Physiologically Based Pharmacokinetic Modeling of Tofacitinib: Predicting Drug Exposure and Optimizing Dosage in Special Populations and Drug-Drug Interaction Scenarios.

Abstract

Background: Tofacitinib is mainly used in the adult population for immune-mediated inflammatory diseases. There is little information available on the pharmacokinetics of tofacitinib in pediatric patients, populations with hepatic impairment and renal impairment, and patients with drug-drug interactions (DDIs). This study aimed to develop a physiologically based pharmacokinetic (PBPK) model to predict the pharmacokinetics of tofacitinib in the populations mentioned above. Methods: We developed the PBPK models in PK-Sim^® and evaluated the models with observed clinical PK data. The Monte Carlo algorithm was used for parameter identification. Results: The adult PBPK model accurately simulated the pharmacokinetic profiles of all administration scenarios. The geometric mean fold errors for the predicted/observed maximum concentration and area under the curve are 1.17 and 1.16, respectively. The extrapolated models accurately simulated the pharmacokinetic characteristics of tofacitinib. The pediatric patients aged 12-to-<18 years and 2-to-<6 years need to adjust the dose to 4 mg BID and 1.7 mg BID, respectively, to achieve comparable steady-state exposures to 5 mg BID in adults. The populations with moderate hepatic impairment and severe renal impairment need to reduce the dose to 50% and 75% of the original dose, respectively. Tofacitinib should be reduced to 50% and 65% of the original dose for concomitant use with fluconazole and ketoconazole, respectively, and increased to 150% of the original dose for concomitant use with rifampicin. Conclusions: We developed a tofacitinib PBPK model and extrapolated it to special populations and DDIs. The predictive results of the models can help the rational use of tofacitinib in these populations.