Simultaneous Ivabradine Parent-Metabolite PBPK/PD Modelling Using a Bayesian Estimation Method
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Research Article Simultaneous Ivabradine Parent-Metabolite PBPK/PD Modelling Using a Bayesian Estimation Method Jennifer Lang,1 Ludwig Vincent,2 Marylore Chenel,3 Kayode Ogungbenro,1 and Aleksandra Galetin1,4
Received 26 June 2020; accepted 18 August 2020 Abstract.
Ivabradine and its metabolite both demonstrate heart rate–reducing effect (If current inhibitors) and undergo CYP3A4 metabolism. The purpose of this study was to develop a joint parent-metabolite physiologically based pharmacokinetic (PBPK)/pharmacodynamic (PD) model to predict the PK and PD of ivabradine and its metabolite following intravenous (i.v.) or oral administration (alone or co-administered with CYP3A4 inhibitors). Firstly, a parent-metabolite disposition model was developed and optimised using individual plasma concentration-time data following i.v. administration of ivabradine or metabolite within a Bayesian framework. Secondly, the model was extended and combined with a mechanistic intestinal model to account for oral absorption and drug-drug interactions (DDIs) with CYP3A4 inhibitors (ketoconazole, grapefruit juice). Lastly, a PD model was linked to the PBPK model to relate parent and metabolite PK to heart rate (HR) reduction. The disposition model described successfully parent-metabolite PK following i.v. administration. Following integration of a gut model, the PBPK model adequately predicted plasma concentration profiles and the DDI risk (92% and 85% of predicted AUC+inhibitor/AUCcontrol and Cmax+inhibitor/Cmaxcontrol for ivabradine and metabolite within the prediction limits). Ivabradine-metabolite PBPK model was linked to PD by using the simulated unbound parent-metabolite concentrations in the heart. This approach successfully predicted the effects of both entities on HR (observed vs predicted − 7.7/− 5.9 bpm and − 15.8/− 14.0 bpm, control and ketoconazole group, respectively). This study provides a framework for PBPK/ PD modelling of a parent-metabolite and can be scaled to other populations or used for investigation of untested scenarios (e.g. evaluation of DDI risk in special populations). KEY WORDS: Bayesian analysis; drug-drug interactions; ivabradine; parent-metabolite; physiologically based pharmacokinetic modelling.
INTRODUCTION For the last decades, physiologically based pharmacokinetic (PBPK) modelling has been widely applied as an in silico tool to predict drug disposition by integrating physiological parameters (e.g. blood flows, tissue volumes) and drug-specific information (e.g. physicochemical properties, Electronic supplementary material The online version of this article (https://doi.org/10.1208/s12248-020-00502-8) contains supplementary material, which is available to authorized users. 1
Centre for Applied Pharmacokinetic Research, Division of Pharmacy and Optometry, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PT, UK. 2 Centre de Pharmacocinétique et Métabolisme, Technologie Servier, Orléans, France. 3 Clinical Pharmacokinetics and Pharmacometrics,
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