One of the current major bottlenecks in drug discovery is in vivo testing of candidate drugs in behavioral paradigms in normal or genetically altered mice. This testing is essential in discovering gene function and predicting potential efficacy of CNS drugs in humans. New efforts in the biotech community aim to alleviate this bottleneck by developing higher-throughput systems of behavioral, neurological and physiological analyses. Together with large pharmacological databases, equipped with state-of-the-art bioinformatic and/or data-mining algorithms, these systems will provide rapid and accurate indices of the therapeutic potential of novel drugs. By providing a substantial increase in the speed of behavioral testing, new high-throughput systems will facilitate current behavioral research with faster, more reliable approaches. Furthermore, screening whole drug-libraries and comparing the profiles of novel compounds to those of known compounds will facilitate the discovery of novel drugs. Target validation will also become more efficient with the fast characterization of novel mutant mice.