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 just a convenience for summarizing or fitting a particular data set--it represents a hypothesis. The more this hypothesis reflects a mechanistically sophisticated view of the likely reality, the more it can lead to potentially informative validating or invalidating types of predictions about the results of real experiments and (in the long run) reasonably credible predictions outside the range of direct observations. This paper first reviews some distinctive features of the nervous system and neurotoxic responses and theoretically explores some basic quantitative implications of these features. Relationships are derived for how dose-response relationships for the inhibition of function should depend on the numbers of neurons in series or redundant parallel arrangements that are required or capable of performing the function. Previous work is reviewed in which some less nervous-system-specific features 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 case of methylmercury; and c) opportunities to use intermediate biomarkers to assist in integrated animal toxicological and epidemiologic investigations of the chronic cumulative risks posed by agents that contribute to neuronal loss with increasing age and pathology.