Please use this identifier to cite or link to this item: doi:10.22028/D291-41883
Title: Physiologically-based pharmacokinetic modeling of quinidine to establish a CYP3A4, P-gp, and CYP2D6 drug-drug-gene interaction network
Author(s): 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
Language: English
Title: CPT: Pharmacometrics & Systems Pharmacology
Volume: 12
Issue: 8
Pages: 1143-1156
Publisher/Platform: Wiley
Year of Publication: 2023
DDC notations: 500 Science
Publikation type: Journal Article
Abstract: 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 (0.1–600mg). 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.
DOI of the first publication: 10.1002/psp4.12981
URL of the first publication: https://doi.org/10.1002/psp4.12981
Link to this record: urn:nbn:de:bsz:291--ds-418833
hdl:20.500.11880/37468
http://dx.doi.org/10.22028/D291-41883
ISSN: 2163-8306
Date of registration: 12-Apr-2024
Description of the related object: Supporting Information
Related object: https://ascpt.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fpsp4.12981&file=psp412981-sup-0001-Supinfo01.pdf
https://ascpt.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fpsp4.12981&file=psp412981-sup-0002-Supinfo02.zip
https://ascpt.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fpsp4.12981&file=psp412981-sup-0003-Supinfo03.zip
https://ascpt.onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002%2Fpsp4.12981&file=psp412981-sup-0004-Supinfo04.zip
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Pharmazie
Professorship: NT - Prof. Dr. Thorsten Lehr
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes



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