WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: • Population pharmacokinetics and pharmacodynamics of rivaroxaban have been characterized in healthy subjects and in patients with total venous thromboembolism, deep vein thrombosis or atrial fibrillation. WHAT THIS STUDY ADDS: • This article is the first description of the population pharmacokinetics (PK) and pharmacodynamics (PD) of rivaroxaban in patients with acute coronary syndrome (ACS). It is the largest population pharmacokinetic and pharmacodynamic study on rivaroxaban conducted to date (n= 2290). The PK and PK-PD relationship of rivaroxaban in patients with ACS were similar to those in other patient populations. In addition, model-based simulations showed that the influence of renal function and age on the exposure to rivaroxaban in the ACS population were similar to the findings from Phase 1 special population studies. These findings suggest that rivaroxaban has highly predictable PK-PD and may provide a consistent anticoagulant effect across the studied patient populations, which allows an accurate prediction of the dose to control anticoagulation optimally. AIMS: The aim of this analysis was to use a population approach to facilitate the understanding of the pharmacokinetics and pharmacodynamics of rivaroxaban in patients with acute coronary syndrome (ACS) and to evaluate the influence of patient covariates on the exposure of rivaroxaban in patients with ACS. METHODS A population pharmacokinetic model was developed using pharmacokinetic samples from 2290 patients inAnti-Xa Therapy to Lower Cardiovascular Events in Addition to Standard Therapy in Subjects with Acute Coronary Syndrome Thrombolysis in Myocardial Infarction 46. The relationship between pharmacokinetics and the primary pharmacodynamic end point, prothrombin time, was evaluated. RESULTS: The pharmacokinetics of rivaroxaban in patients with ACS was adequately described by an oral one-compartment model. The estimated absorption rate, apparent clearance and volume of distribution were 1.24 h(-1) (interindividual variability, 139%), 6.48 l h(-1) (31%) and 57.9 l (10%), respectively. Simulations indicate that the influences of renal function, age and bodyweight on exposure in ACS patients are consistent with the findings in previous Phase 1 studies. Rivaroxaban plasma concentrations exhibit a close-to-linear relationship with prothrombin time in the ACS population, with little interindividual variability. The estimated pharmacokinetic and pharmacodynamic parameters for the ACS patients were comparable to those for venous thromboembolism prevention, deep vein thrombosis and atrial fibrillation patients. CONCLUSIONS: The similarity in pharmacokinetics/pharmacodynamics of rivaroxaban among different patient populations and the low interindividual variability in the exposure-prothrombin time relationship indicate that the anticoagulant effect of rivaroxaban is highly predictable and consistent across all the patient populations studied.
RCT Entities:
WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT: • Population pharmacokinetics and pharmacodynamics of rivaroxaban have been characterized in healthy subjects and in patients with total venous thromboembolism, deep vein thrombosis or atrial fibrillation. WHAT THIS STUDY ADDS: • This article is the first description of the population pharmacokinetics (PK) and pharmacodynamics (PD) of rivaroxaban in patients with acute coronary syndrome (ACS). It is the largest population pharmacokinetic and pharmacodynamic study on rivaroxaban conducted to date (n= 2290). The PK and PK-PD relationship of rivaroxaban in patients with ACS were similar to those in other patient populations. In addition, model-based simulations showed that the influence of renal function and age on the exposure to rivaroxaban in the ACS population were similar to the findings from Phase 1 special population studies. These findings suggest that rivaroxaban has highly predictable PK-PD and may provide a consistent anticoagulant effect across the studied patient populations, which allows an accurate prediction of the dose to control anticoagulation optimally. AIMS: The aim of this analysis was to use a population approach to facilitate the understanding of the pharmacokinetics and pharmacodynamics of rivaroxaban in patients with acute coronary syndrome (ACS) and to evaluate the influence of patient covariates on the exposure of rivaroxaban in patients with ACS. METHODS A population pharmacokinetic model was developed using pharmacokinetic samples from 2290 patients in Anti-Xa Therapy to Lower Cardiovascular Events in Addition to Standard Therapy in Subjects with Acute Coronary Syndrome Thrombolysis in Myocardial Infarction 46. The relationship between pharmacokinetics and the primary pharmacodynamic end point, prothrombin time, was evaluated. RESULTS: The pharmacokinetics of rivaroxaban in patients with ACS was adequately described by an oral one-compartment model. The estimated absorption rate, apparent clearance and volume of distribution were 1.24 h(-1) (interindividual variability, 139%), 6.48 l h(-1) (31%) and 57.9 l (10%), respectively. Simulations indicate that the influences of renal function, age and bodyweight on exposure in ACS patients are consistent with the findings in previous Phase 1 studies. Rivaroxaban plasma concentrations exhibit a close-to-linear relationship with prothrombin time in the ACS population, with little interindividual variability. The estimated pharmacokinetic and pharmacodynamic parameters for the ACS patients were comparable to those for venous thromboembolism prevention, deep vein thrombosis and atrial fibrillationpatients. CONCLUSIONS: The similarity in pharmacokinetics/pharmacodynamics of rivaroxaban among different patient populations and the low interindividual variability in the exposure-prothrombin time relationship indicate that the anticoagulant effect of rivaroxaban is highly predictable and consistent across all the patient populations studied.
Authors: Ajay K Kakkar; Benjamin Brenner; Ola E Dahl; Bengt I Eriksson; Patrick Mouret; Jim Muntz; Andrea G Soglian; Akos F Pap; Frank Misselwitz; Sylvia Haas Journal: Lancet Date: 2008-06-24 Impact factor: 79.321
Authors: Rupert Bauersachs; Scott D Berkowitz; Benjamin Brenner; Harry R Buller; Hervé Decousus; Alex S Gallus; Anthonie W Lensing; Frank Misselwitz; Martin H Prins; Gary E Raskob; Annelise Segers; Peter Verhamme; Phil Wells; Giancarlo Agnelli; Henri Bounameaux; Alexander Cohen; Bruce L Davidson; Franco Piovella; Sebastian Schellong Journal: N Engl J Med Date: 2010-12-03 Impact factor: 91.245
Authors: J L Mega; E Braunwald; S Mohanavelu; P Burton; R Poulter; F Misselwitz; V Hricak; E S Barnathan; P Bordes; A Witkowski; V Markov; L Oppenheimer; C M Gibson Journal: Lancet Date: 2009-06-17 Impact factor: 79.321
Authors: Alexander G G Turpie; Michael R Lassen; Bruce L Davidson; Kenneth A Bauer; Michael Gent; Louis M Kwong; Fred D Cushner; Paul A Lotke; Scott D Berkowitz; Tiemo J Bandel; Alice Benson; Frank Misselwitz; William D Fisher Journal: Lancet Date: 2009-05-04 Impact factor: 79.321