ArticleClinical pharmacokinetics2019
Physiologically Based Pharmacokinetic Models for Prediction of Complex CYP2C8 and OATP1B1 (SLCO1B1) Drug-Drug-Gene Interactions: A Modeling Network of Gemfibrozil, Repaglinide, Pioglitazone, Rifampicin, Clarithromycin and Itraconazole.
Article in Clinical pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Integrated assessment of rifampicin-mediated induction of transporters and drug-metabolizing enzymes in a long-term human liver tissue chip system.Clinical pharmacology and therapeutics · 2026Article
- Physiologically based pharmacokinetic model of two ALK inhibitors to inform drug and dosing regimens for brain metastasis patients.Frontiers in pharmacology · 2026Article
- Coproporphyrin I PBPK model in the open systems pharmacology suite enables precise prediction of OATP 1B- mediated drug interactions through calibratedFrontiers in pharmacology · 2026Article
- Integrated Physiologically-based Pharmacokinetic Model with a Quantitative Systems Pharmacology and Toxicology Model for Statins in Disease Population. Part 2: MIDD and MIPD Applications.The AAPS journal · 2025Article
- Drug Interaction PBPK Modeling: Review of the Literature Exposes the Need for Increased Verification of Model Inputs and Outputs as Part of Credibility Assessment.Clinical and translational science · 2025Review
- A Comprehensive CYP2D6 Drug-Drug-Gene Interaction Network for Application in Precision Dosing and Drug Development.Clinical pharmacology and therapeutics · 2025Article
- Formulation Strategy of BCS-II Drugs by Coupling Mechanistic In-Vitro and Nonclinical In-Vivo Data with PBPK: Fundamentals of Absorption-Dissolution to Parameterization of Modelling and Simulation.AAPS PharmSciTech · 2025Review
- Physiologically based pharmacokinetic modeling of drug-drug interactions between ritonavir-boosted atazanavir and rifampicin in pregnancy.CPT: pharmacometrics & systems pharmacology · 2024Observational
- Physiologically based pharmacokinetic modeling of imatinib and N-desmethyl imatinib for drug-drug interaction predictions.CPT: pharmacometrics & systems pharmacology · 2024Article
- The Pharmacokinetics of the Nonsteroidal Mineralocorticoid Receptor Antagonist Finerenone.Clinical pharmacokinetics · 2023Review
- Drug-drug interaction prediction of ziritaxestat using a physiologically based enzyme and transporter pharmacokinetic network interaction model.Clinical and translational science · 2023Article
- Development of a Physiologically Based Pharmacokinetic Model for Tegoprazan: Application for the Prediction of Drug-Drug Interactions with CYP3A4 Perpetrators.Pharmaceutics · 2023Article
- Article
- Predicting Drug-Drug Interactions between Rifampicin and Ritonavir-Boosted Atazanavir Using PBPK Modelling.Clinical pharmacokinetics · 2022Article
- Physiologically-based pharmacokinetic modeling to predict CYP3A4-mediated drug-drug interactions of finerenone.CPT: pharmacometrics & systems pharmacology · 2022Article
- Cytochrome P450 Enzymes and Drug Metabolism in Humans.International journal of molecular sciences · 2021Review
- Physiologically Based Pharmacokinetic Modeling of Rosuvastatin to Predict Transporter-Mediated Drug-Drug Interactions.Pharmaceutical research · 2021Article
- Evaluation for Potential Drug-Drug Interaction of MT921 Using In Vitro Studies and Physiologically-Based Pharmacokinetic Models.Pharmaceuticals (Basel, Switzerland) · 2021Article
- A generic framework for the physiologically-based pharmacokinetic platform qualification of PK-Sim and its application to predicting cytochrome P450 3A4-mediated drug-drug interactions.CPT: pharmacometrics & systems pharmacology · 2021Article
- Drug-Metabolizing Cytochrome P450 Enzymes Have Multifarious Influences on Treatment Outcomes.Clinical pharmacokinetics · 2021Review
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDrug-drug interactions (DDIs) and drug-gene interactions (DGIs) pose a serious health risk that can be avoided by dose adaptation. These interactions are investigated in strictly controlled setups, quantifying the effect of one perpetrator drug or polymorphism at a time, but in real life patients frequently take more than two medications and are very heterogenous regarding their genetic background.
objectivesThe first objective of this study was to provide whole-body physiologically based pharmacokinetic (PBPK) models of important cytochrome P450 (CYP) 2C8 perpetrator and victim drugs, built and evaluated for DDI and DGI studies. The second objective was to apply these models to describe complex interactions with more than two interacting partners.
methodsPBPK models of the CYP2C8 and organic-anion-transporting polypeptide (OATP) 1B1 perpetrator drug gemfibrozil (parent-metabolite model) and the CYP2C8 victim drugs repaglinide (also an OATP1B1 substrate) and pioglitazone were developed using a total of 103 clinical studies. For evaluation, these models were applied to predict 34 different DDI studies, establishing a CYP2C8 and OATP1B1 PBPK DDI modeling network.
resultsThe newly developed models show a good performance, accurately describing plasma concentration-time profiles, area under the plasma concentration-time curve (AUC) and maximum plasma concentration (C
conclusionsWhole-body PBPK models of gemfibrozil, repaglinide, and pioglitazone have been built and qualified for DDI and DGI prediction. PBPK modeling is applicable to investigate complex interactions between multiple drugs and genetic polymorphisms.
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