Evaluation of the use of static and dynamic models to predict drug-drug interaction and its associated variability: impact on drug discovery and early development

Drug Metabolism and Disposition : the Biological Fate of Chemicals
Sheila Annie PetersH Dolgos

Abstract

Simcyp, a population-based simulator, is widely used for evaluating drug-drug interaction (DDI) risks in healthy and disease populations. We compare the prediction performance of Simcyp with that of mechanistic static models using different types of inhibitor concentrations, with the aim of understanding their strengths/weaknesses and recommending the optimal use of tools in drug discovery/early development. The inclusion of an additional term in static equations to consider the contribution of hepatic first pass to DDIs (AUCR(hfp)) has also been examined. A second objective was to assess Simcyp's estimation of variability associated with DDIs. The data set used for the analysis comprises 19 clinical interactions from 11 proprietary compounds. Except for gut interaction parameters, all other input data were identical for Simcyp and static models. Static equations using an unbound average steady-state systemic inhibitor concentration (I(sys)) and a fixed fraction of gut extraction and neglecting gut extraction in the case of induction interactions performed better than Simcyp (84% compared with 58% of the interactions predicted within 2-fold). Differences in the prediction outcomes between the static and dynamic models are attri...Continue Reading

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Citations

Jan 22, 2013·Expert Opinion on Drug Metabolism & Toxicology·Hugh A BartonManthena V Varma
Dec 30, 2014·Biopharmaceutics & Drug Disposition·Manthena V VarmaPing Zhao
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Jul 17, 2015·Drug Metabolism and Disposition : the Biological Fate of Chemicals·Shinji YamazakiBill J Smith
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Apr 12, 2021·Clinical Pharmacokinetics·Marie-Emilie WilleminJan Snoeys
Apr 3, 2018·Molecular Pharmaceutics·Jaydeep YadavSwati Nagar

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