Prediction of hepatic metabolic clearance based on interspecies allometric scaling techniques and in vitro-in vivo correlations

Clin Pharmacokinet. 1999 Mar;36(3):211-31. doi: 10.2165/00003088-199936030-00003.


This article reviews the methods available for predicting hepatic metabolic clearance in humans, and discusses their application to the processes of drug discovery and development. The application of these techniques has increased markedly during the past few years because of the improved availability of human liver samples, which has increased the opportunities to use in vitro studies to predict human clearance. The techniques available involve both empirical and physiologically based approaches. Allometric scaling using in vitro data from animals and humans combines certain aspects of both approaches. An evaluation of data retrieved from the literature indicates that, together with in vitro human data, allometric scaling based on a combination of in vitro and in vivo preclinical data can accurately predict clearance in humans. With this approach, 80% of the predictions were within a 2-fold factor of actual human clearance values, with an overall accuracy of 1.6-fold. The uncertainties and inaccuracies in predicting human clearance are related to: (i) the specific method that is used to make the prediction; (ii) the experimental design and the model used to determine the in vitro clearance; (iii) protein binding within the in vitro test system; and (iv) various in vivo factors such as the involvement of extrahepatic metabolism and active transport processes, interindividual variability and nonlinearity in pharmacokinetics. In contrast to purely empirical approaches, the physiological approach to predicting clearance gives an opportunity to integrate some of these complexities and, therefore, should provide more confidence in the prediction of clearance in humans.

Publication types

  • Comparative Study
  • Review

MeSH terms

  • Animals
  • Body Weight / physiology*
  • Humans
  • Liver / metabolism*
  • Pharmacokinetics*
  • Predictive Value of Tests
  • Species Specificity