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Pharm Res. 2005 Jan;22(1):103-12.

Prediction of human drug clearance from in vitro and preclinical data using physiologically based and empirical approaches.

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1
School of Pharmacy and Pharmaceutical Sciences, University of Manchester, Manchester M13 9PL, UK.

Abstract

PURPOSE:

The aim of this study is to compare the accuracy of five methods for predicting in vivo intrinsic clearance (CL(int)) and seven for predicting hepatic clearance (CL(h)) in humans using in vitro microsomal data and/or preclinical animal data.

METHODS:

The human CL(int) was predicted for 33 drugs by five methods that used either in vitro data with a physiologic scaling factor (SF), with an empirical SF, with the physiologic and drug-specific (the ratio of in vivo and in vitro CL(int) in rats) SFs, or rat CL(int) directly and with allometric scaling. Using the estimated CL(int), the CL(h) in humans was calculated according to the well-stirred liver model. The CL(h) was also predicted using additional two methods: using direct allometric scaling or drug-specific SF and allometry.

RESULTS:

Using in vitro human microsomal data with a physiologic SF resulted in consistent underestimation of both CL(int) and CL(h). This bias was reduced by using either an empirical SF, a drug-specific SF, or allometry. However, for allometry, there was a substantial decrease in precision. For drug-specific SF, bias was less reduced, precision was similar to an empirical SF. Both CL(int) and CL(h) were best predicted using in vitro human microsomal data with empirical SF. Use of larger data set of 52 drugs with the well-stirred liver model resulted in a best-fit empirical SF that is 9-fold increase on the physiologic SF.

CONCLUSIONS:

Overall, the empirical SF method and the drug-specific SF method appear to be the best methods; they show lower bias than the physiologic SF and better precision than allometric approaches. The use of in vitro human microsomal data with an empirical SF may be preferable, as it does not require extra information from a preclinical study.

PMID:
15771236
[Indexed for MEDLINE]

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