ArticleClinical pharmacokinetics2011
Quantitative prediction of cytochrome P450 (CYP) 2D6-mediated drug interactions.
Article in Clinical pharmacokinetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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The trial behind it
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Who cites it
28 citing papers in PubMed, 48 citations in OpenAlex.
- Pharmacokinetic interaction between pyronaridine-artesunate and metoprolol.Antimicrobial agents and chemotherapy · 2014Trial
- Verification of a Physiologically-based Pharmacokinetic Model for Predicting CYP3A4-mediated Simvastatin and Simvastatin Acid Drug-drug Interactions.The AAPS journal · 2026Article
- Quantitative prediction of intravenous drug interactions caused by cytochromes P450 inhibitors and inducers.British journal of clinical pharmacology · 2026Article
- Integrated Use of In Vitro and In Vivo Information for Comprehensive Prediction of Drug Interactions Due to Inhibition of Multiple CYP Isoenzymes.Clinical pharmacokinetics · 2023Article
- Evaluation of Renal Impairment Influence on Metabolic Drug Clearance using a Modelling Approach.Clinical pharmacokinetics · 2023Article
- Quantitative Prediction of Drug Interactions Caused by Cytochrome P450 2B6 Inhibition or Induction.Clinical pharmacokinetics · 2022Article
- Severe CNS depression with duloxetine, ciprofloxacin and CYP2D6 deficiency-role and recognition of drug-drug-gene interactions.European journal of clinical pharmacology · 2022Article
- Model-Based Comparative Analysis of Rifampicin and Rifabutin Drug-Drug Interaction Profile.Antimicrobial agents and chemotherapy · 2021Article
- Influence of Cation Transporters (OCTs and MATEs) on the Renal and Hepatobiliary Disposition of [Pharmaceutical research · 2021Article
- A Scoping Review of the Evidence Behind Cytochrome P450 2D6 Isoenzyme Inhibitor Classifications.Clinical pharmacology and therapeutics · 2020Article
- Quantitative Prediction of Interactions Mediated by Transporters and Cytochromes: Application to Organic Anion Transporting Polypeptides, Breast Cancer Resistance Protein and Cytochrome 2C8.Clinical pharmacokinetics · 2020Article
- A Generic Model for Quantitative Prediction of Interactions Mediated by Efflux Transporters and Cytochromes: Application to P-Glycoprotein and Cytochrome 3A4.Clinical pharmacokinetics · 2019Article
- Identification of Cytochrome P450-Mediated Drug-Drug Interactions at Risk in Cases of Gene Polymorphisms by Using a Quantitative Prediction Model.Clinical pharmacokinetics · 2018Article
- Semi-Mechanistic Model for Predicting the Dosing Rate in Children and Neonates for Drugs Mainly Eliminated by Cytochrome Metabolism.Clinical pharmacokinetics · 2018Article
- Analysis of Clinical Drug-Drug Interaction Data To Predict Magnitudes of Uncharacterized Interactions between Antiretroviral Drugs and Comedications.Antimicrobial agents and chemotherapy · 2018Article
- Respiratory depression related to multiple drug-drug interactions precipitated by a fluconazole loading dose in a patient treated with oxycodone.European journal of clinical pharmacology · 2017Article
- Quantitative Prediction of Drug-Drug Interactions Involving Inhibitory Metabolites by Physiologically Based Pharmacokinetic Models: Is it Worth It?CPT: pharmacometrics & systems pharmacology · 2017Article
- A Model for Predicting the Interindividual Variability of Drug-Drug Interactions.The AAPS journal · 2017Article
- Quantitative Prediction of Drug Interactions Caused by CYP1A2 Inhibitors and Inducers.Clinical pharmacokinetics · 2016Article
- Pre-clinical evaluation of CYP 2D6 dependent drug-drug interactions between primaquine and SSRI/SNRI antidepressants.Malaria journal · 2016Article
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesAn approach was recently proposed for quantitative predictions of cytochrome P450 (CYP) 3A4-mediated drug-drug interactions. This approach relies solely on in vivo data. It is based on two characteristic parameters: the contribution ratio (CR; i.e. the fraction of victim drug clearance due to metabolism by a specific CYP) and the inhibition ratio (IR) of the inhibitor. Knowledge of these parameters allows forecasting of the ratio between the area under the plasma concentration-time curve (AUC) of the victim drug when the inhibitor is co-administered and the AUC of the victim drug administered alone. The goals of our study were to extend this method to CYP2D6-mediated interactions, to validate it, and to forecast the magnitude of a large number of interactions that have not been studied so far.
methodsA three-step approach was pursued. First, initial estimates of CRs and IRs were obtained by several methods, using data from the literature. Second, an external validation of these initial estimates was carried out, by comparing the predicted AUC ratios with the observed values. Third, refined estimates of CRs and IRs were obtained by orthogonal regression in a Bayesian framework.
resultsThirty-nine AUC ratios were available for external validation. The mean prediction error of the ratios was 0.31, while the mean prediction absolute error was 1.14. Seventy AUC ratios were available for the global analysis. Final estimates of CRs and IRs were obtained for 39 substrates and 11 inhibitors, respectively. The mean prediction error of the AUC ratios was 0.04, while the mean prediction absolute error was 0.51.
conclusionsPredictive distributions for 615 possible interactions were obtained, giving detailed information on some drugs or inhibitors that have been poorly studied so far, such as metoclopramide, bupropion and terbinafine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.