Statistical Design of Pools Using Optimal Coverage and Minimal Collision

Discovery of a new drug involves screening large chemical libraries to identify active compounds. Screening efficiency can be improved by testing compounds in pools. We consider two criteria to design pools: optimal coverage of the chemical space and minimal collision between compounds. Five pooling designs are applied to a public data set. We evaluate each method by determining how well the design criteria are met. One design uniformly dominates all other designs, but all criteria-designed pools outperform randomly created pools. Furthermore, we discuss blocking and synergism between compounds as other effects that must be investigated when performing pooling experiments.