A randomization test-based method for risk assessment in neurotoxicology

A current trend in risk assessment for systemic toxicity (noncancer) endpoi nts is to utilize the observable range of the dose-effect curve in order to estimate the likelihood of obtaining effects at lower concentrations. Meth ods to accomplish this endeavor are typically based on variability in eithe r the effects of fixed doses (benchmark approaches), or on variability in t he doses producing a Axed effect (probabilistic or tolerance-distribution a pproaches). The latter method may be particularly desirable because it can be used to determine variability in the effect of an agent in a population, which is an important goal of risk assessment. This method of analysis, ho wever, has typically been accomplished using dose-effect data from individu al subjects, which can be impractical in toxicology. A new method is theref ore presented that can use traditional groups-design data to generate a set of dose-effect functions. Population tolerances for a specific effect can then be estimated from these model dose-effect functions. It is based on th e randomization test. which assesses the generality of a data set by compar ing it to a data set constructed from randomized combinations of single poi nt estimates. The present article describes an iterative line-fitting progr am that generates such a data set and then uses it to provide risk assessme nts for two pesticides, triadimefon and carbaryl. The effects of these pest icides were studied on the locomotor activity of laboratory rats, a common neurobehavioral end point. Triadimefon produced dose-dependent increases in activity, while carbaryl produced dose-dependent decreases in activity. Ri sk figures derived from the empirical distribution of individual dose-effec t functions were compared to those from the iterative line-fitting program. The results indicate that the method generates comparable risk figures, al though potential limitations are also described.