A physiologically based pharmacokinetic model to predict the pharmacokinetics of highly protein-bound drugs and the impact of errors in plasma protein binding

作者：Ye Min; Nagar Swati; Korzekwa Ken^*

来源：Biopharmaceutics & Drug Disposition, 2016, 37(3): 123-141.

DOI：10.1002/bdd.1996

• physiologically based pharmacokinetic (PBPK) modeling
• protein binding
• distribution volume
• hepatic metabolism

Predicting the pharmacokinetics of highly protein-bound drugs is difficult. Also, since historical plasma protein binding data were often collected using unbuffered plasma, the resulting inaccurate binding data could contribute to incorrect predictions. This study uses a generic physiologically based pharmacokinetic (PBPK) model to predict human plasma concentration-time profiles for 22 highly protein-bound drugs. Tissue distribution was estimated from in vitro drug lipophilicity data, plasma protein binding and the blood: plasma ratio. Clearance was predicted with a well-stirred liver model. Underestimated hepatic clearance for acidic and neutral compounds was corrected by an empirical scaling factor. Predicted values (pharmacokinetic parameters, plasma concentration-time profile) were compared with observed data to evaluate the model accuracy. Of the 22 drugs, less than a 2-fold error was obtained for the terminal elimination half-life (t(1/2), 100% of drugs), peak plasma concentration (C-max, 100%), area under the plasma concentration-time curve (AUC(0-t), 95.4%), clearance (CLh, 95.4%), mean residence time (MRT, 95.4%) and steady state volume (V-ss, 90.9%). The impact of f(up) errors on CLh and V-ss prediction was evaluated. Errors in f(up) resulted in proportional errors in clearance prediction for low-clearance compounds, and in V-ss prediction for high-volume neutral drugs. For high-volume basic drugs, errors in f(up) did not propagate to errors in V-ss prediction. This is due to the cancellation of errors in the calculations for tissue partitioning of basic drugs. Overall, plasma profiles were well simulated with the present PBPK model.

• 出版日期2016-4