ArticleCPT: pharmacometrics & systems pharmacology2016
Simulation and Prediction of the Drug-Drug Interaction Potential of Naloxegol by Physiologically Based Pharmacokinetic Modeling.
Article in CPT: pharmacometrics & systems pharmacology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 39 citations in OpenAlex.
- Population Exposure-Response Modeling Supported Selection of Naloxegol Doses in Phase III Studies in Patients With Opioid-Induced Constipation.CPT: pharmacometrics & systems pharmacology · 2017Trial
- Fixed-dose combination orally disintegrating tablets to treat cardiovascular disease: formulation, in vitro characterization and physiologically based pharmacokinetic modeling to assess bioavailability.Drug design, development and therapy · 2017Trial
- A Physiologically Based Pharmacokinetic Model to Predict Potential Drug-Drug Interactions of TPN171, a Novel Phosphodiesterase Type 5 Inhibitor.CPT: pharmacometrics & systems pharmacology · 2026Article
- The Impact of Paediatric Obesity on Drug Pharmacokinetics: A Virtual Clinical Trials Case Study with Amlodipine.Pharmaceutics · 2024Article
- The Impact of P-Glycoprotein on Opioid Analgesics: What's the Real Meaning in Pain Management and Palliative Care?International journal of molecular sciences · 2022Review
- Article
- Predicting the Drug-Drug Interaction Mediated by CYP3A4 Inhibition: Method Development and Performance Evaluation.The AAPS journal · 2021Article
- Unraveling pleiotropic effects of rifampicin by using physiologically based pharmacokinetic modeling: Assessing the induction magnitude of P-glycoprotein-cytochrome P450 3A4 dual substrates.CPT: pharmacometrics & systems pharmacology · 2021Article
- Potential Drug Interactions of Repurposed COVID-19 Drugs with Lung Cancer Pharmacotherapies.Archives of medical research · 2021Review
- Physiologically-Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug-Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations.Clinical pharmacology and therapeutics · 2020Review
- Peripheral Opioid Receptor Antagonists for Opioid-Induced Constipation: A Primer on Pharmacokinetic Variabilities with a Focus on Drug Interactions.Journal of pain research · 2020Review
- Evaluation of the Drug-Drug Interaction Potential of Acalabrutinib and Its Active Metabolite, ACP-5862, Using a Physiologically-Based Pharmacokinetic Modeling Approach.CPT: pharmacometrics & systems pharmacology · 2019Article
- Detecting drug communities and predicting comprehensive drug-drug interactions via balance regularized semi-nonnegative matrix factorization.Journal of cheminformatics · 2019Article
- Assessing Potential Drug-Drug Interactions Between Dabigatran Etexilate and a P-Glycoprotein Inhibitor in Renal Impairment Populations Using Physiologically Based Pharmacokinetic Modeling.CPT: pharmacometrics & systems pharmacology · 2019Article
- TMFUF: a triple matrix factorization-based unified framework for predicting comprehensive drug-drug interactions of new drugs.BMC bioinformatics · 2018Article
- Physiologically Based Pharmacokinetic Modeling of Fimasartan, Amlodipine, and Hydrochlorothiazide for the Investigation of Drug-Drug Interaction Potentials.Pharmaceutical research · 2018Article
- An Integrated Local Classification Model of Predicting Drug-Drug Interactions via Dempster-Shafer Theory of Evidence.Scientific reports · 2018Article
- Physiologically Based Pharmacokinetic Model Qualification and Reporting Procedures for Regulatory Submissions: A Consortium Perspective.Clinical pharmacology and therapeutics · 2018Review
- Predicting and understanding comprehensive drug-drug interactions via semi-nonnegative matrix factorization.BMC systems biology · 2018Article
- Clinical Pharmacokinetics and Pharmacodynamics of Naloxegol, a Peripherally Acting µ-Opioid Receptor Antagonist.Clinical pharmacokinetics · 2017Review
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Naloxegol, a peripherally acting μ-opioid receptor antagonist for the treatment of opioid-induced constipation, is a substrate for cytochrome P450 (CYP) 3A4/3A5 and the P-glycoprotein (P-gp) transporter. By integrating in silico, preclinical, and clinical pharmacokinetic (PK) findings, minimal and full physiologically based pharmacokinetic (PBPK) models were developed to predict the drug-drug interaction (DDI) potential for naloxegol. The models reasonably predicted the observed changes in naloxegol exposure with ketoconazole (increase of 13.1-fold predicted vs. 12.9-fold observed), diltiazem (increase of 2.8-fold predicted vs. 3.4-fold observed), rifampin (reduction of 76% predicted vs. 89% observed), and quinidine (increase of 1.2-fold predicted vs. 1.4-fold observed). The moderate CYP3A4 inducer efavirenz was predicted to reduce naloxegol exposure by ∼50%, whereas weak CYP3A inhibitors were predicted to minimally affect exposure. In summary, the PBPK models reasonably estimated interactions with various CYP3A modulators and can be used to guide dosing in clinical practice when naloxegol is coadministered with such agents.
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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.