title: Toxicology Strategies for Drug Discovery: Present and Future.
abstract: Attrition due to nonclinical safety represents a major issue for the productivity of pharmaceutical research and development (R&D) organizations, especially during the compound optimization stages of drug discovery and the early stages of clinical development. Focusing on decreasing nonclinical safety-related attrition is not a new concept, and various approaches have been experimented with over the last two decades. Front-loading testing funnels in Discovery with in vitro toxicity assays designed to rapidly identify unfavorable molecules was the approach adopted by most pharmaceutical R&D organizations a few years ago. However, this approach has also a non-negligible opportunity cost. Hence, significant refinements to the "fail early, fail often" paradigm have been proposed recently to reflect the complexity of accurately categorizing compounds with early data points without taking into account other important contextual aspects, in particular efficacious systemic and tissue exposures. This review provides an overview of toxicology approaches and models that can be used in pharmaceutical Discovery at the series/lead identification and lead optimization stages to guide and inform chemistry efforts, as well as a personal view on how to best use them to meet nonclinical safety-related attrition objectives consistent with a sustainable pharmaceutical R&D model. The scope of this review is limited to small molecules, as large molecules are associated with challenges that are quite different. Finally, a perspective on how several emerging technologies may impact toxicity evaluation is also provided.
authors.affiliation: Global Preclinical Safety, AbbVie Inc. , 1 North Waukegan Road, North Chicago, Illinois 60064, United States.
authors.forename: Eric A G
authors.initials: EA
authors.lastname: Blomme
authors.affiliation: Drug Safety Research and Development, Pfizer , Eastern Point Road, Groton, Connecticut 06340, United States.
authors.forename: Yvonne
authors.initials: Y
authors.lastname: Will
mesh_terms: D000818:Animals; D019295:Computational Biology / Q000379:methods; D003198:Computer Simulation; D055808:Drug Discovery / Q000379:methods*; D064420:Drug-Related Side Effects and Adverse Reactions / Q000175:diagnosis / Q000378:metabolism; D057166:High-Throughput Screening Assays / Q000379:methods; D006801:Humans; D008954:Models, Biological; D004364:Pharmaceutical Preparations / Q000737:chemistry / Q000378:metabolism; D011506:Proteins / Q000378:metabolism; D018675:Toxicity Tests / Q000379:methods*
chemical_list: D004364:Pharmaceutical Preparations; D011506:Proteins