 rats exposed to
7 tert-butanol in drinking water for 2 years (NTP. 1995): BMR = 10% extra risk;
8 dose shown in mg/kg-d.
9 ====================================================================
10 Multistage Model. (Version: 3.2; Date: 05/26/2010)
This document is a draft for review purposes only and does not constitute Agency policy.
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Input Data File: M:\NCEA t6/"t-butanol\BMD modeling\BMDS Output\20 NTP
1995b Kidney transitional epithelial hyperplasia, female rats Multi3 10.(d)
Gnuplot Plotting File: M:\NCEA t6rt_butanol\BMD modeling\BMDS Output\20 NTP
1995b Kidney transitional epithelial hyperplasia, female rats Multi3 10.pit
Mon May 09 18:31:33 2011
[notes]
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose/Nl-beta2*dose/N2-beta3*dose/N3) ]
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: le-008
Parameter Convergence has been set to: le-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
( *** The model parameter(s) -Background -Beta(l) -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
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Fitted model
Reduced model
-43.8652
-65.0166
1 0.9301 3 0.8182
1 43.2329 3 <.0001
89.7304
Dose
Goodness of Fit
Scaled
Est. Prob. Expected Observed
Residual
0.0000 0.0000
180.0000 0.0088
330.0000 0.0527
650.0000 0.3389
0.000 0.000
0.438 0.000
2.636 3.000
16.946 17.000
50
50
50
50
0. 000
-0.664
0.230
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 = 4 6 9.73
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.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-4. Summary of BMD modeling results for absolute kidney weight in
2 male F344 rats exposed to tert-butanol in drinking water for 15 months (NTP.
3 1995): BMR = 10% rel. dev. from control mean
Model3
Goodness of fit
BMDiord
(mg/kg-d)
BMDLiord
(mg/kg-d)
Basis for model selection
p-value
AIC
Exponential (M2)b
0.123
-86.757
661
307
Of the models that provided an
adequate fit and a valid BMDL
estimate, the linear model was
selected based on lowest AIC.
Exponential (M3)c
0.123
-86.757
661
307
Exponential (M4)
0.167
-87.041
errord
0
Exponential (M5)
N/Ae
-85.880
errord
0
Hill
0.301
-87.880
errord
errord
Power'
Polynomial 3°B
Polynomial 2°h
Linear
0.126
-86.804
657
296
aConstant variance case presented (BMDS Test 2 p-value = 0.777), selected model in bold; scaled residuals for
selected model for doses 0, 90, 200, and 420 mg/kg-d were -0.78, -0.11,1.65, -0.76, respectively.
bThe Exponential (M2) model can appear equivalent to the Exponential (M3) model, however differences exist in
digits not displayed in the table.
cThe Exponential (M3) model can appear equivalent to the Exponential (M2) model, however differences exist in
digits not displayed in the table.
dBMD or BMDL computation failed for this model.
eNo available degrees of freedom to calculate a goodness-of-fit value.
fFor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model.
gFor the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates
were 0 (boundary of parameters space). The models in this row reduced to the Linear model.
hFor the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Linear model.
This document is a draft for review purposes only and does not constitute Agency policy.
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Linear Model, with BMR of 0.1 Rel. Dev. for the BMD and 0.95 Lower Confidence Limit for the BMDL
dose
11:46 05/26 2015
Figure C-3. Plot of mean response by dose, with fitted curve for Linear model
with constant variance for absolute kidney weight in male F344 rats exposed
to tert-butanol in drinking water for 15 months fNTP. 19951: BMR = 10% rel.
dev. from control mean; dose shown in mg/kg-d.
Polynomial Model. (Version: 2.20; Date: 10/22/2014)
The form of the response function is: Y[dose] = beta_0 + beta_l*dose.
A constant variance model is fit
Benchmark Dose Computation.
BMR = 10% Relative deviation
BMD = 656.583
BMDL at the 95% confidence level = 295.826
Parameter Estimates
Variable
Estimate
Default initial
parameter values
alpha
0.0361494
0.0362125
rho
n/a
0
beta_0
1.83173
1.83173
beta_l
0.000278979
0.000278979
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table of Data and Estimated Values of Interest
Dose
N
Obs Mean
Est Mean
Obs Std Dev
Est Std Dev
Scaled Resid
0
10
1.78
1.83
0.18
0.19
-0.777
90
10
1.85
1.86
0.17
0.19
-0.114
200
10
1.99
1.89
0.18
0.19
1.65
420
10
1.9
1.95
0.23
0.19
-0.763
2 Likelihoods of Interest
Model
Log(likelihood)
# Pa ram's
AIC
A1
48.474229
5
-86.948457
A2
49.025188
8
-82.050377
A3
48.474229
5
-86.948457
fitted
46.401914
3
-86.803828
R
45.368971
2
-86.737942
3 Tests of Interest
Test
-2*log( Likelihood
Ratio)
Test df
p-value
Test 1
7.31243
6
0.2929
Test 2
1.10192
3
0.7766
Test 3
1.10192
3
0.7766
Test 4
4.14463
2
0.1259
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-5. Summary of BMD modeling results for absolute kidney weight in
2 female F344 rats exposed to tert-butanol in drinking water for 15 months
3 (NTP. 1995): BMR = 10% rel. dev. from control mean
Model3
Goodness of fit
BMDiord
(mg/kg-d)
BMDLiord
(mg/kg-d)
Basis for model selection
p-value
AIC
Exponential (M2)
Exponential (M3)b
0.0594
-144.00
318
249
The Exponential (M4) model was
selected as the only model with
adequate fit.
Exponential (M4)
0.176
-145.81
164
91.4
Exponential (M5)
N/Ac
-145.65
207
117
Hill
N/Ac
-145.65
202
119
Powerd
Polynomial 3°e
Polynomial 2°f
Linear
0.0842
-144.70
294
224
aConstant variance case presented (BMDS Test 2 p-value = 0.852), selected model in bold; scaled residuals for
selected model for doses 0,180, 330, and 650 mg/kg-d were 0.21, -0.9, 0.94, -0.25, respectively.
bFor the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the
Exponential (M2) model.
cNo available degrees of freedom to calculate a goodness-of-fit value.
dFor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model.
eFor the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates
were 0 (boundary of parameters space). The models in this row reduced to the Linear model.
fFor the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Linear model.
4
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Exponential 4 Model, with BMR of 0.1 Rel. Dev. for the BMD and 0.95 Lower Confidence Limit for the BMDL
2 Figure C-4. Plot of mean response by dose, with fitted curve for Exponential
3 (M4) model with constant variance for absolute kidney weight in female F344
4 rats exposed to tert-butanol in drinking water for 15 months fNTP. 1995):
5 BMR = 10% rel. dev. from control mean; dose shown in mg/kg-d.
6 Exponential Model. (Version: 1.10; Date: 01/12/2015)
7 The form of the response function is: Y[dose] = a * [c-(c-l) * exp(-b * dose)].
8 A constant variance model is fit
9 Benchmark Dose Computation.
10 BMR = 10% Relative deviation
11 BMD = 163.803
12 BMDL at the 95% confidence level = 91.3614
13 Parameter Estimates
Variable
Estimate
Default initial
parameter values
Inalpha
-4.84526
-4.89115
rho
n/a
0
a
1.06808
1.0203
b
0.00258011
0.00282085
c
1.29013
1.35122
d
n/a
1
14
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table of Data and Estimated Values of Interest
Dose
N
Obs Mean
Est Mean
Obs Std Dev
Est Std Dev
Scaled Resid
0
10
1.07
1.07
0.09
0.09
0.2112
180
10
1.16
1.18
0.1
0.09
-0.8984
330
10
1.27
1.25
0.08
0.09
0.9379
650
10
1.31
1.32
0.09
0.09
-0.2507
2 Likelihoods of Interest
Model
Log(likelihood)
# Pa ram's
AIC
A1
77.82307
5
-145.6461
A2
78.21688
8
-140.4338
A3
77.82307
5
-145.6461
R
62.21809
2
-120.4362
4
76.90527
4
-145.8105
3 Tests of Interest
Test
-2*log(Likelihood
Ratio)
Test df
p-value
Test 1
32
6
<0.0001
Test 2
0.7876
3
0.8524
Test 3
0.7876
3
0.8524
Test 6a
1.836
1
0.1755
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-6. Summary of BMD modeling results for kidney inflammation in
2 female rats exposed to tert-butanol in drinking water for 2 years (NTP. 1995):
3 BMR = 10% extra risk
Model3
Goodness of fit
BMDio%
(mg/kg-d)
BMDLio%
(mg/kg-d)
Basis for model selection
p-value
AIC
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
aSelected model in bold; scaled residuals for selected model for doses 0,180, 330, and 650 mg/kg-d were -0.067,
-0.700,1.347, and -0.724, respectively.
bNo available degrees of freedom to estimate a p-value.
LogProbit Model with 0.95 Confidence Level
17:17 05/13 201 1
5
6
7
Figure C-5. Plot of incidence by dose, with fitted curve for LogpPobit model for
kidney inflammation in female rats exposed to tert-butanol in drinking water
for 2 years (NTP. 1995): BMR = 10% extra risk; dose shown in mg/kg-d.
This document is a draft for review purposes only and does not constitute Agency policy.
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Probit Model. (Version: 3.2; Date: 10/28/2009)
Input Data File: M:/NCEA t6rt_butanol/BMD modeling/BMDS Output/19 NTP
1995b Kidney inflammation, female rats LogProbit 10.(d)
Gnuplot Plotting File: M:/NCEA t6rt_butanol/BMD modeling/BMDS Output/19 NTP
1995b Kidney inflammation, female rats LogProbit 10.pit
Fri May 13 17:17:59 2011
[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: le-008
Parameter Convergence has been set to: le-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 ineguality constraint and thus
has no standard error.
Analysis of Deviance Table
This document is a draft for review purposes only and does not constitute Agency policy.
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Model Log(likelihood) # Param's Deviance Test d.f. P-value
Full model -80.4502 4
Fitted model
Reduced model
-81. 8218
-92.7453
2.7432
24.5902
0.2537
<.0001
AIC:
167.644
Dose
Goodness of Fit
Scaled
Est. Prob. Expected Observed
Residual
0.0000 0.0382
180.0000 0.0880
330.0000 0.1859
650.0000 0.3899
1.909 2.000
4.402 3.000
9.295 13.000
19.495 17.000
50
50
50
50
0. 067
-0.700
1. 347
-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 = 254.34 7
BMDL = 19 9.789
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-7. Summary of BMD modeling results for absolute kidney weight in
2 male F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for 13
3 weeks (NTP. 1997): BMR = 10% relative deviation from the mean
Model3
Goodness of fit
BMCiord
(mg/m3)
BMCLiord
(mg/m3)
Basis for model selection
p-value
AIC
Exponential (M2)
<0.0001
-205.06
errorb
errorb
Although the Hill model was the
only adequately fitting model
(p>0.1), the resulting fit was
essentially a step-function that
does not support interpolation
between the well-fit
observations.
Exponential (M3)
<0.0001
-203.06
9.2E+07
7094
Exponential (M4)
<0.0001
-203.06
errorb
0
Exponential (M5)
<0.0001
-201.06
errorb
0
Hill
0.763
-226.82
1931
1705
Power0
Linear
0.0607
-220.97
5364
3800
Polynomial 5°d
Polynomial 4°e
Polynomial 3°
1.44E-04
-207.06
-9999
errorf
Polynomial 2°
1.44E-04
-207.06
-9999
18436
aConstant variance case presented (BMDS Test 2 p-value = 0.390), selected model in bold; scaled residuals for
selected model for doses 0, 406, 825,1,643, 3,274, and 6,369 mg/m3 were 0.395, 0.374, -0.75, -1.96e-006,
0.381, and -0.381, respectively.
bBMC or BMCL computation failed for this model.
Tor the Power model, the power parameter estimate was 1. The models in this row reduced to the Linear model.
dFor the Polynomial 5° model, the b5 and b4 coefficient estimates were 0 (boundary of parameters space). The
models in this row reduced to the Polynomial 3° model.
eFor the Polynomial 4° model, the b4 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Polynomial 3° model.
fBMC or BMCL computation failed for this model.
This document is a draft for review purposes only and does not constitute Agency policy.
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Hill Model with 0.95 Confidence Level
1 .4
1 .35
1 .3
1 .2
1 .15
1 .1
O 1000 2000 3000 4000 5000 6000
dose
10:15 04/30 2014
Figure C-6. Plot of mean response by concentration, with fitted curve for Hill
model for absolute kidney weight in male F344 rats exposed to tert-butanol
via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP. 1997): BMR = 10%
relative deviation from the mean; concentration shown in mg/m3.
Hill Model. (Version: 2.15; Date: 10/28/2009)
The form of the response function is: Y[dose] = intercept + v*doseAn/(kAn + doseAn).
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
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table of Data and Estimated Values of Interest
Dose
N
Obs Mean
Est Mean
Obs Std Dev
Est Std Dev
Scaled Resid
0
10
1.21
1.2
0.0822
0.0829
0.395
406
9
1.21
1.2
0.096
0.0829
0.374
825
10
1.18
1.2
0.0791
0.0829
-0.75
1643
10
1.25
1.25
0.111
0.0829
-0.00000196
3274
10
1.34
1.33
0.0538
0.0829
0.381
6369
10
1.32
1.33
0.0885
0.0829
-0.381
2 Likelihoods of Interest
Model
Log(likelihood)
# Pa ram's
AIC
A1
117.992549
7
-221.985098
A2
120.600135
12
-217.20027
A3
117.992549
7
-221.985098
fitted
117.41244
4
-226.82488
R
105.528775
2
-207.05755
3 Tests of Interest
Test
-2*log(Likelihood
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.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-8. Summary of BMD modeling results for absolute kidney weight in
2 female F344 rats exposed to tert-butanol via inhalation for 6 hr/d, 5d/wk for
3 13 weeks (NTP. 1997): BMR = 10% relative deviation from the mean
Goodness of fit
BMCiord
(mg/m3)
BMCLiord
(mg/m3)
Model3
p-value
AIC
Basis for model selection
Exponential (M2)
Exponential (M3)b
0.0378
-261.52
14500
7713
No model adequately fit the data.
Exponential (M4)
0.533
-267.48
error0
0
Exponential (M5)
0.374
-265.71
error0
0
Hill
0.227
-265.57
error0
error0
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
aModeled variance case presented (BMDS Test 2 p-value = 1.90E-04, BMDS Test 3 p-value = 0.374), no model was
selected as a best-fitting model.
bFor the Exponential (M3) model, the estimate of d was 1 (boundary). The models in this row reduced to the
Exponential (M2) model.
CBMC or BMCL computation failed for this model.
dFor the Polynomial 3° model, the b3 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Polynomial 2° model. For the Polynomial 3° model, the b3 and b2 coefficient estimates
were 0 (boundary of parameters space). The models in this row reduced to the Linear model.
eFor the Polynomial 2° model, the b2 coefficient estimate was 0 (boundary of parameters space). The models in
this row reduced to the Linear model.
Note: Graphs of the better fitting models are provided for illustration.
4
This document is a draft for review purposes only and does not constitute Agency policy.
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Hill Model
10:32 04/30 2014
Figure C-7. Plot of mean response by concentration, with fitted curve for Hill
model for absolute kidney weight in female F344 rats exposed to tert-butanol
via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP. 1997): BMR = 10%
relative deviation from the mean; concentration shown in mg/m3.
Power Model with 0.95 Confidence Level
10:32 04/30 2014
6000 8000
dose
Figure C-8. Plot of mean response by concentration, with fitted curve for
Power model for absolute kidney weight in female F344 rats exposed to tert-
butanol via inhalation for 6 hr/d, 5d/wk for 13 weeks (NTP. 1997): BMR =
10% relative deviation from the mean; concentration shown in mg/m3.
This document is a draft for review purposes only and does not constitute Agency policy.
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C.1.2. Cancer Endpoints
C.1.2.1. Data Sets
The cancer data sets selected for dose-response modeling are summarized in Table C-9. In
all cases, administered exposure was used in modeling the response data. Due to the significant
difference in survival in the high-dose male mice compared with the concurrent control, the Poly-3
procedure fBailer and Portier. 19881 for adjusting tumor incidence rates for intercurrent mortality
was used. The procedure is based on the observation that the cumulative incidence of tumors tends
to increase with time raised to the second through the fourth powers for a large proportion of
cases. In the Poly-3 procedure, for a study of T weeks' duration, an animal that is removed from the
study after t weeks (t < T) without a specified type of tumor of interest is given a weight of (t/T)3.
An animal that survives until the terminal sacrifice at T weeks is assigned a weight of (T/T)3 = 1. An
animal that develops the specific type of tumor of interest obviously lived long enough to develop
the tumor, and is assigned a weight of 1. The Poly-3 tumor incidence, adjusted for intercurrent
mortality up to time T, is the number of animals in a dose group with the specified type of tumor
divided by the sum of the weights (the effective number of animals at risk). The tumor incidences,
adjusted using this procedure, also are provided in Table C-9.
C.1.2.2 .Model Fit
The multistage model was fit to the cancer data sets. Model coefficients were restricted to
be non-negative (beta values > 0) to estimate a monotonically increasing function. Each model was
fit to the data using the maximum likelihood method, and was tested for goodness of fit using a chi-
square goodness-of-fit test (x2 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 For the NTP f!9951 and Hard etal. f20111 data, models
were run with all doses included, as well as with 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.
*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.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-9. Cancer endpoints selected for dose-response modeling for tert-
2 butanol
Endpoint/Study
Species/Sex
Doses and effect data
Thyroid
Thyroid follicular cell
adenoma
NTP (1995)
B6C3Fi
mice/female
Dose (mg/kg-d)
0
510
1,020
2,110
Incidence/Total
2/58
3/60
2/59
9/59
Thyroid follicular cell
adenoma
NTP (1995)
B6C3Fi
mice/male
Dose (mg/kg-d)
0
540
1,040
2,070
Incidence/Total
1/60
0/59
4/59
2/60
lncidence/Poly-3
adjusted Total
1/50
0/50
4/51
2/35
Kidney3
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
Incidence /Total
8/50
13/50
19/50
13/50
Renal tubule adenoma or
carcinoma
NTP (1995)
Rat (F344) /
Male
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
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
Incidence /Total
4/50
13/50
18/50
12/50
3 aEndpoint presented if kidney tumors are acceptable for quantitation.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 Table C-10. Summary of the oral slope factor derivations
Tumor
Species/Sex
Selected Model
BMR
BMD
(mg/kg-
d)
POD=
BMDL
(mg/kg-d)
BMDLhed3
(mg/kg-d)
Slope factor13
(mg/kg-day)1
Thyroid
Thyroid follicular cell
adenoma
Female
B6C3F1
mouse
3° Multistage
10%
2002
1437
201
5 x 10"4
Kidneyc
Renal tubule
adenoma or
carcinoma
Male F344
rat; dose as
administered
1° Multistage
(high dose
dropped)
10%
70
42
10.1
1 x 10"2
Renal tubule
adenoma or
carcinoma fHard et
al. (2011) reanalvsisl
Male F344
rat; dose as
administered
1° Multistage
(high dose
dropped)
10%
54
36
8.88
1 x 10"2
2 aHED PODs were calculated using BW3/4scaling (U.S. EPA, 2011).
3 bHuman equivalent slope factor = 0.1/BMDLiohed-
4 Alternative endpoint if kidney tumors are acceptable for quantitation.
5
This document is a draft for review purposes only and does not constitute Agency policy.
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C.1.2.1. Modeling Results
Table C-ll. 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. 19951: BMR = 10% extra risk
Model3
Goodness of fit
BMDio%c
(mg/kg-d)
BMDLio%c
(mg/kg-d)
Basis for model selection
p-value
AICb
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
aSelected (best-fitting) model shown in boldface type.
bAIC = Akaike Information Criterion.
Confidence level = 0.95.
0.3
Multistage Cancer Model with 0.95 Confidence Level
Multistage Cancer
Linear extrapolation
0.25
0.2
0.15
0.1
0.05
15:22 05/13 2011
BMDL
500
1000
dose
1500
BMP
2000
Figure C-9. Plot of incidence by dose, with fitted curve for Multistage 3° model
for thyroid follicular cell adenomas in female B6C3F1 mice exposed to tert-
butanol in drinking water for 2 years (NTP. 1995): BMR = 10% extra risk; dose
shown in mg/kg-d.
Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)
Input Data File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP 1995b_Thyroid
folluclar cell andenoma, female mice MultiCanc3 10.(d)
Gnuplot Plotting File: M:\NCEA t-Butanol\BMD modeling\BMDS Output\29 NTP
1995b Thyroid folluclar cell andenoma, female mice MultiCanc3 10.pit
Fri May 13 15:22:18 2011
This document is a draft for review purposes only and does not constitute Agency policy.
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[notes]
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose/Nl-beta2*dose/N2-beta3*dose/N3) ]
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: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.0347373
Beta(1) = 0
Beta(2) = 0
Beta(3) = 1.36917e-011
Asymptotic Correlation Matrix of Parameter Estimates
( The model parameter(s) -Beta(l) -Beta(2)
have been estimated at a boundary point, or have been specified by the
and do not appear in the correlation matrix )
Background Beta(3)
Background 1 -0.53
Beta(3) -0.53 1
Parameter Estimates
95.0% Wald Confidence Interval
Variable Estimate Std. Err. Lower Conf. Limit Upper Conf.
Limit
Background 0.0361209 * * *
Beta(1) 0 * * *
Beta(2) 0 * * *
Beta(3) 1.31301e-011 * * *
* - 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 -54.8326 2 0.577881 2 0.7491
Reduced model -58.5048 1 7.92235 3 0.04764
AIC: 113.665
This document is a draft for review purposes only and does not constitute Agency policy.
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Goodness of Fit
Scaled
Dose Est. Prob. Expected Observed Size Residual
0.0000 0.0361 2.095 2.000 58 -0.067
510.0000 0.0378 2.268 3.000 60 0.496
1020.0000 0.0495 2.918 2.000 59 -0.551
2110.0000 0.1480 8.730 9.000 59 0.099
Chi/N2 = 0.56 d.f. = 2 P-value = 0.7544
Benchmark Dose Computation
Specified effect = 0.1
Risk Type = Extra risk
Confidence level = 0.95
BMD = 2002.03
BMDL = 14 36.69
BMDU = 3802.47
Taken together, (1436.69, 3802.47) is a 90 % two-sided confidence
interval for the BMD
Multistage Cancer Slope Factor = 6.96043e-005
This document is a draft for review purposes only and does not constitute Agency policy.
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Table C-12. Summary of BMD modeling results for thyroid follicular cell
adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in
drinking water for 2 years (NTP. 1995): BMR = 5% extra risk
Model3
Goodness of fit
BMD57.
(mg/kg-d)
BMDL5%c
(mg/kg-d)
Basis for model selection
p-value
AICb
One, Two,
Three
0.202
61.6
1788
787
Multistage 1° was selected. Only form of
multistage that resulted; fit adequate.
aSelected (best-fitting) model shown in boldface type.
bAIC = Akaike Information Criterion.
Confidence level = 0.95.
Multistage Cancer Model, with BMR of 5% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
dose
11:02 06/05 2015
Figure C-10. Plot of incidence by dose, with fitted curve for Multistage 1°
model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice
exposed to tert-butanol in drinking water for 2 years (NTP. 1995): BMR = 5%
extra risk; dose shown in mg/kg-d.
Multistage Model. (Version: 3.4; Date: 05/02/2014)
Input Data File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid tumors
poly3_Mscl-BMR05.(d)
Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid
tumors poly3_Mscl-BMR05.pit
Fri Jun 05 11:02:14 2015
BMDS Model Run
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose^l)]
This document is a draft for review purposes only and does not constitute Agency policy.
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The parameter betas are restricted to be positive
Dependent variable = Effect
Independent variable = Dose
Total number of observations = 4
Total number of records with missing values = 0
Total number of parameters in model = 2
Total number of specified parameters = 0
Degree of polynomial = 1
Maximum number of iterations = 500
Relative Function Convergence has been set to: le-008
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.0164855
Beta(1) = 2.58163e-005
Asymptotic Correlation Matrix of Parameter Estimates
Background Beta(1)
Background 1 -0.56
Beta(1) -0.56 1
Parameter Estimates
95.0% Wald Confidence Interval
Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit
Background 0.0149284 0.0144833 -0.0134584 0.0433151
Beta(1) 2.86952e-005 1.99013e-005 -1.03105e-005 6.7701e-005
Analysis of Deviance Table
Model Log(likelihood) # Param's Deviance Test d.f. P-value
Full model -26.5891 4
Fitted model -28.808 2 4.43785 2 0.1087
Reduced model -29.8255 1 6.47273 3 0.09074
AIC: 61.616
Goodness of Fit
Scaled
Dose Est. Prob. Expected Observed Size Residual
0.0000
540.0000
1040.0000
2070.0000
0.0149
0.0301
0.0439
0.0717
0.746
1.504
2 . 238
2 . 511
1. 000
0. 000
4 . 000
2 . 000
50.000
50.000
51.000
35.000
0.296
-1.245
1.204
-0.335
Chi ^2
3.20
d.f.
P-value
0.2019
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Confidence level = 0.95
BMD = 1787.52
BMDL = 787.153
BMDU did not converge for BMR = 0.050000
BMDU calculation failed
BMDU = Inf
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Table C-13. Summary of BMD modeling results for thyroid follicular cell
adenomas or carcinomas in male B6C3F1 mice exposed to tert-butanol in
drinking water for 2 years, high dose omitted (NTP. 1995): BMR = 5% extra
risk
Model3
Goodness of fit
BMD5%
BMDL5%c
Basis for model selection
p-value
AIC b
One stage
0.105
46.0
1341
538
Multistage 2° was selected based on lowest AIC.
Two stage
0.174
44.9
1028
644
aSelected (best-fitting) model shown in boldface type.
bAIC = Akaike Information Criterion.
Confidence level = 0.95.
Multistage Cancer Model, with BMR of 5% Extra Risk for the BMD and 0.95 Lower Confidence Limit for the BMDL
dose
11:18 06/05 2015
Figure C-ll. Plot of incidence by dose, with fitted curve for Multistage 2°
model for thyroid follicular cell adenomas or carcinomas in male B6C3F1 mice
exposed to tert-butanol in drinking water for 2 years, high dose omitted (NTP.
1995); BMR = 5% extra risk; dose shown in mg/kg-d.
Multistage Model. (Version: 3.4; Date: 05/02/2014)
Input Data File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid tumors
poly3 -h_Msc2-BMR05.(d)
Gnuplot Plotting File: C:/Users/KHOGAN/BMDS/BMDS260/Data/msc_TBA NTP1995 MMthyroid
tumors poly3 -h_Msc2-BMR05.pit
Fri Jun 05 11:18:05 2015
BMDS Model Run
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
The form of the probability function is:
P[response] = background + (1-background)*[1-EXP(
-betal*dose/Nl-beta2*dose/N2 ) ]
The parameter betas are restricted to be positive
Dependent variable = Effect
Independent variable = Dose
Total number of observations = 3
Total number of records with missing values = 0
Total number of parameters in model = 3
Total number of specified parameters = 0
Degree of polynomial = 2
Maximum number of iterations = 500
Relative Function Convergence has been set to: le-006
Parameter Convergence has been set to: le-008
Default Initial Parameter Values
Background = 0.00347268
Beta(1) = 0
Beta(2) = 6.65923e-008
Asymptotic Correlation Matrix of Parameter Estimates
( *** The model parameter(s) -Beta(l)
have been estimated at a boundary point, or have been specified by the user,
and do not appear in the correlation matrix )
Background Beta(2)
Background 1 -0.34
Beta(2) -0.34 1
Parameter Estimates
95.0% Wald Confidence Interval
Variable Estimate Std. Err. Lower Conf. Limit Upper Conf. Limit
Background 0.011558 0.0114911 -0.010964 0.0340801
Beta(1) 0 NA
Beta(2) 4.84624e-008 3.15009e-008 -1.32781e-008 1.10203e-007
NA - Indicates that this parameter has hit a bound
implied by some ineguality constraint and thus
has no standard error.
Analysis of Deviance Table
Model Log(likelihood) # Param's Deviance Test d.f. P-value
Full model -18.9229 3
Fitted model -20.4481 2 3.05031 1 0.08072
Reduced model -21.9555 1 6.0651 2 0.04819
AIC: 44.8962
Goodness of Fit
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Scaled
Dose Est. Prob. Expected Observed Size Residual
0.0000 0.0116 0.578 1.000 50.000 0.558
540.0000 0.0254 1.271 0.000 50.000 -1.142
1040.0000 0.0620 3.164 4.000 51.000 0.485
Chi ^2 = 1.85 d.f. = 1 P-value = 0.1735
Benchmark Dose Computation
Specified effect = 0.05
Risk Type = Extra risk
Confidence level = 0.95
BMD = 1028.79
BMDL = 64 4.475
BMDU did not converge for BMR = 0.050000
BMDU calculation failed
BMDU = 14661.6
Cancer Slope Factor = 7.75825e-005
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
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
fNTP. 19951: BMR = 10% extra risk
Model3
Goodness of fit
BMDiopct (mg/kg-d)
BMDLiopct (mg/kg-
d)
Basis for model
selection
P-
value
Scaled residuals
AIC
Three
Two
0.0806
-0.989, 0.288,1.719,
and -1.010
233.94
294
118
Multistage 2° is
selected as the most
parsimonious model
of adequate fit.
One
0.0806
-0.989, 0.288, 1.719,
and -1.010
233.94
294
errorb
aSelected model in bold.
bBMD or BMDL computation failed for this model.
Multistage Cancer Model with 0.95 Confidence Level
10:57 04/30 2014
Figure C-12. Plot of incidence by dose, with fitted curve for Multistage 2°
model for renal tubule adenoma or carcinoma in male F344 rats exposed to
tert-butanol in drinking water for 2 years modeled with administered dose
units and including all dose groups (NTP. 1995): BMR = 10% extra risk; dose
shown in mg/kg-d.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)
The form of the probability function is: P[response] = background + (l-background)*[l-EXP(-
betal*doseAl-beta2*doseA2...)]
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 atthe 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(l)
0.000358397
0.000268894
Beta(2)
0
0
Analysis of Deviance Table
Model
Log(likelihood)
# Pa ram'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
ChiA2 = 5.04 d.f = 2 P-value = 0.0806
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
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
fNTP. 19951: BMR = 10% extra risk.
Model3
Goodness of fit
BMDiopct (mg/kg-d)
BMDLioPct
(mg/kg-d)
Basis for model
selection
P-
value
Scaled residuals
AIC
Two
N/Ab
0.000, -0.000, and -
0.000
173.68
75.6
41.6
Multistage 1° was
selected as the only
adequately-fitting
model available
One
0.924
0.031, -0.078, and
0.045
171.69
70.1
41.6
aSelected model in bold.
bNo available degrees of freedom to calculate a goodness of fit value.
Multistage Cancer Model with 0.95 Confidence Level
dose
1 1 :02 04/30 2014
Figure C-13. Plot of incidence by dose, with fitted curve for Multistage 1°
model for renal tubule adenoma or carcinoma in male F344 rats exposed to
tert-butanol in drinking water for 2 years modeled with administered dose
units and excluding high-dose group (NTP. 1995): BMR = 10% extra risk.; dose
shown in mg/kg-d.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Multistage Cancer Model. (Version: 1.9; Date: 05/26/2010)
The form of the probability function is: P[response] = background + (l-background)*[l-EXP(-
betal*doseAl-beta2*doseA2...)]
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 atthe 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(l)
0.00150286
0.0015217
Analysis of Deviance Table
Model
Log(likelihood
)
# Pa ram'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
ChiA2 = 0.01 d.f = 1 P-value = 0.9239
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1
2
3
4
5
6
7 Table C-17. Summary of BMD modeling results for renal tubule adenoma or
8 carcinoma in male F344 rats exposed to tert-butanol in drinking water for 2
9 years modeled with administered dose units and excluding high-dose group;
10 re-analyzed data (Hard et al.. 2011: NTP. 1995): BMR = 10% extra risk
11
Model3
Goodness of fit
BMDiopct (mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model
selection
P-
value
Scaled residuals
AIC
Two
One
0.572
-0.141, 0.461, and -
0.296
154.84
54.2
36.3
Multistage 1° was
selected as the most
parsimonious model
of adequate fit.
aSelected model in bold.
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 administered dose units and including all dose groups;
reanalyzed data (Hard et al.. 2011: NTP. 19951: BMR = 10% extra risk
Model3
Goodness of fit
BMDiopct (mg/kg-d)
BMDLiopct
(mg/kg-d)
Basis for model
selection
P-
value
Scaled residuals
AIC
Three
Two
One
0.0117
-1.476, 1.100, 1.855,
and -1.435
218.68
184
94.8
No model fit the
data.
aNo model was selected as a best-fitting model.
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Multistage Cancer Model with 0.95 Confidence Level
Figure C-14. Plot of incidence by dose, with fitted curve for Multistage 1°
model for renal tubule adenoma or carcinoma in male F344 rats exposed to
tert-butanol in drinking water for 2 years modeled with administered dose
units and excluding high-dose group; re-analyzed data fHard et al.. 2011: NTP.
1995): BMR = 10% extra risk; 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 + (l-background)*[l-EXP(-
betal*doseAl-beta2*doseA2...)]
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 atthe 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(l)
0.00194521
0.00179645
Analysis of Deviance Table
Model
Log(likelihood)
# Pa ram's
Deviance
Test d.f.
p-value
Full model
-75.2622
3
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
Fitted model
-75.4201
2
0.315716
1
0.5742
Reduced
model
-81.4909
1
12.4574
2
0.001972
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
ChiA2 = 0.32 d.f = 1 P-value = 0.5715
This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
1 APPENDIX D. PATHOLOGY CONSULT FOR ETBE AND
2 ferf-BUTANOL
This document is a draft for review purposes only and does not constitute Agency policy.
F-l DRAFT—DO NOT CITE OR QUOTE
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Supplemental Information—tert-Butyl Alcohol
UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
November 28. 2018
To: John Buclier. NTP
From: Kristina Thayer, NCEA-IRIS
Subject: Pathology consult for ETBE and tBA
Purpose
The purpose of tins memo is to request a consult for pathoiogy-related issues discussed 111 die
ethyl tertiary butyl etliei iETBE i and fert-biityl alcohol (tBA; draft IRIS assessments,. This
request is bemg conducted under the existing MOU between EPA XC EA find the Xation.il
Toxicology Program i XTP: that covers cooperation and communication in the development of
human health toxicological assessments.
Background
The draft IRIS assessments identify kidney effects as a potential human hazard of ETBE and its
metabolite tBA. primarily based on evidence m rats iETBE and tBA Sections 1.2.1. 1.3.1). EPA
evaluated the evidence, including the role of a2u — globulin! in accordance vs'icli EPA guidance
[U,S, EPA. 1991] i and chronic piogressive nephropathy (CPX: for which no formal guidance is
available i. tBA was determined to induce o.2u -globulin mediated nephrotoxicity. however, for
ETBE, although increased hyaime droplets of ct2u -globulin were observed, data were insufficient
to conclude that ETBE induces o'2o-glob«liii nephropathy i only one of the five steps in the
pathological sequence, linear' mineralization, was consistently observed), Both chemicals show
dose-i elated exacerbation of CPX iinci eased incidence and or severity), as well as lesions tliar are
not specifically defined as C PX (increased urothelial hyperplasia of the renal pelvis and
suppurative inflammation I but are reported to be associated with late stages of CPX I Frazier et
al.. 2012 i. Tims, EPA selected urothelial hyperplasia transitional epithelial hyperplasia of the
renal pelvis as the basis for the reference values for both ETBE and tBA.
The SAB committee reviewing ETBE and tBA was unable to reach a consensus with lespect to
how the EPA interpreted the ETBE and tBA databases for noncancer kidney effects. There was
disagreement within the SAB as to whether any noncancer kidney effects for ETBE and tBA
should be considered a hazard relevant to humans. Specifically, the difference m opinion was
related to the extent of confidence in the roles that CPX and or cOu-glcbulin-based mechanisms
played m the development of the renal effects seen with tBA and ETBE,
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C barge Questions
In tins pathology consult. IRIS is seeking additional input on the icle that «2u-globulin and CPN
play in the observed kidney toxicity, Please consider the following questions and provide
references, as applicable, with your responses, Please also comment on any sex-related aspects
that are pertinent to these questions,
• Is the etiology of CPX" in rats known?
• Are urothelial hyperplasia of the renal pelvis and transitional epithelial hyperplasia of the
renal pelvis considered to be the same lesion?
• Suppurative inflammation and urothelial hj'peiplasia have been reported to be associated
with advanced stages of CPN , i 201 Oa: Carcinogenicity test of 2-Ethoxy-2-
methylpropane m rat-1 Drinking water study j, i Stud}- Xo; 0691!
JPEC 1,2010b I Carcinogenicity test of 2-Etlioxy-2-
methyipropane m rats i Inhalation study! j Stud;- Xo; 06S6!
Kiistina Thayer, Ph.D.
Director. XCEA-IRIS
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DEPARTMENT OF HEALTH & HUMAN SERVICES
Public Health Service
National Institutes of Health
National Institute of
Environmental Health Sciences
P. O. Box 12233
Research Triangle Park, NC 27709
Website: httpi/www. niehs.nih.gov
February 13, 2019
Kristina Thayer, Ph.D.
Director, NCEA-IRIS
U.S. Environmental Protection Agency
109 T.W. Alexander Drive, MD B243-01
Research Triangle Park, NC 27709
Dear Dr. Thayer,
With respect to your November 28, 2018 request for a pathology consult under the NTP/NCEA
Memorandum of Understanding, I asked Dr. Robert Sills, Chief, Cellular and Molecular Pathology
Branch to provide responses reflecting the current NTP perspective on the issues you raise. Dr. Sills
worked with John Curtis Seely, DVM Diplomate, ACVP Senior Pathologist Experimental Pathology
Laboratories, tnc, an internationally recognized expert in rodent renal pathology, to provide
answers to your questions.
1. Is the etiology of CRN known?
The etiology of CPN is unknown {Peter et al., 1986; Hard and Khan, 2004; Hard et al., 2013).
Although several theories have been postulated to be the etiology of CPN none have been
recognized as the absolute cause of CPN. Factors which have been suggested to be associated with
the etiology of CPN include genetics, increased glomerular permeability and dysfunction due to
hyperfiltration and functional overload, high renal protein levels, and hemodynamic changes. All of
these may influence the progression of CPN but do not appear to initiate renal CPN disease (Baylis,
1984; Barthold, 1998; Abrass, 2000; Hard and Khan, 2004). CPN is a spontaneous and complex
degenerative/regenerative disease process influenced by age (incidence and severity increases
with age), sex (males affected more than females), and strain (in order of highest to lowest CPN
incidence: Sprague-Dawley -^Fischer 344 -^Wistar rats). It can be modified by diet (increased
protein and high caloric intake), hormones (testosterone, estrogen), and many other factors (Seely
et al., 2018).
2. Are urothelial hyperplasia of the renal pelvis and transitional epithelial hyperplasia of the renal
pelvis considered to be the same lesion?
Yes, the older terminology of "transitional epithelium hyperplasia, renal pelvis" is being updated
and replaced by the newer terminology of "urothelial hyperplasia, renal pelvis". Urothelium is
recognized as the correct terminology of the epithelium lining the renal pelvis, ureter, urinary
bladder and a portion of the urethra (Frazier and Seely, 2018). However, in advanced stages of CPN
a type of epithelial proliferation/hyperplasia may be observed along the epithelial lining of the
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tetial papilla which :n some older studies was designated as "urothelial hyperplasia". Recently, the
epithelial lining of the renal papilla has been unequivocally demonstrated to represent a type of
epithelium different from the urothelium lining the renal pelv's, The difference between
urothelium (uroplakin positive) and the ep'theliurr lin'ng the renal papilla {uroplakin negative) was
confirmed by irrrrunostaining for uroplakin (a d st'nct cell marker for urothekum) (Souza et ak,
2018).
3, Suppurat've 'nflammation and urothelial hyperplasia have been reported to be associated with
advanced stages of f PN (Fraz'er et ak, 2012), Does NTP agree with this conclus:on? Are these
lesions also assoc:ated w~th a2u-globul'n nephropathy?
Renal inflammation is not uncommon in the laboratory rat and can be observed throughout all
portions of the kidney, Withr'n the pelvis, :nflammation tends to result in a reactive hyperplasia of
the urothelium |Seely et at., 201.3), Most cases of suppurative inflammation and urothelial
hyperplasia are observed as spontaneous changes of undetermined origin, InterstYa! mononuclear
cell 'nfiltrates are commonly observed in advanced stages of CPN (Frazier and Seeiy, 2018),
However, suppurative inflammation and urothelial hyperplasia are typically unrelated to CPM or, at
most, occasionally noted as an uncommon secondary change to CPN, Therefore, CPN does not
directly result in suppurative inflammation or urothekal hyperplasia of the renal pehrs in its
advanced stages, Cases of suppurative Inflammat'on and urothelial hyperplasia are more Fkeiy to
be associated vrth the presence of renal pelv'c mineralization, pelvic calculi, or from an ascending
bacterial infection or pyelonephritis (Seeiy et ak, 2018). Furthermore, minerakzation has been
reported to be associated with an increased iru'dence and sever'ty of spontaneous 'riflammation
and urothelial hyperplasia in the renal pelvis of female rats (Tomonah et ak, 2016), In addition,
there is no information that appears to support that suppurative inflammation and pelv'c urothelial
hyperplasia are cliitectly associated with the spectrum of morphological changes associated w:th
a2u-glohulin nephropathy (Frazier et ak, 2012; Frazier and Seeiy. 2018).
4, CPN exacerbation has been reported in some chenfcals that NTP identified as candidates for a tmt
via the a2u-globul'n pathway {Travlos et ak, 2011). A theory has been proposed that CPN
exacerbation seen in male animals with ETBE and tBA exposure is caused by a2-globu!in related
processes. Please comment on the strength of the above proposition
According to the (ARC Scientific Publication No. 147 (1999), chemicals which cause a2u-globulin
nephropathy are often associated with an accelerated onset and severity (exacerbation) of the
cortical changes typical of chronic progressive nephropathy seen in older male rats (Alden et ak,
1984; Svvenberg and Lehman-McKeenan, 1999, Travlos et ak, 2011' Frazier et ak, 2012). However,
studies on 2-ethoxy-2 methylpropene (ethyl tertiary butyl ether; inhalation and drinking water
studies) confirmed the presence of exacerbated CPN in both male and female rats at the highest
dose levels (Japan Industrial Safety and Health Association/japan Bioassay Research Center, 2010'
2010b). Because of "urothelial hyperplasia'' and linear pelvic (papillary) m'neralizat'on noted in the
male rats from these studies, lit was proposed that ct2u-globulin nephropathy contributed to the
exacerbation of CPN in the males although no pathogeneses of the exacerbated CPN in females was
given, Additionally, in these studies, "urothelial hyperplaj'a"' was apparently and according to its
description more likely to represent a proliferation of the papillary lining epithelium and not
representative of true "urothelial hyperplasia". This proliferative epithelial finding is often observed
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as part of advanced cases of rat CPW and has no similarity to any human renal papillary findrng
(Seely et al., 2018: Souza et al,, 201S), Long term exposures to methyl tertiary -butyl ether also
resulted in an a2u-globulin nephropathy and exacerbated CPN n both male and female rats
(Cruzan et al., 2007). The etiology of exacerbated CPN in females is not known since alu-glabulin
nephropathy is regarded as a male only cond'tion. Therefore, although ctlu-globulin nephropathy
may account for cases of chemically exacerbated CPN, other undetermined factors contributing to
CPN exacerbation cannot be discounted (Doi et al,, 2007).
5. it has been hypothesized that there is no analog to the CPN process in the aging human kidney.
Does this posit'on reflect the consensus in the field of pathology.
Yes, the publication by Hard, Johnson, and Cohen makes a very strong case that the renal
development, b'ological behavior, and morphological spectrum of CPN have no analog in the
human kidney and that CPN is a distinct entity in the rat, {Hard et al., 2009), Overall, CPN has
prominent protein filled dilated tubules, no vascular changes, no 'nvnunological or autoumnume
basis, and little inflammation which distinguishes CPN from most human nephropathies (Hard et
al,, 2009), There appears to be nothing 'n the literature that counters this assumption.
8, Given what is known about the biology of CPN development in rodents, 's't plausible a chemical
which exacerbates CPN in rats could also exacerbate disease processes in the human kidney (e.g.
diabetic nephropathy, glomerulonephritis, interst:tlal nephritis)?
The ecology of CPN is unknown and represents a complex disease piocess 'n rats. Given the fact
that there is no definitive pathogenesis for this multifactorial disease process, it cannot be fullv
ruled out that chemicals whicn exacerbate CPN in rats may have the potent'3l to exacerbate
disease processes in the human kidney.
Please let me know if you have additional questions or wish further clarification of any of these
responses.
Sincerely,
John Bucher, Ph D.
National Tox'cology Program,
NIEHS
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References;
Abrass CK. 2000, The nature of chronic progressive nephropathy in aging rats. Adv Renal
Replacement Therapy 7(1): 4-10.
Alden CL, Kanerva RL, Ricider G, Stone LC. 1984. The pathogeneses of the nephrotoxicity of volatile
hydrocarbons in the male. In: Renal Effects of Petroleum Hydrocarbons, Advances in Modern
Environmental Toxicology, Vol 7. MA Mehlman, CP Nemstreet, JJ Thorpe, NK Weaver {eels}
Princeton Sc- Pub, Princeton. NJ, pp, 107-120,
Bartholcl SW. 1998, Chronic progressive nephropathy, rat. In: Urinary System. 2"" ed, TC Jones, GC
Hard, U Mohr (eds), pp 228-233, Spnnger-Verlag, Berlin.
Baylis C. 1994, Age-dependent glomerular damage in the rat: dissociation between glomerular
injury and both glomerular hypertension and hypertrophy. Male gender as a primary risk factor, i
Clin Invest 94:1823-1829.
Capen CC et al, (eels)11999, Speoes Differences in Thyroid, Kidney and Urinary Bladder
Carcinogenesis, IARC Scient'fic Publications No, 147, internat:onal Agency for Research on Cancer,
Lvon, France.
Cruzan G, Borghoff SJ, cle Peyiter A, Hard GC, McClain M, McGregor DB,Thomas MG, 2007, Reg
Toxicol Pharmacol 47: 156-165,
Doi AM, Hill G, Seelyi, Hailey JR. Msding G, Bucher JR. 2007 ct2j-globulin nephropathy and renal
tumors in National Toxicology Program studies, Toxicol Pathol 35:533-540,
Frazier KS, Seely JC, Hard GC, Betton G, Burnet R, Nakatsuj' S, Nishil> jwa A, Durchfeld-Meyer B,
Bube A 2012, Proliferative and nonproliferative les:ons of the rat and mouse urinary system,
Toxicol Pathol 40 (4 Suppl): 14S-865.
FrazterKS, Seely JC, 2018, Urinary system, In: Toxicologic Pathology NoncluVcal Safety
Assessment, 2nd ed, PS Sahota, JA Popp, PR Bouchard, JF Harclisty, C Gopinath (eels), CRC
press/Taylor and Francis, Boca Raton, pp. 569-638,
Hard GC, Khan KN, 2004, A contemporary overview of chronic progressive nephropathy "n the
laboratory rat and its significance for human risk assessment, Toxicol Pathol 32:171-180
Hard GC, Johnson KJ, Cohen SM. 2009. A comparison of rat chronic progressive nephropathy with
human renal d:sease-implications for human risk assessment. Crit Rev Toxicol. 39(41:332-346.
Japan Industrial Safety and Health Association/Japan Bioassay Research Center. 2010',
Carcinogenicity Test of 2-ethoxy-2-methypropene :n Rat (Drinking Water Study (Study 0691).
Japan industrial Safety and Health Association/Japan Bioassay Research Center, 2010",
Carcinogenicity Study of 2-ethyI-2-methylpropene in F344 Rats (Study 0686).
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Peter CP, Burek JD, van Zvvieten MJ. 1986 Spontaneous nephropathies in rats. Toxicol Pathol
14(15:91-100.
Seely K, Hard GC, Btanl-enship B. 2018, K'ciney. In: Boorman's Pathology of the Rat. AWSutte JR
Leininger, AE Bradley jedij, pp. 125-186, Elsevier, Academic Press.
Souza N. Hard G, Arnold L, Foster K, Pennington K, Cohen S, 2018, EpitheFum lining rat renal
papilla: nomenclature and association with chronic progressive nephropathy (CPNl Toxicol Pathol
46(31:266-272.
S wen berg JA, Lehman-McKeenan LD, 1998. a2- Ur«nary globulin-associated nephropathy as a
mecharvsm of renal tubule cell catenogenesis 'n male rats. 199S In: Species Differences in
Thyroid, Kidney, and Urinary Bladder Carcinogenesis, CC Capen, E Dybing E, JM Rxe, JD Eilboum
(eels), IARC Sc'entific Publications No 147. I ARC, Lyon pp 95-118,
Tomonari Y, kurotdl i T, Sato i, Doi T, Kokoshima H, Kanno T, Tsuchitani M, Seefy JC 2016,
Spontaneous age-related lesions of the kidney fornices in Spraeue-Dawley rats. Tox'col Pathol 44:
226-232,
Travlos GS, Hard GC, Betz U, KissPng GE. 2011. Chronic progressive nephropathy in male F344 rats
in 90-day toxicity studies: its occurrence and associated with renal tubule tumors in subsequent 2-
Vear bioassays, Toxicol Pathol 39:381-339,
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APPENDIX E. SUMMARY OF SCIENCE ADVISORY
BOARD (SAB) PEER REVIEW COMMENTS AND
EPA'S DISPOSITION
The Toxicological Review of tert-butyl alcohol [tert-butanol; tBA), dated June 2017,
underwent a formal external peer review in accordance with U.S. Environmental Protection Agency
(EPA) guidance on peer review (U.S. EPA, 2015). This peer review was conducted by the Chemical
Assessment Advisory Committee (CAAC) Augmented for Review of the Draft IRIS tert-butanol
Assessment (SAB-CAAC tert-butanol panel) of EPA's Science Advisory Board (SAB). An external
peer review workshop was held on August 15-17, 2017. Public teleconferences of the SAB-CAAC
tert-butanol panel were held on July 11, 2017, March 22, 2018, March 27, 2018, and June 6, 2018.
The Chartered SAB held a public meeting on September 26, 2018 to conduct a quality review of the
draft SAB-CAAC peer review report1. The final report of the SAB was released on February 27, 2019.
The SAB-CAAC was tasked with providing feedback in response to charge questions that
addressed scientific issues related to the hazard identification and dose-response assessment of
tert- butanol. Key recommendations of the SAB2 and EPA's responses to these recommendations,
organized by charge question, follow. Editorial changes and factual corrections offered by SAB were
incorporated in the document as appropriate and are not discussed further.
1. Literature Search/Study Selection and Evaluation - Systematic Review Methods
Charge Question 1. Please comment on the strategy for literature searches, criteria for study
inclusion or exclusion, and evaluations of study methods and quality discussed in the
Literature Search Strategy/Study Selection and Evaluation section. Were the strategies
clearly described and objectively applied?
Key Recommendation: The SAB recommended EPA should provide clarification on the rationales
for several decisions that impacted how the literature search was conducted. This includes (a) the
rationale for the selection of some synonyms of tert-butanol as key search words and not others;
(b) the rationale for imposing limitations on sources in the first stage of the scientific literature
1 During the quality review by the Chartered SAB, 2 of the 44 members provided dissenting comments related to
the cancer weight of evidence descriptors and the quantitative cancer risk estimates for ETBE and tBA. These
comments were included as an appendix to the final SAB report and are summarized and addressed following the
disposition of the SAB-CAAC recommendations below.
2 The SAB provided tiered recommendations: Tier 1 (key recommendations), Tier 2 (suggestions), and Tier 3
(future considerations).
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search (i.e., PubMed, Web of Science); and (c) the rationale for limiting the search for additional
citations to only some of the publications available in peer-reviewed literature and secondary
sources, but not others.
Response: The literature search was developed and executed in consultation with information
specialists and librarians through EPA's Health and Environmental Research Online (HERO)
database. This includes developing, testing, and implementing a comprehensive literature search
strategy in an iterative and collaborative manner, (a) The most common synonyms and trade
names were used as the keywords in the literature search. This included the preferred IUPAC name
of 2-Methylpropan-2-ol. Clarification has been added in the Literature Search Strategy/Study
Selection and Evaluation Section, (b) PubMed, Web of Science, and Toxline are the core sources that
IRIS uses for published studies. Prior experience has also demonstrated that searching of PubMed,
Web of Science and Toxline provides sufficient coverage for literature pertinent to human health
assessments. TSCATS2 database was included to capture submissions of health and safety data
submitted to the EPA either as required or voluntarily under certain sections of TSCA. Based on the
attributes of the chemical, along with input from HERO, EPA did not include supplemental
databases (e.g., databases for pesticides, U.S. Department of Agriculture (USDA)-related compounds
or inhalation values). Clarification has been added in the Literature Search Strategy/Study Selection
and Evaluation Section, (c) To ensure no key studies were missed, a manual search of citations was
performed on published reviews and studies identified from public comments, as well as reviews
previously conducted by other international and federal health agencies. Table LS-2 lists the
approach used and the sources used in the manual searching of citations.
Key Recommendation: The SAB recommended EPA should provide a rationale for the exclusion of
studies of dermal contact as a relevant route of exposure in light of the occurrence of tert-butanol in
many consumer products such as perfumes and cosmetics.
Response: Studies evaluating dermal exposure were not excluded (see Table LS-3 on inclusion-
exclusion criteria). Several studies were identified that examined acute dermal exposures; however,
as stated in the Literature Search Strategy/Study Selection and Evaluation Section, studies
investigating the effects of acute dermal chemical exposures are generally less pertinent for
characterizing health hazards associated with chronic exposure, and therefore were not
considered as primary evidence. These studies were considered as sources of supporting health
effects data (see Figure LS-1).
Key Recommendation: The SAB recommended EPA should provide a justification for the complete
exclusion of studies with non-mammalian species, which affects the completeness of the hazard
identification.
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Response: As described in Table LS-3, the populations of interest are humans and animals. Non-
mammalian species were not included because studies in mammalian model systems are available.
However, these studies were considered supplemental and retained as secondary literature and
sources of contextual information as shown in Figure LS-1.
Key Recommendation: The SAB recommended EPA should provide more transparent
documentation of the process of application of inclusion and exclusion criteria and the quality
evaluation of studies, in order to support decision making by the EPA. This could be done through
the HERO database.
Response: This assessment was conducted prior to the implementation of systematic review tools
in the IRIS program, like HAWC, that could be used to document the systematic review process.
Database evaluation is described in the Literature Search Strategy/Study Selection and Evaluation
Section. As stated in the section, information on study evaluation is reported in evidence tables and
documented in the synthesis of evidence. Study strengths and limitations are also included in the
text, where relevant.
2. Hazard Identification-Chemical Properties and Toxicokinetics
Charge Question 2a.-Chemical Properties- Is the information on chemical properties accurate?
Key Recommendations: The SAB recommended EPA make improvements to the chemical
properties table by focusing on increasing confidence and transparency in the values presented.
The SAB also recommended the use of a template focusing on the chemical properties most
relevant to the chemical and the assessment Several recommendations focused on a preference for
the citation of chemical properties from primary sources, for vetting the data in cases in which
more than one value is published, and for presenting rationales for the selected values.
Response: In response to SAB comments, EPA has revised the tert-butanol chemical properties
table (Table 1-1) to present average experimental and predicted chemical properties from high
quality databases as curated by EPA's CompTox Chemicals Dashboard
(https://comptox.epa.gov/dashboard). EPA's CompTox Chemicals Dashboard aggregates and
presents both experimental and predicted chemical property data, with links to the source and/or
model data. The experimental data are sourced from publicly available databases as well
PHYSPROP downloadable files (see Mansouri et al., 2016). Predicted chemical property data are
curated from EPISuite, OPERA models (see Mansouri etal., 2016)), NICEATM models (see Zang et
al., 2017), Toxicity Estimation Software Tool (TEST) Models, and the Open PHACTS project (as
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predicted by ACD/LabsEXIT). A key benefit of this aggregation of chemical properties over
reporting an individual measurement is a more robust point estimate than is possible from the
measure derived from any individual study, with each study reporting measurements that are
expected to have some degree of error. For more information on EPA's CompTox Chemicals
Dashboard see Williams etal. (2017).
Charge Question 2b.-Toxicokinetic modeling- Section B.1.5 of Appendix B in the Supplemental
Information describes the application and modification of a physiologically-based
toxicokinetic model of tert- butanol in rats (Borghoffet al., 2016). Is use of the model
appropriate and clearly described, including assumptions and uncertainties? Are there
additional peer-reviewed studies that should be considered for modeling?
Key Recommendations: The SAB recommended the model code should be revised to describe
metabolism as a function of the free liver concentration, CVL, and metabolic parameters (e.g., Km or
first order rate constants) should be re-estimated. Metabolism based upon total liver concentration,
CL, is not scientifically correct.
Response: Model code has been revised to describe metabolism as a function of the free liver
concentration and metabolic parameters have been re-estimated. The new final code is available in
HERO (https://hero.epa.gov/hero/index.cfm/project/page/project id/1543/usage id/2896).
Key Recommendations: The SAB recommended evaluation of tert-butanol dose metrics for kidney
toxicity should be compared for ETBE and tert-butanol exposures (similar to Figure 6 in Salazar et
al. ("201SH
Response: Change in absolute kidney weight in female rats as a function of estimated tert-butanol
blood concentration and tert-butanol rate of metabolism for both ETBE and tert-butanol exposures
has been added to Appendix B of the Supplemental Information (see Figure B-3).
Key Recommendations: The SAB recommended the overall presentation of the PBPK modeling
should be cohesive, clear, and transparent, and should provide essential information, assumptions,
results and conclusions. The text in Section 1.1.3 of the draft tert-butanol assessment and text in
Appendix should be reworded. The SAB suggests that the material in U.S. EPA (2017c) be included
in Appendix B or as a separate appendix and a conclusion section added to it.
Response: Text has been added and revised in Section 1.1.3 and Appendix B to increase cohesion
and to ensure essential information, assumptions, results, and conclusions are clear and
transparent Text describing PBPK model evaluation for the IRIS assessments of ethyl tertiary butyl
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ether and tert-butanol (US EPA, 2017c) has been added as a new appendix to the toxicological
review (Appendix B.I.7.). Text in Section 1.1.3 and Appendix B have been revised to clarify that no
models of tert-butanol have been created independently of other chemicals from which it arises as a
metabolite.
Charge Question 2c.-Choice of dose metric- Is the average concentration of tert-butanol in
blood an appropriate choice for the dose metric?
Key Recommendation: The SAB recommended EPA state in the draft tert-butanol assessment how
the average concentration of tert-butanol in blood was calculated given that the SAB agrees with
use of this dose metric. The SAB also agreed with the use of an oral to inhalation extrapolation for
tert- butanol.
Response: For non-continuous exposures the PBPK model was run for a number of days or weeks
such that the predicted time course of tert-butanol in blood did not change with further days or
weeks simulated. The average blood concentration of tert-butanol was calculated during the final
periodic exposure. For uniformity, all scripts now calculate the average from episodic exposures on
the basis of the final week of exposure (regardless of whether exposure is once per day or 5 times
per week, since either exposure profile will be fully captured by averaging a 1-week time
period). Details on how the average concentration of tert-butanol in blood was calculated has been
added to Section 2.2.2, under subsection PODsfrom oral studies- use of PBPK model for route-to-
route extrapolation.
3. Hazard Identification and Dose-Response Assessment- Noncancer
Charge Question 3a.-Noncancer kidney toxicity (Sections 1.2.1,1.3.1) identifies kidney effects
as a potential human hazard of tert- butanol. EPA evaluated the evidence, including the role of
alpha 2u -globulin and chronic progressive nephropathy, in accordance with EPA guidance
(U.S. EPA, 1991). Please comment on whether this conclusion is scientifically supported and
clearly described.
Key Recommendation: The SAB recommended EPA should provide a more thorough explanation
for considering the enhancement of CPN as a kidney effect relevant to human hazard assessment
The SAB was unable to reach consensus on whether noncancer kidney effects should be considered
a hazard relevant to humans based on the available evidence.
Response: In response to SAB comments, EPA consulted with pathologists at the National
Toxicology Program (NTP) on the applicability of alpha 2u-globulin and the components of CPN in
the evaluation of the human relevance of kidney effects (see Appendix D of the Supplemental
Information). In consideration of the expert opinions of the pathologists, the assessment was
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revised to strengthen the explanation for considering the enhancement of CPN as a kidney effect
relevant to human hazard (see Section 1.2.1). Briefly, following tert-butanol exposure, dose related
increases in kidney weight and exacerbation of CPN were observed in both male and female rats.
While tert-butanol exposure has been shown to act through an alpha-2u-globulin mechanism in
male rats (which can exacerbate CPN, see Section 1.2.1), the dose related exacerbation of kidney
effects in female rats cannot be explained by a2u-globulin. The NTP consultation NIEHS. 2019
acknowledged existing literature and concluded that no analog to CPN occurs in humans (Hard et
al.. 2009) and that the etiology of CPN is unknown (Hard etal. (2013): Hard and Khan (2004):
Peter et al., (1986)). However, many of the lesions observed in CPN are also observed in chronic
kidney disease in humans fLusco etal.. 2016: Zoia etal.. 2015: Frazier etal.. 2012: Satirapoi et al..
2012: NIEHS. 20191. As summarized in the consultation, NTP concluded that due to the unknown
etiology and lack of a clear pathogenesis "it cannot be ruled out that chemicals which exacerbate
CPN in rats may have the potential to exacerbate disease processes in the human kidney". A more
thorough explanation for considering the enhancement of CPN as a kidney effect relevant to human
hazard assessment has been added to Section 1.2.1.
Charge Question 3b.-Noncancer at other sites (Sections 1.2.3-6, and 1.3.1) finds inadequate
information to assess developmental, neurodevelopmental, and reproductive toxicity. Please
comment on whether these conclusions are scientifically supported and clearly described. If
there are publicly available studies to associate other health outcomes with tert-butanol
exposure, please identify them and outline the rationale for including them in the assessment.
Key Recommendation: The SAB recommended EPA include contact dermatitis (Edwards, 1982) in
hazard identification as dermal exposure is a relevant route of exposure.
Response: Studies investigating the effects of acute dermal exposures are generally less pertinent
for characterizing health hazards associated with chronic exposure. However, these studies were
considered as sources of supporting health effects data (see Figure LS-1).
Key Recommendation: The SAB recommended EPA change the description to "minimal effects at
otherwise toxic dose levels," rather than "inadequate information to assess," since the SAB believes
there is an adequate amount of information, and only minimal effects have been shown, even at
toxic dose levels.
Response: The description of noncancer effects was revised to be responsive to the SAB's suggested
language in Sections 1.2.3-1.2.6 and 1.3.1.
Charge Question 3c.-Oral reference dose for noncancer kidney outcomes- Section 2.1 presents
an oral reference dose of 4x10-1 mg/kg-day, based on increases in severity of nephropathy in
female rats via drinking water (NTP, 1995). Please comment on whether this value is
scientifically supported and its derivation clearly described. If an alternative data set or
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approach would be more appropriate, please outline how such data might be used or how the
approach might be developed.
Key Recommendation: The SAB recommended EPA carefully reexamine the validity and
applicability of the endpoints chosen and analyzed for the oral RfD for tert-butanol, including the
potential for CPN and/or alpha- 2u-globulin to serve as mechanism(s) of the kidney effects of tert-
butanol, in light of SAB advice regarding consideration of the criteria for definition of CPN. The SAB
was unable to reach a consensus as to whether the selection of nephropathy effects was
appropriate. The SAB states that if EPA determines that increases in severity of nephropathy in
female rats following tert-butanol in drinking water exposure remains the basis of the oral RfD,
then the "SAB considers the derivation of the oral reference dose to be scientifically supported and
its derivation clearly described".
Response: As recommended by SAB, EPA carefully reexamined the kidney endpoints analyzed for
the RfD with consideration of CPN and alpha 2u-globulin. EPA also consulted with pathologists at
the National Toxicology Program (NTP) on the applicability of alpha 2u-globulin and the
components of CPN in the evaluation of the human relevance of kidney effects (see Appendix D of
the Supplemental Information). With this additional expert consultation, the assessment has been
revised to clarify which effects were considered and to strengthen the justification regarding the
human relevance of the observed kidney effects. For example, the assessment was revised to clarify
that the kidney endpoints in males were not considered and the endpoints in females not
confounded by alpha-2u-globin were considered (Section 1.2.1). See Integration of Kidney Effects in
Section 1.2.1 of the Toxicological Review. See also response to Charge Question 3a.
Key Recommendation: The SAB recommended that the units need to be added to the tables in this
section for completeness and interpretability. It would be useful to attempt a more integrated
presentation of the current text, tables and graphs (i.e., the EPA should present key and related
information/graphics on concurrent pages as much as possible). As currently laid out, the reader is
forced to engage in a lot of page flipping in order to read the draft tert-butanol assessment, making
it difficult to track information.
Response: Units have been added to the tables were missing, however, endpoints which display
changes as "% change relative to control" are unitless. A more integrated presentation of text, table
and figures is being implemented in future IRIS assessment templates.
Key Recommendation: The SAB recommended EPA include the outcomes of statistical analyses and
their rationale in study selection choice in the draft tert-butanol assessment.
This document is a draft for review purposes only and does not constitute Agency policy.
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Response: Statistical significance as reported by the study authors was included in the appropriate
evidence tables in Section 1.2.1. Key toxicological effects in the kidney were reported in eight
studies derived from five references following oral exposure (Section 1.2.1). However, all kidney
outcomes considered for dose response were derived from a single study fNTP. 19951. As described
in Section 2.1.1, NTP. 1995 was identified as the most suitable for dose-response assessment
considering the study duration, comprehensive reporting of outcomes, and multiple doses tested.
Section 1.2.1 has been edited for clarity.
Charge Question 3d.-Inhalation reference concentration for noncancer kidney outcomes-
Section 2.2 presents an inhalation reference concentration of 5x100 mg/m3, based on
increases in severity of nephropathy in female rats via drinking water (NTP, 1995), converted
for inhalation exposure using a toxicokinetic model (Borghoffet al., 2016). Please comment on
whether this value is scientifically supported and its derivation clearly described. If an
alternative data set or approach would be more appropriate, please outline how such data
might be used or the approach might be developed.
Key Recommendation: The SAB recommended EPA provide more detailed information about the
specific application of the Borghoff et al. (2016)/U.S. EPA (2017e) PBPK model used for route-to-
route extrapolation to derive the inhalation RfC.
Response: Detailed information has been provided in Section 2.2 under PODsfrom oral studies- use
of PBPK model for route-to-route extrapolation. This includes the choice of internal dose metric and
uncertainty inherent in the use of a PBPK model for route-to route extrapolation. Section 2.2.4.
provides an explanation for why preference was given to an RfC derived from the route-to-route
extrapolated POD based on the chronic oral study over a POD from the subchronic inhalation study.
Key Recommendation: The SAB recommended EPA provide more reporting of statistical analysis of
individual studies to help clarify the appropriateness of inclusion/exclusion and use of studies.
Response: Statistical significance as reported by the study authors has been included in the
appropriate evidence tables for each hazard section. The rationale for study selection and endpoint
inclusion is discussed in Section 2.1.1.
4. Hazard Identification and Dose-Response Assessment- Cancer
Charge Question 4a.-Cancer modes of action
(i) Cancer modes of action in the kidney- As described in section 1.2.1, kidney tumors were
observed in male rats following tert-butanol exposure, and a mode-of-action involving alpha
2u-globulin and/or chronic progressive nephropathy was evaluated. The analysis, conducted
in accordance with EPA'sguidance on renal toxicity and neoplasia in the male rat (U.S. EPA,
1991), considered the kidney tumors in male rats to be relevant to human hazard
identification. Please comment on whether this conclusion is scientifically supported.
This document is a draft for review purposes only and does not constitute Agency policy.
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Key Recommendation: The SAB recommended EPA provide additional justification for the
assumption that kidney tumors in male rats exposed to tert-butanol are relevant to humans.
Response: Based on EPA fU.S. EPA f!991al and IARC criteria fCapen etal.. 19991 alpha 2u-globulin
may contribute to kidney tumor formation in male rats exposed to tert-butanol (See section 1.2.1).
However, evidence indicative of the alpha 2u-globulin process was not consistently observed across
all studies. This observation suggests that tert-butanol may be a weak inducer of alpha 2u-globulin
and its associated nephropathy. These inconsistencies are discussed in detail in Section 1.2.1.
Although renal tubule hyperplasia and renal tumors are poorly correlated following tert-butanol
exposure fNTP. 19951. there is a moderate correlation between CPN and renal tumor incidence in
male rats suggesting a role for CPN in renal tumorigenesis. EPA requested an independent
pathology consultation on the applicability of alpha 2u-globulin and CPN on kidney effects ffNIEHS.
2019): see Appendix D). NTP (NIEHS. 2019) concluded that the unknown etiology and poorly
understood pathogenesis of CPN suggest that chemicals that exacerbate CPN may potentially induce
kidney effects in humans. CPN also was exacerbated in female rats in the absence of renal tumor
formation; therefore, it is also possible that other unknown mechanisms relevant to humans
contribute to renal tumor formation in male rats. Additional justification for the human relevance of
kidney tumors in male rats exposed to tert-butanol has been added in Section 1.2.1.
(iij Cancer modes of action in the thyroid- As described in section 1.2.2, thyroid tumors were
observed in male and female mice following tert-butanol exposure, and an anti-thyroid mode-
of-action was evaluated. The analysis, conducted in accordance with EPA'sguidance on thyroid
follicular cell tumors in rodents (U.S. EPA, 1998), found the information inadequate to
determine whether an anti-thyroid mode-of-action was operating and considered the thyroid
follicular cell tumors in male and female mice to be relevant to humans. Please comment on
whether this conclusion is scientifically supported.
Key Recommendations: The SAB concurred with EPA's determination that the mode of action for
follicular tumors is unknown in male and female mice following tert- butanol exposure and should
be considered relevant to humans in accordance with EPA policy. The SAB had no specific
recommendations.
Response: No response needed.
Charge Question 4b- Cancer characterization- As described in sections 1.2.1,1.2.2, and 1.3.2,
and in accordance with EPA's cancer guidelines (U.S. EPA, 2005), the draft assessment
concludes that there is suggestive evidence of carcinogenic potential for tert-butanol, based on
thyroid follicular cell tumors in male and female B6C3F1 mice via drinking water and on renal
tubule tumors in male F344 rats via drinking water. Please comment on whether this cancer
descriptor is scientifically supported. If another cancer descriptor should be selected, please
outline how it might be supported. Please comment on whether the "suggestive evidence"
cancer descriptor is scientifically supported for all routes of exposure. If another cancer
descriptor should be selected, please outline how it might be supported.
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2 Key Recommendation: The SAB agrees that there is scientific support for EPA's conclusion that
3 there is suggestive evidence of carcinogenic potential for tert-butanol for all routes of exposure. The
4 SAB recommended EPA expand the scope and breadth of its discussion of potential modes and sites
5 of action of tert-butanol on the thyroid.
6
7 Response: Discussion of modes of action for thyroid tumor formation was expanded in Section 1.2.2
8 and Appendix B to include studies that evaluate the mutagenic mode of action as recommended by
9 EPA's guidance on the assessment of thyroid cell tumors (U.S. EPA. 1998b) (See section 1.2.2 and
10 Appendix B). Information on other potential MOAs for tert-butanol in the thyroid is not currently
11 available.
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13 Charge Question 4c- Cancer toxicity values- Section 3 of EPA's cancer guidelines (2005) states:
14 "When there is suggestive evidence, the Agency generally would not attempt a dose-response
15 assessment, as the data generally would not support one, however, when the evidence includes
16 a well-conducted study, quantitative analyses may be useful for some purposes, for example,
17 providing a sense of the magnitude and uncertainty of potential risks, ranking potential
18 hazards, or setting research priorities. In each case, the rationale for the quantitative analysis
19 is explained, considering the uncertainty in the data and the suggestive nature of the weight of
20 evidence." Please comment on whether Sections 2.3 of the draft assessment adequately
21 explains the rationale for including a quantitative analysis given the "suggestive evidence"
22 descriptor. Also comment whether the NTP (1995) study is a suitable basis for this quantitative
23 analysis.
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25 Key Recommendation: The SAB recommended EPA provide a rationale for performing a
26 quantitative analysis of thyroid tumors in Section 2.3 and suggested EPA consider potential worker
27 and consumer exposures as a rationale. The SAB thought the dose-response modeling of thyroid
28 tumors may not be useful because tumors were only observed at the highest dose; however, several
29 committee members supported conducting a quantitative analysis to provide some sense of
30 magnitude of potential carcinogenic risk. Therefore, the SAB recommended EPA refrain from
31 conducting a quantitative analysis for tert-butanol carcinogenicity or explain the limitations of the
32 analysis and clearly state the intended purpose is to simply provide some sense of the magnitude of
33 potential risks.
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3 5 Response: A rationale for performing a quantitative analysis of thyroid tumors has been added to
36 Section 2.3, including potential worker and consumer exposures. One possible limitation in the
37 interpretation of thyroid tumors that has been added to the discussion in the assessment is the
3 8 increased incidence of thyroid tumors observed at highest dose tested and the possibility of
39 nonlinear kinetics at the high dose. However, at the high dose level no increase in mortality was
40 observed in female mice suggesting that the incidence of thyroid tumors was neither confounded
41 by increased mortality nor exceeded the MTD (see added text in Section 1.2.2). Text was added to
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1 clearly state the intended purpose is to simply provide some sense of the magnitude of potential
2 risks (See added text in Section 2.3).
3
4 Charge Question 4d- Oral slope factor for cancer- Section 2.3 presents an oral slope factor of 5
5 xl 0-4 per mg/kg-day, based on thyroid tumors in male or female mice via drinking water
6 (NTP, 1995). Please comment on whether this value is scientifically supported and its
7 derivation clearly described. If an alternative approach would be more appropriate, please
8 outline how it might be developed.
9
10 Key Recommendation: The SAB had no specific recommendations. The SAB was unable to reach a
11 consensus on the suitability of the NTP (1995) drinking water study for developing an oral slope
12 factor. Some reviewers were concerned about the potential lack of biological relevance due to the
13 magnitude of the high dose and the possibility of non-linear kinetics at the high dose at which
14 follicular tumors were observed. However, other members concluded that EPA's choice for the oral
15 slope factor for tert-butanol was scientifically supported.
16
17 Response: Justification (including strengths and limitations) for the derivation of an oral slope
18 factor using thyroid tumors in mice was added in Section 1.3.2, as well as Sections 1.2.2 and 2.3 (see
19 response to Question 4c).
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21 Charge Question 4e- Inhalation unit risk for cancer- Section 2.4 presents no inhalation unit
22 risk. The lack of a toxicokinetic model for mice precluded the use of the oral thyroid tumor
23 data, and the inability to determine the relative contribution of alpha 2u - globulin
24 nephropathy and other processes precluded the use of the oral renal tumor data from male
25 rats. If an alternative approach would yield an inhalation unit risk estimate, please outline
26 how it might be developed.
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28 Key Recommendation: The SAB has no specific recommendations for this tier.
29
30 Response: The SAB concurred with EPA's decision to not develop an inhalation unit risk for tert-
31 butanol.
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33 Charge Question 5- Susceptible Populations and Lifestages- As described in Section 1.3.3, the
34 draft assessment found inadequate information to identify susceptible populations or
3 5 lifestages, due to a lack of chemical-specific data. Please comment on whether this conclusion
3 6 is scientifically supported and clearly described. If there are publicly available studies to
3 7 identify other susceptible populations or lifestages, please identify them and outline their
3 8 impact on the conclusions.
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40 Key Recommendation: The SAB recommended EPA correct the actual body weight for the treated
41 group in Table 1-12 of the EPA's draft tert-butanol assessment
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43 Response: Body weight is presented as percent change in Table 1-12. No errors were identified in
44 the tables.
This document is a draft for review purposes only and does not constitute Agency policy.
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Charge Question 6- Question on the Executive Summary- The Executive Summary is intended to
provide a concise synopsis of the key findings and conclusions for a broad range of audiences.
Please comment on whether the executive summary clearly and appropriately presents the
major conclusions of the draft assessment
Key Recommendations: The SAB recommended EPA highlight the consequences of alternative
choices for the final assessment in the Executive Summary, especially when these hinge on
decisions made about the interpretation and relevance of key toxicity endpoints that have been
contested (based on the history of public comment on the draft assessment).
Response: Text has been added to the Executive Summary to more clearly highlight the context
around the interpretation and relevance of key endpoints such as the human relevance of the
observed kidney effects (see Key Issues Addressed in Assessment).
Key Recommendations: The SAB recommended EPA provide clarification for the Reference HSDB
fHSDB. 20071 cited on page xiii. Reference HSDB f20071 is cited for tert-butanol in human milk. The
two articles cited by HSDB. 2007 do not provide evidence for the presence of tert-butanol in milk.
Response: The articles cited by the HSDB. 2007 reference reported the results for 2-methyl-2-
propanol, which is a synonym for tert-butanol; demonstrating the presence of tert-butanol in
mother's milk. This synonym for tert-butanol was included in Table LS-1 for clarification.
Comments from two members of the Chartered SAB during the QA Review of the SAAB CAAC
Peer Review Report
The Chartered SAB is tasked with conducting quality reviews of draft SAB reports to
determine if they are ready for transmittal to the Administrator, reviewing whether the charge
questions were adequately addressed by the CAAC, whether the report has technical errors or
omissions, if the report is clear and logical, and if the CAAC recommendations in the report are
supported by the body of the draft report. During this quality review of the draft SAB-CAAC report
on the Draft IRIS assessments of ETBE and tert-butanol, two members of the chartered SAB (44
total members) disagreed with the CAAC regarding the recommendation for the cancer weight of
evidence descriptors for ETBE and tert-butanol. These two members provided additional
comments which were included as Appendix C of the Final SAB report A summary and response to
their comments, as they pertain to tert-butanol, are included below.
Comment: Two members of the chartered SAB disagreed with the SAB-CAAC's support of EPA's
cancer weight of evidence descriptor of "suggestive evidence" for tert-butanol. They stated tert-
butanol should be characterized as "insufficient evidence" (presumably analogous to EPA's cancer
weight of evidence descriptor for "inadequate evidence") because thyroid follicular cell tumors
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were observed only in female mice at the highest exposure concentration in the NTP 2-year
drinking water bioassay fNTP. 19951. a concentration they characterized as beyond the maximum
tolerated dose (MTD) due to a 10-15% reduction in body weight. They concluded that the renal
tubule adenomas are not relevant to humans because of poor survival rates in control animals in
NTP 2-year drinking water bioassay (NTP, 1995), rat-specific MOA(s), and dose exceeds the MTD.
Response: The SAB-CAAC agreed with EPA's determination of'suggestive evidence of carcinogenic
potential" (See Charge Question 4b), as the database was consistent with this descriptor as
illustrated in EPA's 2005 Cancer Guidelines, based on thyroid follicular cell adenomas in female
mice and thyroid follicular cell adenomas and carcinomas in male mice and renal tubule adenomas
in male rats, although the SAB-CAAC did not reach consensus regarding the MOA(s) by which tert-
butanol caused renal tubule adenomas in male rats. Briefly, an increase in thyroid adenomas was
observed in female mice exposed to tert-butanol via drinking water (primarily at the high dose)
with the incidence of combined adenomas and carcinomas of 2/58, 3/60, 2/59, 9/59 atO, 510,
1,020, and 2,110 mg/kg-d. The incidence of combined thyroid adenomas and carcinomas in male
mice of 1/60, 0/59, 4/59, 2/57 at 0, 510,1,020, and 2,110 mg/kg-d was observed. The incidence of
renal tubule adenomas and carcinomas observed by NTP in male rats was 8/50,13/50,19/50,
13/50 (or observed by Hard etal. (20111 in male rats was 4/50,13/50,18/50,12/50 ) at 0, 90,
200, and 420 mg/kg-d. These thyroid and kidney tumors were statistically significantly increased
by pairwise comparison (Fisher exact test, p < 0.05) and by trend test (Cochran-Armitage trend test,
p < 0.05). Taken together, this evidence supports the descriptor of "suggestive evidence of
carcinogenic potential".
With regards to the comments on thyroid tumors, as discussed above, thyroid tumors were
also observed in male mice. Regarding the assertion that the highest oral dose in the NTP T19951
study exceeded the MTD in mice, EPA's 2005 Cancer Guidelines discuss the determination of an
"excessively high dose" and describe the process as one of expert judgment which requires that
"...adequate data demonstrate that the effects are solely the result of excessive toxicity rather than
carcinogenicity of the tested agent." In the case of thyroid follicular cell adenomas, the study
authors noted that water consumption by exposed female mice was similar to controls and that no
overt toxicity was observed. In addition, the final average body weight reduction in female mice at
the highest dose was 12% fNTP. 19951 and female mice in the high dose group had higher rates of
survival than control animals (see discussion and added text in Sections 1.2.2 and 2.3.1). The final
average body weight reduction in male mice at the highest dose was 5% to 10% (NTP. 1995) and
water consumption by exposed males was similar to controls, but survival was reduced at the
highest dose and the tumor response in male mice was adjusted for early mortality. Thus, there is
no evidence of exceedance of the MTD or that this is the cause of tumor development.
With regards to the comment on renal tubule adenomas and poor survival rates in the
controls, EPA's cancer guidelines fU.S. EPA. 2005al states that "the most relevant historical control
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data come from the same laboratory and the same supplier and are gathered within 2 or 3 years
one way or the other of the study under review; other data should be used only with extreme
caution." Genetic drift in the laboratory strains and differences in pathology examination at
different times and in different laboratories could affect comparability of historical and concurrent
control data. In this case due to the lack of suitable historical control data, it is preferred to use
concurrent controls to determine statistical significance of tumor incidence. Decreased survival in
controls may be due in part to the increased severity of CPN in control animals (see Section 1.2.1).
However, tumor increases were statistically significant in trend testing which accounted for
mortality. With regards to the additional comments on MOA, the etiology of CPN is unknown and
CPN is both a spontaneous and complex disease whose processes are affected by aging and strain
specificity fNIEHS. 20191. Therefore, it is difficult to separate the effects of spontaneously occurring
CPN from those effects on CPN induced by chemical exposure (see response to comments under
Question 4a and discussion in Section 1.2.1.). With regards to the comment related to the MTD, in
the case of renal tubule adenomas, the study authors did not report exposure-related overt toxicity
in male rats or any changes in toxicokinetics at the middle or high doses. Mortality increased with
increasing exposure (p=0.001) over the 2-year exposure period; however increased mortality does
not account for the highest tumor incidence occurring at the middle dose. Furthermore, the tumor
incidence at the high dose in male rats, which had a final body weight reduction of 24% was not
significantly different from controls (see discussion and added text in Section 1.2.1).
Discussion regarding the cancer descriptor for all routes of exposure, the rationale for
deriving the oral slope factor, and the characterization of the cancer risk estimate can be found in
Sections 1.3.2 and 2.3.1, and in response to comments under Charge Questions 4b, 4c, and 4d.
This document is a draft for review purposes only and does not constitute Agency policy.
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APPENDIX F. QUALITY ASSURANCE (QA) FOR THE
IRIS TOXICOLOGICAL REVIEW OF TEAT-BUTYL
ALCOHOL (TERT-BUTANOL)
This assessment was prepared under the auspices of the U.S. Environmental Protection
Agency's (EPA's) Integrated Risk Information System (IRIS) Program. The IRIS Program is housed
within the Office of Research and Development (ORD) in the Center for Public Health and
Environmental Assessment (CPHEA). EPA has an agency-wide quality assurance policy, and that
policy is outlined in the EPA Quality Manual for Environmental Programs (see CIO 2105-P-01-0)
and follows the specifications outlined in EPA Order CIO 2105.0.
As required by CIO 2105.0, ORD maintains a Quality Management Program, which is
documented in an internal Quality Management Plan (QMP). The latest version was developed in
2013 and was developed using Guidance for Developing Quality Systems for Environmental
Programs fOA/G-11. An NCEA/CPHEA-specific QMP was also developed in 2013 as an appendix to
the ORD QMP. Quality Assurance for products developed within CPHEA is managed under the ORD
QMP and applicable appendices.
The IRIS Toxicological Review of tert-Butanol has been designated as Influential Scientific
Information (ISI) and is classified as QA Category A. Category A designations require reporting of all
critical QA activities, including audits. The development of IRIS assessments is done through a
seven-step process. Documentation of this process is available on the IRIS website:
https://www.epa.gOv/iris/basic-information-about~integrated-risk~information-svstem#process.
Specific management of quality assurance within the IRIS Program is documented in a
Programmatic Quality Assurance Project Plan (PQAPP). A PQAPP was developed using the EPA
Guidance for Quality Assurance Project Pla and the latest approved version is dated
March 2020. All IRIS assessments follow the IRIS PQAPP and all assessment leads and team
members are required to receive QA training on the IRIS PQAPP. During assessment development,
additional QAPPs may be applied for quality assurance management They include:
Title
Document Number
Date
Program Quality Assurance
Project Plan (PQAPP) for the
Integrated Risk Information
System (IRIS) Program
L-CPAD-0030729-QP-1-3
March 2020
An Umbrella Quality
Assurance Project Plan
(QAPP) for PBPK Models
B-003740-QP-1-0
Feb 2018
This document is a draft for review purposes only and does not constitute Agency policy.
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Quality Assurance Project Plan
(QAPP) for Enhancements to
Benchmark Dose Software
(BMDS)
B-003742-QP-1-0
Apr 2019
Contractor QAPP 1
B-IRISD-0030538
Contractor QAPP 2
B-IRISD-0030622
During assessment development, this project underwent two quality audits during
assessment development including:
Date
Type of audit
Major findings
Actions taken
August 2019
Technical System
Audit
None
None
June 2018
Technical System
Audit
None
None
During Step 3 of the IRIS Process, IRIS toxicological review was subjected to external
reviews by other federal agency partners including the Executive Offices of the White House.
Comments during these IRIS Process steps are available in the Docket (Docket ID No. EPA-HO-ORD-
2013-11111 on regulations.gov.
During Step 4 of assessment development, the IRIS Toxicological Review of tert-Butanol
underwent public commentfrom May 16, 2016 to Jul 15, 2016. Following this comment period, the
toxicological review underwent external peer review by SAB on June 2017. The peer review report
is available on the SAB website
fhttps://yosemite.epa.gov/sab/sabproductnsf/0/8e4436d62dalfd2d85257e38006a3131!OpenDo
cument&TableRow=2.3#2.]. All public and peer review comments are available in the Docket
(Docket ID No. EPA-HO-ORD-2013-1111) on regulations.gov.
Prior to release (Step 7 of the IRIS Process), the final toxicological review is submitted to
management and QA clearance. During this step the CPHEA QA Director and QA Managers review
the project QA documentation and ensure that EPA QA requirements have been met.
This document is a draft for review purposes only and does not constitute Agency policy.
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This document is a draft for review purposes only and does not constitute Agency policy.
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This document is a draft for review purposes only and does not constitute Agency policy.
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This document is a draft for review purposes only and does not constitute Agency policy.
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Supplemental Information—tert-Butyl Alcohol
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4
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