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EVALUATION OF BIOLOGICALLY BASED DOSE-RESPONSE MODELING FOR DEVELOPMENTAL TOXICITY: A WORKSHOP REPORT
Citation:
Lau, C S., M. E. Andersen, D. J. CrawfordBrown, R J. Kavlock, C. A. Kimmel, T. B. Knudsen, K. Muneoka, J M. Rogers, R W. Setzer, G. Smith, AND R. Tyl. EVALUATION OF BIOLOGICALLY BASED DOSE-RESPONSE MODELING FOR DEVELOPMENTAL TOXICITY: A WORKSHOP REPORT. REGULATORY TOXICOLOGY AND PHARMACOLOGY 31(2):190-199, (2000).
Description:
Evaluation of biologically based dose-response modeling for developmental toxicity: a workshop report.
Lau C, Andersen ME, Crawford-Brown DJ, Kavlock RJ, Kimmel CA, Knudsen TB, Muneoka K, Rogers JM, Setzer RW, Smith G, Tyl R.
Reproductive Toxicology Division, NHEERL, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina 27711, USA.
Biologically based dose-response (BBDR) modeling represents a novel approach for quantitative assessment of health risk by incorporating pharmacokinetic and pharmacodynamic characteristics of a chemical and by relating the immediate cellular responses to a cascade of aberrant biological actions that leads to detectable adverse outcomes. The quantitative relationship of each 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 of 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 laboratories, biomathematical modelers, and risk assessment scientists was convened in a workshop to evaluate the approaches undertaken by the EPA team and to discuss the future prospects of BBDR modeling. This report summarizes the 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 confidence of the model is directly proportional to our current understanding of basic biology and can be enhanced only through the ongoing novel discoveries. More importantly, the extent of "uncertainty" (inherent with the default assumptions associated with the NOAEL or benchmark approach) reducible by BBDR modeling requires further scrutiny and comparison.
Publication Types:
Congresses
PMID: 10854125 [PubMed - indexed for MEDLINE]