ArticleClinical pharmacokinetics2019
A Comprehensive Whole-Body Physiologically Based Pharmacokinetic Model of Dabigatran Etexilate, Dabigatran and Dabigatran Glucuronide in Healthy Adults and Renally Impaired Patients.
Article in Clinical pharmacokinetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 23 citations in OpenAlex.
- Translation of a physiologically-based pharmacokinetic model for dabigatran etexilate to the design of a safety and efficacy study in post-partum women.British journal of clinical pharmacology · 2026Article
- Idarucizumab more effectively reverses the anticoagulant effects of dabigatran acylglucuronide than dabigatran.Scientific reports · 2025Article
- Evaluation of Drug-Drug Interactions Between Clarithromycin and Direct Oral Anticoagulants Using Physiologically Based Pharmacokinetic Models.Pharmaceutics · 2024Article
- Membrane transporters in drug development and as determinants of precision medicine.Nature reviews. Drug discovery · 2024Review
- Article
- Assessing the relative contribution of CYP3A-and P-gp-mediated pathways to the overall disposition and drug-drug interaction of dabigatran etexilate using a comprehensive mechanistic physiological-based pharmacokinetic model.Frontiers in pharmacology · 2024Article
- Physiologically-based pharmacokinetic modeling to predict drug-drug interactions of dabigatran etexilate and rivaroxaban in the Chinese older adults.European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences · 2023Article
- The Impact of Suboptimal 25-Hydroxyvitamin D Levels and Cholecalciferol Replacement on the Pharmacokinetics of Oral Midazolam in Control Subjects and Patients With Chronic Kidney Disease.Journal of clinical pharmacology · 2022Article
- Dabigatran Acylglucuronide, the Major Metabolite of Dabigatran, Shows a Weaker Anticoagulant Effect than Dabigatran.Pharmaceutics · 2022Article
- Physiologically-based pharmacokinetics modeling to investigate formulation factors influencing the generic substitution of dabigatran etexilate.CPT: pharmacometrics & systems pharmacology · 2021Article
- Risk of Hospitalization With Hemorrhage Among Older Adults Taking Clarithromycin vs Azithromycin and Direct Oral Anticoagulants.JAMA internal medicine · 2020Article
- Effect of P-glycoprotein (P-gp) Inducers on Exposure of P-gp Substrates: Review of Clinical Drug-Drug Interaction Studies.Clinical pharmacokinetics · 2020Review
- Data Digitizing: Accurate and Precise Data Extraction for Quantitative Systems Pharmacology and Physiologically-Based Pharmacokinetic Modeling.CPT: pharmacometrics & systems pharmacology · 2020Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
objectivesThe thrombin inhibitor dabigatran is administered as the prodrug dabigatran etexilate, which is a substrate of esterases and P-glycoprotein (P-gp). Dabigatran is eliminated via renal excretion but is also a substrate of uridine 5'-diphospho (UDP)-glucuronosyltransferases (UGTs). The objective of this study was to build a physiologically based pharmacokinetic (PBPK) model comprising dabigatran etexilate, dabigatran, and dabigatran 1-O-acylglucuronide to describe the pharmacokinetics in healthy adults and renally impaired patients mechanistically.
methodsModel development and evaluation were carried out using (i) physicochemical and absorption, distribution, metabolism, and excretion (ADME) parameter values of all three analytes; (ii) concentration-time profiles from 13 studies of healthy and renally impaired individuals after varying doses (0.1-300 mg), intravenous (dabigatran) and oral (dabigatran etexilate) administration, and different formulations of dabigatran etexilate (capsule, solution); and (iii) drug-drug interaction studies of dabigatran with the P-gp perpetrators rifampin (inducer) and clarithromycin (inhibitor).
resultsA PBPK model of dabigatran was successfully developed. The predicted area under the plasma concentration-time curve, trough concentration, and half-life values of the assessed clinical studies satisfied the two-fold acceptance criterion. Metabolic clearances of dabigatran etexilate and dabigatran were implemented using data on carboxylesterase 1/2 enzymes and UGT subtype 2B15. In severe renal impairment, the UGT2B15 metabolism and the P-gp transport in the model were reduced to 67% and 65% of the rates in healthy adults.
conclusionThis is the first implementation of a PBPK model for dabigatran to distinguish between the prodrug, active moiety, and main active metabolite. Following adjustment of the UGT2B15 metabolism and P-gp transport rates, the PBPK model accurately predicts the pharmacokinetics in renally impaired patients.
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