Prediction of human pharmacokinetics--improving microsome-based predictions of hepatic metabolic clearance.

摘要

Physiologically based methods generally perform poorly in predicting in-vivo hepatic CL (CL(H)) from intrinsic clearance (CL(int)) in microsomes in-vitro and unbound fraction in blood (f(u,bl)). Various strategies to improve the predictability have been developed, and inclusion of an empirical scaling factor (SF) seems to give the best results. This investigation was undertaken to evaluate this methodology and to find ways to improve it further. The work was based on a diverse data set taken from Ito and Houston (2005). Another objective was to evaluate whether rationalization of CL(H) predictions can be made by replacing blood/plasma-concentration ratio (C(bl)/C(pl)) measurements with SFs. There were apparently no or weak correlations between prediction errors and lipophilicity, permeability (compounds with low permeability missing in the data set) and main metabolizing CYP450s. The use of CL(int) class (high/low) and drug class (acid/baseeutral) SFs (the CD-SF method) gives improved and reasonable predictions: 1.3-fold median error (an accurate prediction has a 1-fold error), 76% within 2-fold-error, and a median absolute rank ordering error of 2 for CL(H) (n = 29). This approach is better than the method with a single SF. Mean (P < 0.05) and median errors, fraction within certain error ranges, higher percentage with most accurate predictions, and ranking were all better, and 76% of predictions were more accurate with this new method. Results are particularly good for bases, which generally have higher CL(H) and the potential to be incorrectly selected/rejected as candidate drugs. Reasonable predictions of f(u,bl) can be made from plasma f(u) (f(u,pl)) and empirical blood cell binding SFs (B-SFs; 1 for low f(u,pl) acids; 0.62 for other substances). Mean and median f(u,bl) prediction errors are negligible. The use of the CD-SF method with predicted f(u,bl) (the BCD-SF method) also gives improved and reasonable results (1.4-fold median error; 66% within 2-fold-error; median absolute rank ordering error =1). This new empirical approach seems sufficiently good for use during the early screening; it gives reasonable estimates of CL(H) and good ranking, which allows replacement of C(bl)/C(pl) measurements by a simple equation.