A statistical-heuristic method for automated selection of drugs for screening

Abstract

A statistical-heuristic method for selecting [antineoplastic] drugs for animal screening is developed with molecular structure features as predictors of biological activity. The method is intended to work on large amounts of data over varied structures. A trial of this method on a small data set allows some comparison with more sophisticated pattern recognition methods. Problems connected with interdependence among structure predictors are critical in this method and schemes to eliminate redundancy are reviewed. Alternate sets of structure predictors are considered. The discussion here outlines directions to be taken in the near future.