A unified approach to computational drug discovery. Issue 11 (November 2015)

• Record Type: Journal Article
• Authors: Tseng, Chih-Yuan; Tuszynski, Jack
• Is Part Of: Drug discovery today. Volume 20:Issue 11(2015)
• Page Start: 1328
• Page End: 1336
• Publication Date: 2015-11
• Subjects: Drugs -- Design -- Periodicals; Drugs -- Research -- Periodicals; 615.1
• DOI: 10.1016/j.drudis.2015.07.004
• Languages: English
• ISSNs: 1359-6446

Abstract

Highlights: Current strategies for drug discovery are reviewed. We propose that drugs can be better discovered through a unified approach. Examples from different discovery stages demonstrate the use of the unified approach. Abstract : It has been reported that a slowdown in the development of new medical therapies is affecting clinical outcomes. The FDA has thus initiated the Critical Path Initiative project investigating better approaches. We review the current strategies in drug discovery and focus on the advantages of the maximum entropy method being introduced in this area. The maximum entropy principle is derived from statistical thermodynamics and has been demonstrated to be an inductive inference tool. We propose a unified method to drug discovery that hinges on robust information processing using entropic inductive inference. Increasingly, applications of maximum entropy in drug discovery employ this unified approach and demonstrate the usefulness of the concept in the area of pharmaceutical sciences. Abstract : Entropic inductive inference is the foundation of an information-based unified approach to computational drug discovery.