Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction
As rifampicin can cause the induction and inhibition of multiple metabolizing enzymes and transporters, it has been challenging to accurately predict the complex drug–drug interactions (DDIs). We previously constructed a physiologically‐based pharmacokinetic (PBPK) model of rifampicin accounting for...
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doaj-6cea19c6dad64068b889793b645b8a6f2020-11-25T03:25:20ZengWileyCPT: Pharmacometrics & Systems Pharmacology2163-83062019-11-0181184585710.1002/psp4.12457Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B InductionRyuta Asaumi0Karsten Menzel1Wooin Lee2Ken‐ichi Nunoya3Haruo Imawaka4Hiroyuki Kusuhara5Yuichi Sugiyama6Pharmacokinetic Research Laboratories Ono Pharmaceutical Co., Ltd. Tsukuba JapanMerck & Co., Inc. Kenilworth New Jersey USACollege of Pharmacy and Research Institute of Pharmaceutical Sciences Seoul National University Seoul KoreaPharmacokinetic Research Laboratories Ono Pharmaceutical Co., Ltd. Tsukuba JapanPharmacokinetic Research Laboratories Ono Pharmaceutical Co., Ltd. Tsukuba JapanLaboratory of Molecular Pharmacokinetics Graduate School of Pharmaceutical Sciences The University of Tokyo Tokyo JapanSugiyama Laboratory RIKEN Baton Zone Program RIKEN Cluster for Science, Technology and Innovation Hub RIKEN Yokohama JapanAs rifampicin can cause the induction and inhibition of multiple metabolizing enzymes and transporters, it has been challenging to accurately predict the complex drug–drug interactions (DDIs). We previously constructed a physiologically‐based pharmacokinetic (PBPK) model of rifampicin accounting for the components for the induction of cytochrome P450 (CYP) 3A/CYP2C9 and the inhibition of organic anion transporting polypeptide 1B (OATP1B). This study aimed to expand and verify the PBPK model for rifampicin by incorporating additional components for the induction of OATP1B and CYP2C8 and the inhibition of multidrug resistance protein 2. The established PBPK model was capable of accurately predicting complex rifampicin‐induced alterations in the profiles of glibenclamide, repaglinide, and coproporphyrin I (an endogenous biomarker of OATP1B activities) with various dosing regimens. Our comprehensive rifampicin PBPK model may enable quantitative prediction of DDIs across diverse potential victim drugs and endogenous biomarkers handled by multiple metabolizing enzymes and transporters.https://doi.org/10.1002/psp4.12457 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ryuta Asaumi Karsten Menzel Wooin Lee Ken‐ichi Nunoya Haruo Imawaka Hiroyuki Kusuhara Yuichi Sugiyama |
spellingShingle |
Ryuta Asaumi Karsten Menzel Wooin Lee Ken‐ichi Nunoya Haruo Imawaka Hiroyuki Kusuhara Yuichi Sugiyama Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction CPT: Pharmacometrics & Systems Pharmacology |
author_facet |
Ryuta Asaumi Karsten Menzel Wooin Lee Ken‐ichi Nunoya Haruo Imawaka Hiroyuki Kusuhara Yuichi Sugiyama |
author_sort |
Ryuta Asaumi |
title |
Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction |
title_short |
Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction |
title_full |
Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction |
title_fullStr |
Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction |
title_full_unstemmed |
Expanded Physiologically‐Based Pharmacokinetic Model of Rifampicin for Predicting Interactions With Drugs and an Endogenous Biomarker via Complex Mechanisms Including Organic Anion Transporting Polypeptide 1B Induction |
title_sort |
expanded physiologically‐based pharmacokinetic model of rifampicin for predicting interactions with drugs and an endogenous biomarker via complex mechanisms including organic anion transporting polypeptide 1b induction |
publisher |
Wiley |
series |
CPT: Pharmacometrics & Systems Pharmacology |
issn |
2163-8306 |
publishDate |
2019-11-01 |
description |
As rifampicin can cause the induction and inhibition of multiple metabolizing enzymes and transporters, it has been challenging to accurately predict the complex drug–drug interactions (DDIs). We previously constructed a physiologically‐based pharmacokinetic (PBPK) model of rifampicin accounting for the components for the induction of cytochrome P450 (CYP) 3A/CYP2C9 and the inhibition of organic anion transporting polypeptide 1B (OATP1B). This study aimed to expand and verify the PBPK model for rifampicin by incorporating additional components for the induction of OATP1B and CYP2C8 and the inhibition of multidrug resistance protein 2. The established PBPK model was capable of accurately predicting complex rifampicin‐induced alterations in the profiles of glibenclamide, repaglinide, and coproporphyrin I (an endogenous biomarker of OATP1B activities) with various dosing regimens. Our comprehensive rifampicin PBPK model may enable quantitative prediction of DDIs across diverse potential victim drugs and endogenous biomarkers handled by multiple metabolizing enzymes and transporters. |
url |
https://doi.org/10.1002/psp4.12457 |
work_keys_str_mv |
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