Application of physiologically based pharmacokinetic modeling to the prediction of drug-drug and drug-disease interactions for rivaroxaban.

PURPOSE

Rivaroxaban 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.

METHODS

A 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.

RESULTS

The 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.

CONCLUSIONS

Our 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.