Advanced biological information such as computational biology, in vitro transformation assays, genome pathway analysis, genotoxicity assays, proteomics, gene expression, cell signaling disruption and hormone receptors offer the poten- tial for significant improvements in the ability of regulatory agencies to consider the risks of the thousands of compounds—and mixtures of compounds—currently unexamined. While the science for performing the assays underlying such information is developing rapidly, there is significantly less understanding of the rationality of using these data in specific decision problems. This paper explores these issues of rationality, identifying the issues of rationality that remain to be developed for applications in regulatory risk assessment, and providing a draft decision framework for these applications. The conclusion is that these rapid, high throughput methods hold the potential to significantly improve the protection of public health through better understanding of risks from compounds and mixtures, but incorporating them into existing risk assessment methodologies requires improvements in understanding the reliability and rates of Type I and Type II errors for specific applications.