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

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 contain...

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Autores principales: Ngo, Lien Thi, Yang, Sung‐yoon, Shin, Sooyoung, Cao, Duc Tuan, Van Nguyen, Hung, Jung, Sangkeun, Lee, Jae‐Young, Lee, Jong‐Hwa, Yun, Hwi‐yeol, Chae, Jung‐woo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9662201/
https://www.ncbi.nlm.nih.gov/pubmed/36193622
http://dx.doi.org/10.1002/psp4.12844
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author Ngo, Lien Thi
Yang, Sung‐yoon
Shin, Sooyoung
Cao, Duc Tuan
Van Nguyen, Hung
Jung, Sangkeun
Lee, Jae‐Young
Lee, Jong‐Hwa
Yun, Hwi‐yeol
Chae, Jung‐woo
author_facet Ngo, Lien Thi
Yang, Sung‐yoon
Shin, Sooyoung
Cao, Duc Tuan
Van Nguyen, Hung
Jung, Sangkeun
Lee, Jae‐Young
Lee, Jong‐Hwa
Yun, Hwi‐yeol
Chae, Jung‐woo
author_sort Ngo, Lien Thi
collection PubMed
description 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(inf)) of RIV was reduced by 35.2% (from 2221.3 to 1438.7 ng*h/ml) and by 25.5% (from 2467.3 to 1838.4 ng*h/ml) after the first dose and at the steady‐state, respectively, whereas the maximum plasma concentration (C (max)) of RIV was reduced by 37.7% (from 266.3 to 166.1 ng/ml) and 36.4% (from 282.3 to 179.5 ng/ml), respectively. The developed PBPK model of RIV could be paired with PBPK models of other interested perpetrators to predict DDI profiles. Further studies investigating the extent of DDI between CBZ and RIV should be conducted in humans to gain a full understanding of their safety and effects.
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spelling pubmed-96622012022-11-14 Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine Ngo, Lien Thi Yang, Sung‐yoon Shin, Sooyoung Cao, Duc Tuan Van Nguyen, Hung Jung, Sangkeun Lee, Jae‐Young Lee, Jong‐Hwa Yun, Hwi‐yeol Chae, Jung‐woo CPT Pharmacometrics Syst Pharmacol Research 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(inf)) of RIV was reduced by 35.2% (from 2221.3 to 1438.7 ng*h/ml) and by 25.5% (from 2467.3 to 1838.4 ng*h/ml) after the first dose and at the steady‐state, respectively, whereas the maximum plasma concentration (C (max)) of RIV was reduced by 37.7% (from 266.3 to 166.1 ng/ml) and 36.4% (from 282.3 to 179.5 ng/ml), respectively. The developed PBPK model of RIV could be paired with PBPK models of other interested perpetrators to predict DDI profiles. Further studies investigating the extent of DDI between CBZ and RIV should be conducted in humans to gain a full understanding of their safety and effects. John Wiley and Sons Inc. 2022-10-03 2022-11 /pmc/articles/PMC9662201/ /pubmed/36193622 http://dx.doi.org/10.1002/psp4.12844 Text en © 2022 The Authors. CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics. https://creativecommons.org/licenses/by-nc/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Research
Ngo, Lien Thi
Yang, Sung‐yoon
Shin, Sooyoung
Cao, Duc Tuan
Van Nguyen, Hung
Jung, Sangkeun
Lee, Jae‐Young
Lee, Jong‐Hwa
Yun, Hwi‐yeol
Chae, Jung‐woo
Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title_full Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title_fullStr Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title_full_unstemmed Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title_short Application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine
title_sort application of physiologically‐based pharmacokinetic model approach to predict pharmacokinetics and drug–drug interaction of rivaroxaban: a case study of rivaroxaban and carbamazepine
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9662201/
https://www.ncbi.nlm.nih.gov/pubmed/36193622
http://dx.doi.org/10.1002/psp4.12844
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