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Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network

The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P‐glycoprotein (P‐gp) and is therefore recommended for use in clinical drug–drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P‐gp, it is susceptible to DDIs involving thes...

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Autores principales: Feick, Denise, Rüdesheim, Simeon, Marok, Fatima Zahra, Selzer, Dominik, Loer, Helena Leonie Hanae, Teutonico, Donato, Frechen, Sebastian, van der Lee, Maaike, Moes, Dirk Jan A. R., Swen, Jesse J., Schwab, Matthias, Lehr, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10431052/
https://www.ncbi.nlm.nih.gov/pubmed/37165978
http://dx.doi.org/10.1002/psp4.12981
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author Feick, Denise
Rüdesheim, Simeon
Marok, Fatima Zahra
Selzer, Dominik
Loer, Helena Leonie Hanae
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Schwab, Matthias
Lehr, Thorsten
author_facet Feick, Denise
Rüdesheim, Simeon
Marok, Fatima Zahra
Selzer, Dominik
Loer, Helena Leonie Hanae
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Schwab, Matthias
Lehr, Thorsten
author_sort Feick, Denise
collection PubMed
description The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P‐glycoprotein (P‐gp) and is therefore recommended for use in clinical drug–drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P‐gp, it is susceptible to DDIs involving these proteins. Physiologically‐based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug–drug(–gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P‐gp perpetrators as well as CYP2D6 and P‐gp victims. The quinidine parent‐metabolite model including 3‐hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1–600 mg). The model covers efflux transport via P‐gp and metabolic transformation to either 3‐hydroxyquinidine or unspecified metabolites via CYP3A4. The 3‐hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two‐fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two‐fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is.
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spelling pubmed-104310522023-08-17 Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network Feick, Denise Rüdesheim, Simeon Marok, Fatima Zahra Selzer, Dominik Loer, Helena Leonie Hanae Teutonico, Donato Frechen, Sebastian van der Lee, Maaike Moes, Dirk Jan A. R. Swen, Jesse J. Schwab, Matthias Lehr, Thorsten CPT Pharmacometrics Syst Pharmacol Research The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P‐glycoprotein (P‐gp) and is therefore recommended for use in clinical drug–drug interaction (DDI) studies. However, as quinidine is also a substrate of CYP3A4 and P‐gp, it is susceptible to DDIs involving these proteins. Physiologically‐based pharmacokinetic (PBPK) modeling can help to mechanistically assess the absorption, distribution, metabolism, and excretion processes of a drug and has proven its usefulness in predicting even complex interaction scenarios. The objectives of the presented work were to develop a PBPK model of quinidine and to integrate the model into a comprehensive drug–drug(–gene) interaction (DD(G)I) network with a diverse set of CYP3A4 and P‐gp perpetrators as well as CYP2D6 and P‐gp victims. The quinidine parent‐metabolite model including 3‐hydroxyquinidine was developed using pharmacokinetic profiles from clinical studies after intravenous and oral administration covering a broad dosing range (0.1–600 mg). The model covers efflux transport via P‐gp and metabolic transformation to either 3‐hydroxyquinidine or unspecified metabolites via CYP3A4. The 3‐hydroxyquinidine model includes further metabolism by CYP3A4 as well as an unspecific hepatic clearance. Model performance was assessed graphically and quantitatively with greater than 90% of predicted pharmacokinetic parameters within two‐fold of corresponding observed values. The model was successfully used to simulate various DD(G)I scenarios with greater than 90% of predicted DD(G)I pharmacokinetic parameter ratios within two‐fold prediction success limits. The presented network will be provided to the research community and can be extended to include further perpetrators, victims, and targets, to support investigations of DD(G)Is. John Wiley and Sons Inc. 2023-05-23 /pmc/articles/PMC10431052/ /pubmed/37165978 http://dx.doi.org/10.1002/psp4.12981 Text en © 2023 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
Feick, Denise
Rüdesheim, Simeon
Marok, Fatima Zahra
Selzer, Dominik
Loer, Helena Leonie Hanae
Teutonico, Donato
Frechen, Sebastian
van der Lee, Maaike
Moes, Dirk Jan A. R.
Swen, Jesse J.
Schwab, Matthias
Lehr, Thorsten
Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title_full Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title_fullStr Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title_full_unstemmed Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title_short Physiologically‐based pharmacokinetic modeling of quinidine to establish a CYP3A4, P‐gp, and CYP2D6 drug–drug–gene interaction network
title_sort physiologically‐based pharmacokinetic modeling of quinidine to establish a cyp3a4, p‐gp, and cyp2d6 drug–drug–gene interaction network
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10431052/
https://www.ncbi.nlm.nih.gov/pubmed/37165978
http://dx.doi.org/10.1002/psp4.12981
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