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. 2022 Nov;11(11):1430-1442.
doi: 10.1002/psp4.12844. Epub 2022 Oct 3.

Application of physiologically-based pharmacokinetic model approach to predict pharmacokinetics and drug-drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine

Affiliations

Application of physiologically-based pharmacokinetic model approach to predict pharmacokinetics and drug-drug interaction of rivaroxaban: A case study of rivaroxaban and carbamazepine

Lien Thi Ngo et al. CPT Pharmacometrics Syst Pharmacol. 2022 Nov.

Abstract

Rivaroxaban (RIV; Xarelto; Janssen Pharmaceuticals, Beerse, Belgium) is one of the direct oral anticoagulants. The drug is a strong substrate of cytochrome P450 (CYP) enzymes and efflux transporters. This study aimed to develop a physiologically-based pharmacokinetic (PBPK) model for RIV. It contained three hepatic metabolizing enzyme reactions (CYP3A4, CYP2J2, and CYP-independent) and two active transporter-mediated transfers (P-gp and BCRP transporters). To illustrate the performance of the developed RIV PBPK model on the prediction of drug-drug interactions (DDIs), carbamazepine (CBZ) was selected as a case study due to the high DDI potential. Our study results showed that CBZ significantly reduces the exposure of RIV. The area under the concentration-time curve from zero to infinity (AUCinf ) of RIV was reduced by 35.2% (from 2221.3 to 1438.7 ng*h/ml) and by 25.5% (from 2467.3 to 1838.4 ng*h/ml) after the first dose and at the steady-state, respectively, whereas the maximum plasma concentration (Cmax ) of RIV was reduced by 37.7% (from 266.3 to 166.1 ng/ml) and 36.4% (from 282.3 to 179.5 ng/ml), respectively. The developed PBPK model of RIV could be paired with PBPK models of other interested perpetrators to predict DDI profiles. Further studies investigating the extent of DDI between CBZ and RIV should be conducted in humans to gain a full understanding of their safety and effects.

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Conflict of interest statement

The authors declared no competing interests in this work.

Figures

FIGURE 1
FIGURE 1
The workflow of the PBPK model development and evaluation for RIV and its application to predict drug–drug interaction between RIV and CBZ in humans. AUCinf, area under the concentration‐time curve from zero to infinity; CBZ, carbamazepine; Cmax, maximum plasma concentration; K cat, catalytic/transport rate constant; K m, Michaelis–Menten constant; PBPK, physiologically‐based pharmacokinetic; PK, pharmacokinetic; RIV, rivaroxaban.
FIGURE 2
FIGURE 2
Predicted and observed plasma concentration–time curves of RIV after oral administration of RIV in healthy subjects. Training dataset. Solid lines are predicted values of each model. Circles are clinical observations. Details on dosing regimens, characteristics, subject demographics, and references are listed in Table S1. RIV, rivaroxaban.
FIGURE 3
FIGURE 3
Predicted and observed plasma concentration–time curves of RIV after oral administration of RIV in healthy subjects. Test dataset. Solid lines are predicted values of each model. Circles are clinical observations. Details on dosing regimens, characteristics, subject demographics, and references are listed in Table S1. RIV, rivaroxaban.
FIGURE 4
FIGURE 4
Goodness‐of‐fit plots for the developed PBPK model of RIV for the prediction of (a) plasma concentration, (b) C max, and (c) AUCinf. The line of identity is presented as a solid line; 1.25‐fold dimensions and 2.0‐fold dimensions are shown using dotted lines and dashed lines, respectively. AUCinf, area under the concentration‐time curve from zero to infinity; Cmax, maximum plasma concentration; PBPK, physiologically‐based pharmacokinetic; RIV, rivaroxaban.
FIGURE 5
FIGURE 5
Simulated plasma concentration–time profiles of RIV in humans after oral administration at a dose of 20 mg/day with or without the co‐administration of CBZ at a dose of 900 mg/day. CBZ, carbamazepine; RIV, rivaroxaban.

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