ArticleClinical pharmacokinetics2017
Physiologically Based Pharmacokinetic Modeling to Predict Drug-Drug Interactions with Efavirenz Involving Simultaneous Inducing and Inhibitory Effects on Cytochromes.
Article in Clinical pharmacokinetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 25 citations in OpenAlex.
- Effect of patient genetics on etonogestrel pharmacokinetics when combined with efavirenz or nevirapine ART.The Journal of antimicrobial chemotherapy · 2019Trial
- Physiologically Based Pharmacokinetic Modeling to Assess Antiretroviral-BTK Inhibitor Interactions and Provide Recommendations for Co-Administration Regimens.Pharmaceutics · 2026Article
- Physiologically Based Pharmacokinetic Modeling of Efavirenz Nanoparticles: from Animal Model to Human Extrapolation.ACS omega · 2025Article
- Predicting Drug-Drug Interactions between Rifampicin and Ritonavir-Boosted Atazanavir Using PBPK Modelling.Clinical pharmacokinetics · 2022Article
- Drug-Drug Interaction Between Oxycodone and Diazepam by a CombinedACS chemical neuroscience · 2021Article
- Innovative Approaches for Pharmacology Studies in Pregnant and Lactating Women: A Viewpoint and Lessons from HIV.Clinical pharmacokinetics · 2020Article
- The Segregated Intestinal Flow Model (SFM) for Drug Absorption and Drug Metabolism: Implications on Intestinal and Liver Metabolism and Drug-Drug Interactions.Pharmaceutics · 2020Review
- Physiologically Based Pharmacokinetic Modelling to Identify Pharmacokinetic Parameters Driving Drug Exposure Changes in the Elderly.Clinical pharmacokinetics · 2020Article
- Utilization of Physiologically Based Pharmacokinetic Modeling in Clinical Pharmacology and Therapeutics: an Overview.Current pharmacology reports · 2020Review
- Predicting Drug-Drug Interactions Between Rifampicin and Long-Acting Cabotegravir and Rilpivirine Using Physiologically Based Pharmacokinetic Modeling.The Journal of infectious diseases · 2019Article
- Physiologically based pharmacokinetic modelling prediction of the effects of dose adjustment in drug-drug interactions between levonorgestrel contraceptive implants and efavirenz-based ART.The Journal of antimicrobial chemotherapy · 2018Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAntiretroviral drugs are among the therapeutic agents with the highest potential for drug-drug interactions (DDIs). In the absence of clinical data, DDIs are mainly predicted based on preclinical data and knowledge of the disposition of individual drugs. Predictions can be challenging, especially when antiretroviral drugs induce and inhibit multiple cytochrome P450 (CYP) isoenzymes simultaneously.
methodsThis study predicted the magnitude of the DDI between efavirenz, an inducer of CYP3A4 and inhibitor of CYP2C8, and dual CYP3A4/CYP2C8 substrates (repaglinide, montelukast, pioglitazone, paclitaxel) using a physiologically based pharmacokinetic (PBPK) modeling approach integrating concurrent effects on CYPs. In vitro data describing the physicochemical properties, absorption, distribution, metabolism, and elimination of efavirenz and CYP3A4/CYP2C8 substrates as well as the CYP-inducing and -inhibitory potential of efavirenz were obtained from published literature. The data were integrated in a PBPK model developed using mathematical descriptions of molecular, physiological, and anatomical processes defining pharmacokinetics. Plasma drug-concentration profiles were simulated at steady state in virtual individuals for each drug given alone or in combination with efavirenz. The simulated pharmacokinetic parameters of drugs given alone were compared against existing clinical data. The effect of efavirenz on CYP was compared with published DDI data.
resultsThe predictions indicate that the overall effect of efavirenz on dual CYP3A4/CYP2C8 substrates is induction of metabolism. The magnitude of induction tends to be less pronounced for dual CYP3A4/CYP2C8 substrates with predominant CYP2C8 metabolism.
conclusionPBPK modeling constitutes a useful mechanistic approach for the quantitative prediction of DDI involving simultaneous inducing or inhibitory effects on multiple CYPs as often encountered with antiretroviral drugs.
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