Abstract
Numerical taxonomy and pattern recognition analysis offer powerful tools that can greatly reduce the information burden of multiple-assay screening programs. These methods can be used to rationally design prescreens, identify assays that have similar chemical response patterns, select reporter assays for chemical response groups, evaluate drug selectivity, and predict a drug's likely mechanism of action. When combined with assays designed to identify lead compounds that have characteristics likely to cause failure at a later and more expensive stage of development, a simple three-stage primary discovery process consisting of a rational prescreen, reporters, and clinical failure assay can reduce the number of required culture wells by more than 20-fold and can eliminate all but 1–2 drugs per 1000 tested as leads for further evaluation and development.