Evaluation of biologically based dose-response modeling for developmental toxicity: A workshop report

Citation
C. Lau et al., Evaluation of biologically based dose-response modeling for developmental toxicity: A workshop report, REGUL TOX P, 31(2), 2000, pp. 190-199
Citations number
28
Categorie Soggetti
Pharmacology & Toxicology
Journal title
REGULATORY TOXICOLOGY AND PHARMACOLOGY
ISSN journal
02732300 → ACNP
Volume
31
Issue
2
Year of publication
2000
Part
1
Pages
190 - 199
Database
ISI
SICI code
0273-2300(200004)31:2<190:EOBBDM>2.0.ZU;2-U
Abstract
Biologically based dose-response (BBDR) modeling represents a novel approac h for quantitative assessment of health risk by incorporating pharmacokinet ic and pharmacodynamic characteristics of a chemical and by relating the im mediate cellular responses to a cascade of aberrant biological actions that leads to detectable adverse outcomes. The quantitative relationship of eac h of the intervening events can be described in mathematical forms that are amenable for adjustment and extrapolation over a range of doses and across species. A team of investigators at the Reproductive Toxicology Division o f the U.S. Environmental Protection Agency has explored the feasibility of BBDR modeling by examining the developmental toxicity of a known teratogen, 5-fluorouracil. A panel of researchers from academic and industrial labora tories, biomathematical modelers, and risk assessment scientists was conven ed in a workshop to evaluate the approaches undertaken by the EPA team and to discuss the future prospects of BBDR modeling. This report summarizes th e lessons learned from one approach to BBDR modeling and comments from the panelists: while it is possible to incorporate mechanistic information into quantitative dose-response models for the assessment of health risks, the process is enormously data-intensive and costly; in addition, the confidenc e of the model is directly proportional to our current understanding of bas ic biology and can be enhanced only through the ongoing novel discoveries. More importantly, the extent of "uncertainty" (inherent with the default as sumptions associated with the NOAEL or benchmark approach) reducible by BBD R modeling requires further scrutiny and comparison. (C) 2000 Academic Pres s.