THE CHALLENGE OF MECHANISM-BASED MODELING IN RISK ASSESSMENT FOR NEUROBEHAVIORAL END-POINTS

The mathematical form for a dose-time-response model is ideally not ju st a convenience for summarizing or fitting a particular data set-it r epresents a hypothesis. The more this hypothesis reflects a mechanisti cally sophisticated view of the likely reality, the more it can lead t o potentially informative validating or invalidating types of predicti ons about the results of real experiments and (in the long run) reason ably credible predictions outside the range of direct observations. Th is paper first reviews some distinctive features of the nervous system and neurotoxic responses and theoretically explores some basic quanti tative implications of these features. Relationships are derived for h ow dose-response relationships for the inhibition of function should d epend on the numbers of neurons in series or redundant parallel arrang ements that are required or capable of performing the function. Previo us work is reviewed in which some less nervous-system-specific feature s were the foci of quantitative risk-assessment modeling for specific neurotoxic end points. These include a) rates of repair of putatively reversible damage in the case of acrylamide; b) human interindividual variability in susceptibility to fetal/developmental effects in the ca se of methylmercury; and c) opportunities to use intermediate biomarke rs to assist in integrated animal toxicological and epidemiologic inve stigations of the chronic cumulative risks posed by agents that contri bute to neuronal loss with increasing age and pathology.