Determination of a chemical’s mode of action
is the key step for:
·
Determining human relevance of tumors
·
Determining whether to use linear or nonlinear low-dose
extrapolation for cancer assessment.
·
Replacing default uncertainty factors (UFs) with chemical-specific
adjustment factors (CSAFs).
Addressing these questions requires consideration of many
issues:
·
How much data is enough to meet EPA’s criteria for identifying a
mode of action? What studies are needed to address EPA’s framework?
·
How can data be used to move away from default approaches, and
what are the implications for risk assessment?
·
What is the impact of genetic polymorphisms on total human
variability?
TERA scientists have frequently addressed these
questions, along with determining the human relevance of tumors and whether to
use linear or nonlinear low-dose extrapolation for cancer assessment. In
addition, we have evaluated replacing default uncertainty factors (UFs) with
chemical-specific adjustment factors (CSAFs).
TERA has addressed cancer mode of action for a
number of assessments for EPA, state, and private sponsors, including the
chloroform risk characterization,
soluble nickel salts, tetrahydrofuran, and C8 (ammonium
perfluoroctanoate). TERA facilitated the
peer review of captan carcinogenicity, for which the panel determined
that cancer observed in laboratory animals was due to a nongenotoxic MOA; captan
is weakly genotoxic in vitro, but not in vivo. Based on our
understanding of both risk assessment methods and molecular toxicology, we have
assisted laboratory researchers by evaluating a chemical’s overall database in
order to identify key studies needed to resolve MOA issues. A
collaboration among TERA,
NCTR, and Environ has been established to to enhance the use of mutagenicity
data for informing the mode of action analysis for cancer risk assessment, by
investigating a new approach to quantitatively compare in vivo mutation
data with tumor data.
TERA participated in an
IPCS-led effort to develop
guidelines for the development of CSAFs. We have applied those
guidelines in a number of projects. For example, we used PBPK modeling and
Monte Carlo analysis (in collaboration with Environ) to evaluate the impact on
tissue dose of polymorphisms in genes for metabolic enzymes
(Haber et al., 2002;
Gentry et al., 2002). These data were used to calculate CSAFs under
a variety of proposed alternative definitions. We have developed and presented
courses in the use of CSAFs in risk assessment, and in using the EPA
framework to apply MOA data for cancer risk assessment.
·
Naumann, B., B. Meek, M.L. Dourson, and E.
Ohanian. 2005.
The Future of Chemical Specific Adjustment Factors in Risk Assessment. Risk
Policy Report.
12(31): 14.
·
Haber, L.T., A. Maier, Q. Zhao, J.S. Dollarhide, R.E. Savage and
M.L. Dourson. 2001
Applications of Mechanistic Data in Risk Assessment -- The Past, Present, and
Future. Toxicological Sciences. 61(1): 32-39.
·
Lipscomb, J. C., M. Meek, K. Krishnan, G.L. Kedderis, H. Clewell
and L.T. Haber. 2004.
Incorporation of Pharmacokinetic and Pharmacodynamic Data into Risk Assessments.
Toxicol. Mech. Methods. 14:145-158.
·
Zhao, Q., J. Unrine and M. Dourson. 1999.
Replacing the Default Values of 10 With Data-Derived Values: A Comparison of Two
Different Data Derived Uncertainty Factors for Boron. Human and Ecological
Risk Assessment. 5(5): 973-983.
·
Dourson, M.L., A. Maier, B. Meek, A. Renwick, E. Ohanian and K.
Poirier. 1998.
Re-evaluation of toxicokinetics for data-derived uncertainty factors. Biol.
Trace Element Res. 66: 453-463.
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