ArticleEuropean journal of clinical pharmacology2018
Application of physiologically based pharmacokinetic modeling to the prediction of drug-drug and drug-disease interactions for rivaroxaban.
Article in European journal of clinical pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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
18 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Drug-drug interactions with direct oral anticoagulants associated with adverse events in the real world: A systematic review.Thrombosis research · 2020Pooled it
- Characterizing Apixaban Pharmacokinetics Through Physiologically-Based Pharmacokinetic Modeling: Critical Role of Biliary Secretion and Enterohepatic Circulation in Humans.CPT: pharmacometrics & systems pharmacology · 2026Article
- RSM and AI based machine learning for quality by design development of rivaroxaban push-pull osmotic tablets and its PBPK modeling.Scientific reports · 2025Article
- Dose Optimization of Rivaroxaban in Elderly Chinese Patients with Non-Valvular Atrial Fibrillation: Analysis of Populations Pharmacokinetics and Exposure-Response Relationships.Drug design, development and therapy · 2025Observational
- Apixaban and rivaroxaban's physiologically-based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side.CPT: pharmacometrics & systems pharmacology · 2023Article
- Clinical significance of the rivaroxaban-dronedarone interaction: insights from physiologically based pharmacokinetic modelling.European heart journal open · 2023Review
- Prediction of cytochromes P450 3A and 2C19 modulation by both inflammation and drug interactions using physiologically based pharmacokinetics.CPT: pharmacometrics & systems pharmacology · 2022Article
- Predicting the Drug-Drug Interaction Mediated by CYP3A4 Inhibition: Method Development and Performance Evaluation.The AAPS journal · 2021Article
- Applications of Physiologically Based Pharmacokinetic Modeling of Rivaroxaban-Renal and Hepatic Impairment and Drug-Drug Interaction Potential.Journal of clinical pharmacology · 2021Article
- Multi-factorial pharmacokinetic interactions: unraveling complexities in precision drug therapy.Expert opinion on drug metabolism & toxicology · 2021Review
- Drug-Drug Interactions Leading to Adverse Drug Reactions with Rivaroxaban: A Systematic Review of the Literature and Analysis of VigiBase.Journal of personalized medicine · 2021Review
- Prediction of Rivaroxaban-Rifampin Interaction After Major Orthopedic Surgery: Physiologically Based Pharmacokinetic Modeling and Simulation.Frontiers in pharmacology · 2021Article
- Influence of Inflammation on Cytochromes P450 Activity in Adults: A Systematic Review of the Literature.Frontiers in pharmacology · 2021Review
- Physiologically-Based Pharmacokinetic Modeling for the Prediction of a Drug-Drug Interaction of Combined Effects on P-glycoprotein and Cytochrome P450 3A.CPT: pharmacometrics & systems pharmacology · 2020Article
- Risk of Hospitalization With Hemorrhage Among Older Adults Taking Clarithromycin vs Azithromycin and Direct Oral Anticoagulants.JAMA internal medicine · 2020Article
- Towards Personalized Antithrombotic Treatments: Focus on P2YClinical pharmacokinetics · 2019Review
- Current trends in drug metabolism and pharmacokinetics.Acta pharmaceutica Sinica. B · 2019Review
- Drug-drug interactions in an era of multiple anticoagulants: a focus on clinically relevant drug interactions.Hematology. American Society of Hematology. Education Program · 2018Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
purposeRivaroxaban is a direct oral anticoagulant with a large inter-individual variability. The present study is to develop a physiologically based pharmacokinetic (PBPK) model to predict several scenarios in clinical practice.
methodsA whole-body PBPK model for rivaroxaban, which is metabolized by the cytochrome P450 (CYP) 3A4/5, 2J2 pathways and excreted via kidneys, was developed to predict the pharmacokinetics at different doses in healthy subjects and patients with hepatic or renal dysfunction. Hepatic clearance and drug-drug interactions (DDI) were estimated by in vitro in vivo extrapolation (IVIVE) based on parameters obtained from in vitro experiments. To validate the model, observed concentrations were compared with predicted concentrations, and the impact of special scenarios was investigated.
resultsThe PBPK model successfully predicted the pharmacokinetics for healthy subjects and patients as well as DDIs. Sensitivity analysis shows that age, renal, and hepatic clearance are important factors affecting rivaroxaban pharmacokinetics. The predicted fold increase of rivaroxaban AUC values when combined administered with the inhibitors such as ketoconazole, ritonavir, and clarithromycin were 2.3, 2.2, and 1.3, respectively. When DDIs and hepatic dysfunction coexist, the fold increase of rivaroxaban exposure would increase significantly compared with one factor alone.
conclusionsOur study using PBPK modeling provided a reasonable approach to evaluate exposure levels in special patients under special scenarios. Although further clinical study or real-life experience would certainly merit the current work, the modeling work so far would at least suggest caution of using rivaroxaban in complicated clinical settings.
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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.