Background The direct oral anticoagulants (DOACs) dabigatran and rivaroxaban are both substrates of the P-glycoprotein (P-gp) transporter, encoded by the ABCB1 gene. Rivaroxaban is metabolized by cytochrome P450 A4 (CYP3A4). Interindividual variability in DOAC exposure and frequent P-gp-associated drug-drug interactions have been described in patients. Objective To assess the influence of ABCB1 polymorphisms on the pharmacokinetics of dabigatran and rivaroxaban, associated or not with clarithromycin, a P-gp and CYP3A4 inhibitor. Methods Sixty healthy male volunteers, selected according to ABCB1 genotype (20 homozygous mutated, 20 heterozygous mutated, and 20 wild-type for haplotype 2677-3435), were included in this randomized, two-center, crossover study. All received sequentially a single dose of dabigatran etexilate (300 mg) and rivaroxaban (40 mg) associated or not with clarithromycin. Peak plasma concentration and area under the curve (AUC) were compared across the three ABCB1 genotypes. The effect of clarithromycin on dabigatran or rivaroxaban pharmacokinetics was assessed. Results Interindividual coefficients of variation for AUC were 77% for dabigatran and 51% for rivaroxaban. ABCB1 genotype did not significantly affect drug pharmacokinetics: AUC ratios between mutant-allele carriers and wild-type volunteers were 1.27 (95% confidence interval [CI] 0.84-1.92) and 1.20 (95% CI 0.96-1.51) for dabigatran and rivaroxaban, respectively. Clarithromycin coadministration led to a two-fold increase in both drugs' AUC, irrespective of ABCB1 genotype: ratios of geometric means were 2.0 (95% CI 1.15-3.60) and 1.94 (95% CI 1.42-2.63) for dabigatran and rivaroxaban, respectively. Conclusions ABCB1 genotype is not a significant determinant of interindividual variability in dabigatran and rivaroxaban pharmacokinetics. The levels of one drug did not predict the levels of the other. Coadministration of a P-gp/CYP3A4 inhibitor with dabigatran or rivaroxaban may warrant caution in patients at risk of overexposure.
AIMThe aim of this study was to develop a PK/PD model to assess drug-drug interactions between dabigatran and P-gp modulators, using the example of clarithromycin, a strong inhibitor of P-gp. METHODSTen healthy male volunteers were randomized to receive in the first treatment period a single 300 mg dose of dabigatran etexilate (DE) and in the second treatment period 500 mg clarithromycin twice daily during 3 days and then 300 mg DE plus 500 mg clarithromycin on the fourth day, or the same treatments in the reverse sequence. Dabigatran plasma concentration and ecarin clotting time (ECT) were measured on 11 blood samples. Models were built using a non-linear mixed effect modelling approach. RESULTSThe best PK model was based on an inverse Gaussian absorption process with two compartments. The relationship between dabigatran concentration and ECT was implemented as a linear function. No continuous covariate was associated with a significant decrease in the objective function. The concomitant administration of clarithromycin induced a significant change only in DE bioavailability, which increased from 6.5% to 10.1% in the presence of clarithromycin. Clarithromycin increased peak concentration and AUC by 60.2% and 49.1% respectively. CONCLUSIONThe model proposed effectively describes the complex PK of dabigatran and takes into account drug-drug interactions with P-gp activity modulators, such as clarithromycin. WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• Dabigatran etexilate has a bioavailability of 6.5% due to a complex absorption process.• Dabigatran etexilate is a substrate for P-gp and its reflux can be modulated by other drugs.• P-gp inhibitors increase the AUC of dabigatran from about 50% to over 200%. WHAT THIS STUDY ADDS• The pharmacokinetics and pharmacodynamics of dabigatran were described by a two compartment model with an absorption following an inverse Gaussian law, associated with a linear effect model. • We showed that this phenomenon is explained solely by an increase in bioavailability from 6.5 to 10%. • Exposure to dabigatran is increased by 50% in the presence of clarithromycin and is characterized by substantial variability.
This study allowed identification of three different profiles of ABC carrier-mediated transport: predominantly P-gp-dependent transport (dabigatran), preferential BCRP-dependent transport (apixaban) and approximately equivalent P-gp and BCRP-mediated transport (edoxaban and rivaroxaban).
Over the past decades, haemophilia management has continually evolved, with prophylaxis now considered the treatment of choice. Prophylaxis primarily seeks to prevent bleeding and haemarthrosis episodes from occurring and avert the otherwise inevitable haemophilic arthropathy. Yet, numerous unanswered issues remain. These concern dose levels, dosing intervals, ways of integrating variability in bleeding phenotype, patient age, joint status, lifestyle, physical activity, treatment adherence and individual responses to FVIII or FIX concentrates. Individualized prophylaxis may thus be paramount. One crucial tool that may allow more accurate prophylaxis regimens to be implemented is the individual pharmacokinetic (PK) study. Therefore, physicians in charge of managing those living with haemophilia must be comfortable with PK profiling in order to be in a position to tailor patients' treatment, taking into account PK data, while minimizing patients' inconvenience, discomfort, as well as, possibly, treatment costs. For optimization of prophylaxis, recent development of recombinant molecules with more attractive PK properties, such as prolonged elimination half-life, increases the choice of dosing regimens, enabling decreased frequency of dosing for some, if deemed appropriate. For each patient, PK parameters can be determined, including trough levels, AUC, and time spent under a predefined threshold, with additional pharmacodynamic (PD) parameters possibly established by means of a global coagulation test like the thrombin generation test. Most importantly, target PK/PD parameters will need to consider clinical variables like patient age, body weight, joint status, treatment adherence, number of bleeding episodes, activity index or lifestyle.
Introduction: Lupus Anticoagulant (LA) testing using dilute Russell Viper Venom Time (dRVVT) is challenging in patients receiving Direct Oral AntiCoagulants (DOAC) due to potential false positive results. In a multicenter study, we evaluated the in vitro removal of DOAC by activated charcoal (DOAC remove ®), allowing reliable dRVVT testing. Materials and Methods: Patient samples were analyzed before and after treatment with DOAC remove ® : 49 apixaban, 48 rivaroxaban, 24 dabigatran and 30 none. DOAC plasma concentrations were measured using anti-Xa or anti-IIa diluted thrombin time assays. In a subset of 28 samples, DOAC concentrations were also measured using HPLC-MS/MS following treatment with DOAC remove ®. DRVVT was performed using STA-Staclot dRVVT Screen ® /Confirm ® (Stago) or LAC-Screening ® /Confirm ® (Siemens). Results: Baseline median [min-max] concentrations were 94 [<20-479] for apixaban, 107 [<20-501] for rivaroxaban and 135 ng/mL [<20-792] for dabigatran; dRVVT screen ratio /confirm normalized ratio was positive in 47, 90 and 42 % of apixaban, rivaroxaban and dabigatran samples. Treatment with DOAC remove ® did not affect dRVVT results in non-DOAC patients while it resulted in DOAC concentrations < 20 ng/mL in 82, 98 and 100 % of samples, respectively. Concentrations were < 5 ng/mL with HPLC-MS/MS in 5 out of 10, 8 out of 10 and 7 out of 8 samples, respectively. DOAC remove ® corrected DOAC interference with dRVVT assays allowed excluding LA in 76, 85 and 95 % of the patients, respectively. without affecting dRVVT results in non-DOAC patients. Conclusion: For dRVVT testing in DOAC patients, we suggest the use of DOAC remove ® for every rivaroxaban sample, whereas it might only be used in positive apixaban and dabigatran samples. A residual DOAC interference cannot be ruled out in case of persisting dRVVT positive results after treatment with DOAC remove ®. For those with persisting positive results, LA-diagnosis using dRVVT remains questionable.
Background Rivaroxaban is a direct factor Xa inhibitor with substantial inter‐individual pharmacokinetic (PK) variability. Pharmacodynamic (PD) variability, especially assessed with thrombin generation (TG), has been less documented. Objectives (i) To assess TG parameter time profiles in healthy volunteers, with TG being studied under different conditions and (ii) to model the relationship between rivaroxaban concentrations and TG parameters and subsequently estimate interindividual variability. Methods Sixty healthy male volunteers (DRIVING‐NCT01627665) received a single 40‐mg rivaroxaban dose. Blood sampling was performed at baseline and 10 predefined time points over 24 h. The TG was investigated with the fully automated ST‐Genesia system (Stago), using two tissue‐factor (TF) concentrations, in the absence (−), or presence (+) of thrombomodulin (TM) for the lowest one. The PD models were built to characterize the relationships between plasma rivaroxaban concentrations and endogenous thrombin potential (ETP) or peak height induced by the lowest TF concentration. Results Thrombin generation parameter time profiles with the lowest TF concentration showed a good sensitivity to rivaroxaban, especially +TM (active protein C negative feedback). The relationship between rivaroxaban concentrations and TG parameters was modeled with a sigmoidal relation. Mean rivaroxaban concentrations halving the baseline value of ETP and peak height (−TM) (C50) were of 284 and 33.2 ng/mL, respectively: +TM, C50 declined to 19.4 and 13.8 ng/mL, reflecting a powerful inhibitory effect. The estimated C50 population coefficients of variation were of 12.2% (−TM) and 31.3% (+TM) with the peak height models, 34.8% (+TM) with the ETP model. Conclusions This low‐rivaroxaban to moderate‐rivaroxaban PD variability in healthy volunteers contrasts with the substantial PK variability and deserves to be studied in different patient settings.
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