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

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.