ArticleEuropean journal of drug metabolism and pharmacokinetics2021
Physiologically-Based Pharmacokinetic Modelling of Entrectinib Parent and Active Metabolite to Support Regulatory Decision-Making.
Article in European journal of drug metabolism and pharmacokinetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 14 citations in OpenAlex.
- Clinical Exploration and Physiologically Based Modelling of the Impact of Hepatic Impairment on Entrectinib Pharmacokinetics.Clinical pharmacokinetics · 2025Trial
- Entrectinib in children and young adults with solid or primary CNS tumors harboring NTRK, ROS1, or ALK aberrations (STARTRK-NG).Neuro-oncology · 2022Trial
- Evaluation of the Effects of Nicardipine on Entrectinib Metabolism in vitro and in Rats.European journal of drug metabolism and pharmacokinetics · 2026Article
- Evaluation of the potential impact on pharmacokinetics of various cytochrome P450 substrates of increasing IL-6 levels following administration of the T-cell bispecific engager glofitamab.CPT: pharmacometrics & systems pharmacology · 2024Article
- Prediction of ROS1 and TRKA/B/C occupancy in plasma and cerebrospinal fluid for entrectinib alone and in DDIs using physiologically based pharmacokinetic (PBPK) modeling approach.Cancer chemotherapy and pharmacology · 2024Article
- Application of physiologically based pharmacokinetics modeling in the research of small-molecule targeted anti-cancer drugs.Cancer chemotherapy and pharmacology · 2023Review
- Alternatives to rifampicin: A review and perspectives on the choice of strong CYP3A inducers for clinical drug-drug interaction studies.Clinical and translational science · 2022Review
Corrections and comments
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Authors and funding
11 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectiveEntrectinib is a selective inhibitor of ROS1/TRK/ALK kinases, recently approved for oncology indications. Entrectinib is predominantly cleared by cytochrome P450 (CYP) 3A4, and modulation of CYP3A enzyme activity profoundly alters the pharmacokinetics of both entrectinib and its active metabolite M5. We describe development of a combined physiologically based pharmacokinetic (PBPK) model for entrectinib and M5 to support dosing recommendations when entrectinib is co-administered with CYP3A4 inhibitors or inducers.
methodsA PBPK model was established in Simcyp
resultsThe final model showed good predictive performance for entrectinib and M5, meeting commonly used predictive performance acceptance criteria in each case. The model predicted that co-administration of various moderate CYP3A4 inhibitors (verapamil, erythromycin, clarithromycin, fluconazole, and diltiazem) would result in an average increase in entrectinib exposure between 2.2- and 3.1-fold, with corresponding average increases for M5 of approximately 2-fold. Co-administration of moderate CYP3A4 inducers (efavirenz, carbamazepine, phenytoin) was predicted to result in an average decrease in entrectinib exposure between 45 and 79%, with corresponding average decreases for M5 of approximately 50%.
conclusionsThe model simulations were used to derive dosing recommendations for co-administering entrectinib with CYP3A4 inhibitors or inducers. PBPK modeling has been used in lieu of clinical studies to enable regulatory decision-making.
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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.