Application of physiologically-based pharmacokinetic model approach to predict pharmacokinetics and drug-drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine.


Journal

CPT: pharmacometrics & systems pharmacology
ISSN: 2163-8306
Titre abrégé: CPT Pharmacometrics Syst Pharmacol
Pays: United States
ID NLM: 101580011

Informations de publication

Date de publication:
11 2022
Historique:
revised: 21 06 2022
received: 13 12 2021
accepted: 24 06 2022
pubmed: 5 10 2022
medline: 18 11 2022
entrez: 4 10 2022
Statut: ppublish

Résumé

Rivaroxaban (RIV; Xarelto; Janssen Pharmaceuticals, Beerse, Belgium) is one of the direct oral anticoagulants. The drug is a strong substrate of cytochrome P450 (CYP) enzymes and efflux transporters. This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model for RIV. It contained three hepatic metabolizing enzyme reactions (CYP3A4, CYP2J2, and CYP-independent) and two active transporter-mediated transfers (P-gp and BCRP transporters). To illustrate the performance of the developed RIV PBPK model on the prediction of drug-drug interactions (DDIs), carbamazepine (CBZ) was selected as a case study due to the high DDI potential. Our study results showed that CBZ significantly reduces the exposure of RIV. The area under the concentration-time curve from zero to infinity (AUC

Identifiants

pubmed: 36193622
doi: 10.1002/psp4.12844
pmc: PMC9662201
doi:

Substances chimiques

Rivaroxaban 9NDF7JZ4M3
ATP Binding Cassette Transporter, Subfamily G, Member 2 0
Neoplasm Proteins 0
Cytochrome P-450 CYP3A EC 1.14.14.1
Cytochrome P-450 Enzyme System 9035-51-2
Carbamazepine 33CM23913M

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

1430-1442

Informations de copyright

© 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.

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Auteurs

Lien Thi Ngo (LT)

College of Pharmacy, Chungnam National University, Daejeon, Korea.

Sung-Yoon Yang (SY)

College of Pharmacy, Chungnam National University, Daejeon, Korea.

Sooyoung Shin (S)

College of Pharmacy, Ajou University, Suwon, Korea.

Duc Tuan Cao (DT)

Department of Pharmaceutical Chemistry and Quality Control, Faculty of Pharmacy, Haiphong University Medicine and Pharmacy, Haiphong, Vietnam.

Hung Van Nguyen (H)

Department of Pharmacology, Faculty of Pharmacy, Haiphong University Medicine and Pharmacy, Haiphong, Vietnam.

Sangkeun Jung (S)

Department of Computer Science and Engineering, Chungnam National University, Daejeon, Korea.

Jae-Young Lee (JY)

Department of Computer Science and Engineering, Chungnam National University, Daejeon, Korea.

Jong-Hwa Lee (JH)

Korea Institute of Toxicology, Daejeon, Korea.
Department of Human and Environment Toxicology, University of Science and Technology, Daejeon, Korea.

Hwi-Yeol Yun (HY)

College of Pharmacy, Chungnam National University, Daejeon, Korea.

Jung-Woo Chae (JW)

College of Pharmacy, Chungnam National University, Daejeon, Korea.

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Classifications MeSH