title: A unified approach to computational drug discovery.
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.
authors.affiliation: Department of Oncology, University of Alberta, Edmonton, AB T6G 1Z2, Canada; MDT Canada, Edmonton, AB, Canada. Electronic address: chih-yuan.tseng@ualbeta.ca.
authors.forename: Chih-Yuan
authors.initials: CY
authors.lastname: Tseng
authors.affiliation: Department of Oncology, University of Alberta, Edmonton, AB T6G 1Z2, Canada; Department of Physics, University of Alberta, Edmonton, AB T6G 1Z2, Canada.
authors.forename: Jack
authors.initials: J
authors.lastname: Tuszynski
mesh_terms: D015195:Drug Design; D055808:Drug Discovery / Q000379:methods*; D019277:Entropy; D006801:Humans; D013816:Thermodynamics; D014481:United States; D014486:United States Food and Drug Administration