Statistical Design of Pools Using Optimal Coverage and Minimal Collision

Abstract

Discovery of a new drug involves screening large chemical libraries to identify new and diverse active compounds. Screening efficiency can be improved by testing compounds in pools. We consider two criteria for designing pools: optimal coverage of the chemical space and minimal collision between compounds. We apply four pooling designs to a public dataset. We evaluate each method by determining how well the design criteria are met and whether the methods are able to find many diverse active compounds. One pooling design emerges as a winner, but all designed pools clearly outperform randomly created pools.

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