Drug Discovery Today

Presented at the October 7th, 1999 meeting of the LRIG Mid Atlantic

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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Table of Contents

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Drug Discovery Today

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Questions

HTS Data Analysis Bottlenecks

What is Needed?

How Can AI Help?

Goals

What Can the Data Tell You?

What Can the Neural Net Tell You?

Beyond Similarity Clustering

LeadPharmer™ Strategy

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Some of the Underlying Technology

Self-Organizing Maps

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Classification

Beyond 2D

Also in the Go/No-Go Arena

Collaborative AI-based Solutions

Collaborative AI-based Solutions

Our People

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Author: Susan Hruska

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