With high-throughput screening systems in place and beginning to produce data reliably, the data analysis and interpretation becomes a bottleneck in the process of moving more high-quality leads to the clinic. The decision-making processes that go into lead discovery, evaluation, and development are quite complex, and can benefit from judicious use of appropriate computational intelligence techniques. Knowledge-based reasoning systems that capture the decision process of a pharmaceutical chemist during lead identification and development and aid in decision support will be presented in this talk. Bioreason's HTS data interpretation systems are an example of an automated solution aimed at helping identify top quality lead candidates while minimizing costly mistakes. The fundamental aspects of technology for combining computational intelligence techniques with knowledge discovery from data mining to this end will be presented.
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|Author: Susan Hruska|
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