Applying data mining techniques to library design, lead generation and lead optimization.
Many data mining techniques have been applied to activity and ADMET datasets and the resulting models are being used to understand quantitative structure-activity relationships and design new libraries. This review summarizes data mining concepts and discuss their application to library design, lead generation (particularly for sequential screening) and lead optimization (specifically for generating and interpreting QSAR models). Also, this review discusses recent comparative studies between data mining techniques and draws some conclusions about the patterns emerging in the drug discovery data mining field.
Weaver
Daniel C
DC
Array Biopharma, Inc., 3200 Walnut Street, Boulder, Colorado 80303, USA. dweaver@arraybiopharma.com
D000465:Algorithms; D016208:Databases, Factual; D015195:Drug Design; D016247:Information Storage and Retrieval / Q000379:methods*; D007990:Libraries / Q000639:trends*; D008492:Medical Informatics Computing / Q000706:statistics & numerical data / Q000639:trends*; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis; D012984:Software