Simulation of febuxostat pharmacokinetics in healthy subjects and patients with impaired kidney function using physiologically based pharmacokinetic modeling

Authors: Xu Y, Chen J, Ruan Z
Publication: Biopharm Drug Dispos
Software: GastroPlus®


Febuxostat is recommended by the American College of Rheumatology Gout Management Guidelines as a first-line therapy for lowering the level of urate in patients with gout. At present, this drug is being prescribed mainly based on the clinical experience of doctors. The potential effects of clinical and demographic variables on the bioavailability and therapeutic effectiveness of febuxostat are not being considered. In this study a physiologically based pharmacokinetic (PBPK) model of febuxostat was developed, thereby providing a theoretical basis for the individualized dosing of this drug in gout patients. The plasma concentration–time profiles corresponding to healthy subjects and gout patients with normal kidney function were simulated and validated; then, the model was used to predict the pharmacokinetic (PK) data of the drug in gout patients suffering from varying degrees of impaired kidney function. The error values (the predicted value/observed value) were used to validate the simulated PK parameters predicted by the PBPK model, including the area under the plasma concentration–time curve, the maximum plasma concentration, and time to maximum plasma concentration. Considering that to all error fold changes were smaller than 2, the PBPK model was. In subjects suffering from mild kidney impairment, moderate kidney impairment, severe kidney impairment, and endstage kidney disease (ESRD), the predicted AUC0-24h values increased by 1.62, 1.74, 2.27, and 2.65-fold, respectively, compared to gout patients with normal kidney function. Overall, the results showed that the PBPK model constructed in this study predict the pharmacokinetic changes in gout patients suffering from varying degrees of impaired kidney function.

By Yichao Xu, Jinliang Chen, Zourong Ruan, Bo Jiang, Dandan Yang, Yin Hu, Honggang Lou