Practical considerations on the use of predictive models for regulatory purposes

Interest in the use of quantitative structure-activity relationships (QSARs) for regulatory purposes has been growing steadily over the years, and many models have been evaluated under the guidance and acceptability criteria defined at the Setubal workshop held in March 2002. This work explores some of the practical issues related to the use of QSARs for regulatory purposes using results obtained from rat oral lethality and fish acute toxicity estimates generated from computational models (including TOPKAT, MCASE, OASIS, and ECOSAR). Using data submitted under the Environmental Protection Agency's (EPA's) High Production Volume (HPV) Challenge Program, the results on the quality of the estimations are compared using a standard statistical review and an additional classification approach in which the hazard predictions were grouped using well-defined regulatory criteria (those used in EPA's New Chemical Program). Our results indicate that an evaluation of a model's regulatory applicability and predictive power is ultimately dependent on the specific criteria used in the assessment process. This work also discusses the practical difficulties associated with defining the domain of a predictive model using the estimates of four different ready biodegradation models and experimental data submitted under the EPA's New Chemical program. Our results suggest that the method a model employs for its predictions is as important as the training set in determining its domain of applicability. Together, these results highlight the challenges associated with developing reliable and easily applied acceptability criteria for the regulatory use of QSAR models.