METAPRINT, a metabolic fingerprint, has been developed by predicting metabolic pathways and corresponding potential metabolites. Calculated drug-likeness parameters (log P and MW) have been incorporated into METAPRINT to allow the encoding of metabolic diversity within a chemical library. The application of METAPRINT in the design of cassette dosing experiments is demonstrated using a library of alpha-1a antagonists synthesized at Glaxo Wellcome. Results obtained by Ward's clustering algorithm suggest that METAPRINTs are able to discriminate between low- and high-clearance compounds. Cassette design was performed by maximizing the intracassette Euclidean distances between compounds in METAPRINT space, using simulated annealing. Calculated distances in METAPRINT space were in accordance with experimental data.