1. The opportunities of mining historical and collective data in drug discovery.
- Author
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Wassermann AM, Lounkine E, Davies JW, Glick M, and Camargo LM
- Subjects
- Animals, Computer Simulation, Drug Discovery history, History, 21st Century, Humans, Models, Molecular, Molecular Structure, Signal Transduction drug effects, Structure-Activity Relationship, Data Mining history, Databases, Chemical history, Databases, Pharmaceutical history, Drug Discovery methods, Pharmaceutical Preparations chemistry
- Abstract
Vast amounts of bioactivity data have been generated for small molecules across public and corporate domains. Biological signatures, either derived from systematic profiling efforts or from existing historical assay data, have been successfully employed for small molecule mechanism-of-action elucidation, drug repositioning, hit expansion and screening subset design. This article reviews different types of biological descriptors and applications, and we demonstrate how biological data can outlive the original purpose or project for which it was generated. By comparing 150 HTS campaigns run at Novartis over the past decade on the basis of their active and inactive chemical matter, we highlight the opportunities and challenges associated with cross-project learning in drug discovery., (Copyright © 2014 Elsevier Ltd. All rights reserved.)
- Published
- 2015
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