title: Applications of mechanistic data in risk assessment: the past, present, and future.
abstract: Mechanistic data, when available, have long been considered in risk assessment, such as in the development of the nitrate RfD based on effects in a sensitive group (infants). Recent advances in biology and risk assessment methods have led to a tremendous increase in the use of mechanistic data in risk assessment. Toxicokinetic data can improve extrapolation from animals to humans and characterization of human variability. This is done by the development of improved tissue dosimetry, by the use of uncertainty factors based on chemical-specific data, and in the development of physiologically based pharmacokinetic (PBPK) models. The development of the boron RfD illustrates the use of chemical-specific data in the improved choice of uncertainty factors. The draft cancer guidelines of the U.S. Environmental Protection Agency emphasize the use of mode of action data. The first choice under the guidelines is to use a chemical-specific, biologically based dose-response (BBDR) model. In the absence of a BBDR model, mode of action data are used to determine whether low-dose extrapolation is done using a linear or nonlinear (margin of exposure) approach. Considerations involved in evaluating a hypothesized mode of action are illustrated using 1,3-dichloropropene, and use of a BBDR model is illustrated using formaldehyde. Recent developments in molecular biology, including transgenic animals, microarrays, and the characterization of genetic polymorphisms, have significant potential for improving risk assessments, although further methods development is needed. Overall, use of mechanistic data has significant potential for reducing the uncertainty in assessments, while at the same time highlighting the areas of uncertainty.
authors: Toxicology Excellence for Risk Assessment, 1757 Chase Avenue, Cincinnati, Ohio 45223, USA. haber@tera.org
authors: L T
authors: LT
authors: Haber
authors: A
authors: A
authors: Maier
authors: Q
authors: Q
authors: Zhao
authors: J S
authors: JS
authors: Dollarhide
authors: R E
authors: RE
authors: Savage
authors: M L
authors: ML
authors: Dourson
mesh_terms: D000498:Allyl Compounds / Q000032:analysis / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000592:standards; D000818:Animals; D001895:Boron / Q000032:analysis / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000592:standards; D004305:Dose-Response Relationship, Drug; D004781:Environmental Exposure / Q000009:adverse effects / Q000032:analysis / Q000592:standards*; D005544:Forecasting / Q000379:methods*; D005557:Formaldehyde / Q000032:analysis / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000592:standards; D006801:Humans; D006843:Hydrocarbons, Chlorinated; D009566:Nitrates / Q000032:analysis / Q000493:pharmacokinetics* / Q000494:pharmacology* / Q000592:standards; D012016:Reference Values; D018570:Risk Assessment; D012307:Risk Factors; D012680:Sensitivity and Specificity
chemical_list: D000498:Allyl Compounds; D006843:Hydrocarbons, Chlorinated; D009566:Nitrates; D005557:Formaldehyde; C023891:1,3-dichloro-1-propene; D001895:Boron