| Literature DB >> 27052879 |
Tonika Bohnert1, Aarti Patel2, Ian Templeton2, Yuan Chen2, Chuang Lu2, George Lai2, Louis Leung2, Susanna Tse2, Heidi J Einolf2, Ying-Hong Wang2, Michael Sinz2, Ralph Stearns2, Robert Walsky2, Wanping Geng2, Sirimas Sudsakorn2, David Moore2, Ling He2, Jan Wahlstrom2, Jim Keirns2, Rangaraj Narayanan2, Dieter Lang2, Xiaoqing Yang2.
Abstract
Under the guidance of the International Consortium for Innovation and Quality in Pharmaceutical Development (IQ), scientists from 20 pharmaceutical companies formed a Victim Drug-Drug Interactions Working Group. This working group has conducted a review of the literature and the practices of each company on the approaches to clearance pathway identification (fCL), estimation of fractional contribution of metabolizing enzyme toward metabolism (fm), along with modeling and simulation-aided strategy in predicting the victim drug-drug interaction (DDI) liability due to modulation of drug metabolizing enzymes. Presented in this perspective are the recommendations from this working group on: 1) strategic and experimental approaches to identify fCL and fm, 2) whether those assessments may be quantitative for certain enzymes (e.g., cytochrome P450, P450, and limited uridine diphosphoglucuronosyltransferase, UGT enzymes) or qualitative (for most of other drug metabolism enzymes), and the impact due to the lack of quantitative information on the latter. Multiple decision trees are presented with stepwise approaches to identify specific enzymes that are involved in the metabolism of a given drug and to aid the prediction and risk assessment of drug as a victim in DDI. Modeling and simulation approaches are also discussed to better predict DDI risk in humans. Variability and parameter sensitivity analysis were emphasized when applying modeling and simulation to capture the differences within the population used and to characterize the parameters that have the most influence on the prediction outcome.Entities:
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Year: 2016 PMID: 27052879 DOI: 10.1124/dmd.115.069096
Source DB: PubMed Journal: Drug Metab Dispos ISSN: 0090-9556 Impact factor: 3.922