Physiologically based pharmacokinetic model of renally cleared antibacterial drugs in Chinese renal impairment patients.

Purpose To preliminarily develop physiologically based population models for Chinese renal impairment patients and to evaluate the prediction performance of new population models by renally cleared antibacterial drugs. Methods Firstly, demographic data and physiological parameters of Chinese renal impairment patients were collected, and then the coefficients of the relative demographic and physiological equation were recalibrated to construct the new population models. Secondly, drug independent parameters of ceftazidime, cefodizime, vancomycin, and cefuroxime were collected and verified by Chinese healthy volunteers, Caucasian healthy volunteers, Caucasian renal impairment population models built in Simcyp. Finally, the newly developed population models were applied to predict the plasma concentration of four antibacterial drugs in Chinese renal impairment patients. Results The new PBPK population models can predict the main pharmacokinetic parameters, including area under the plasma concentration-time curve extrapolated to infinity (AUCinf ), renal clearance (CLr ) and peak concentration (Cmax ), of ceftazidime, cefodizime, vancomycin, and cefuroxim following intravenous administrations with less than 2-fold error in mild, moderate, and severe Chinese renal impairment patients. The accuracy and precision of the predictions were improved compared with the Chinese healthy volunteers and Caucasian renal impairment population models. Conclusions The PBPK population models were preliminarily developed and first step validation results of four antibacterial drugs following intravenous administration showed acceptable accuracy and precision. The population models still need more systematic validation by using more drugs and scenarios in future studies to support their applications on dosage recommendation for Chinese renal impairment patients. This article is protected by copyright. All rights reserved.