Literature DB >> 31506301

Systematic Development and Verification of a Physiologically Based Pharmacokinetic Model of Rivaroxaban.

Eleanor Jing Yi Cheong1, Denise Wun Xi Teo1, Denise Xin Yi Chua1, Eric Chun Yong Chan2.   

Abstract

Rivaroxaban is indicated for stroke prevention in nonvalvular atrial fibrillation (AF). Its elimination is mediated by both hepatic metabolism and renal excretion. Consequently, its clearance is susceptible to both intrinsic (pathophysiological) and extrinsic (concomitant drugs) variabilities that in turn implicate bleeding risks. Upon systematic model verification, physiologically based pharmacokinetic (PBPK) models are qualified for the quantitative rationalization of complex drug-drug-disease interactions (DDDIs). Hence, this study aimed to develop and verify a PBPK model of rivaroxaban systematically. Key parameters required to define rivaroxaban's disposition were either obtained from in vivo data or generated via in vitro metabolism and transport kinetic assays. Our developed PBPK model successfully predicted rivaroxaban's clinical pharmacokinetic parameters within predefined success metrics. Consideration of basolateral organic anion transporter 3 (OAT3)-mediated proximal tubular uptake in tandem with apical P-glycoprotein (P-gp)-mediated efflux facilitated mechanistic characterization of the renal elimination of rivaroxaban in both healthy and renal impaired patients. Retrospective drug-drug interaction (DDI) simulations, incorporating in vitro metabolic inhibitory parameters, accurately recapitulated clinically observed attenuation of rivaroxaban's hepatic clearance due to enzyme-mediated DDIs with CYP3A4/2J2 inhibitors (verapamil and ketoconazole). Notably, transporter-mediated DDI simulations between rivaroxaban and the P-gp inhibitor ketoconazole yielded minimal increases in rivaroxaban's systemic exposure when P-gp-mediated efflux was solely inhibited, but were successfully characterized when concomitant basolateral uptake inhibition was incorporated in the simulation. In conclusion, our developed PBPK model of rivaroxaban is systematically verified for prospective interrogation and management of untested yet clinically relevant DDDIs pertinent to AF management using rivaroxaban. SIGNIFICANCE STATEMENT: Rivaroxaban is susceptible to DDDIs comprising renal impairment and P-gp and CYP3A4/2J2 inhibition. Here, systematic construction and verification of a PBPK model of rivaroxaban, with the inclusion of a mechanistic kidney component, provided insight into the previously arcane role of OAT3-mediated basolateral uptake in influencing both clinically observed renal elimination of rivaroxaban and differential extents of transporter-mediated DDIs. The verified model holds potential for investigating clinically relevant DDDIs involving rivaroxaban and designing dosing adjustments to optimize its pharmacotherapy in atrial fibrillation.
Copyright © 2019 by The American Society for Pharmacology and Experimental Therapeutics.

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Year:  2019        PMID: 31506301     DOI: 10.1124/dmd.119.086918

Source DB:  PubMed          Journal:  Drug Metab Dispos        ISSN: 0090-9556            Impact factor:   3.922


  5 in total

1.  Mechanistic PBPK Modeling of Urine pH Effect on Renal and Systemic Disposition of Methamphetamine and Amphetamine.

Authors:  Weize Huang; Lindsay C Czuba; Nina Isoherranen
Journal:  J Pharmacol Exp Ther       Date:  2020-03-20       Impact factor: 4.030

2.  Physiologically-Based Pharmacokinetic Modeling for the Prediction of a Drug-Drug Interaction of Combined Effects on P-glycoprotein and Cytochrome P450 3A.

Authors:  Yukio Otsuka; Mary P Choules; Peter L Bonate; Kanji Komatsu
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2020-11-12

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Authors:  Ziteng Wang; Eric Chun Yong Chan
Journal:  Clin Pharmacol Ther       Date:  2022-07-04       Impact factor: 6.903

4.  Risk assessment and molecular mechanism study of drug-drug interactions between rivaroxaban and tyrosine kinase inhibitors mediated by CYP2J2/3A4 and BCRP/P-gp.

Authors:  Tingting Zhao; Xuening Li; Yanwei Chen; Jie Du; Xiaodong Chen; Dalong Wang; Liyan Wang; Shan Zhao; Changyuan Wang; Qiang Meng; Huijun Sun; Kexin Liu; Jingjing Wu
Journal:  Front Pharmacol       Date:  2022-08-22       Impact factor: 5.988

5.  P-Glycoprotein Aggravates Blood Brain Barrier Dysfunction in Experimental Ischemic Stroke by Inhibiting Endothelial Autophagy.

Authors:  Liangliang Huang; Yan Chen; Rui Liu; Binbin Li; Xuan Fei; Xiang Li; Ge Liu; Yunman Li; Baohui Xu; Weirong Fang
Journal:  Aging Dis       Date:  2022-10-01       Impact factor: 9.968

  5 in total

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