PhRMA CPCDC Initiative on Predictive Models of Human Pharmacokinetics, Part 2: Comparative Assessment of Prediction Methods of Human Volume of Distribution

The objective of this study was to evaluate the performance of various empirical, semimechanistic and mechanistic methodologies with and without protein binding corrections for the prediction of human volume of distribution at steady state (V(ss)). PhRMA member companies contributed a set of blinded data from preclinical and clinical studies, and 18 drugs with intravenous clinical pharmacokinetics (PK) data were available for the analysis. In vivo and in vitro preclinical data were used to predict V(ss) by 24 different methods. Various statistical and outlier techniques were employed to assess the predictability of each method. There was not simply one method that predicts V(ss) accurately for all compounds. Across methods, the maximum success rate in predicting human V(ss) was 100%, 94%, and 78% of the compounds with predictions falling within tenfold, threefold, and twofold error, respectively, of the observed V(ss). Generally, the methods that made use of in vivo preclinical data were more predictive than those methods that relied solely on in vitro data. However, for many compounds, in vivo data from only two species (generally rat and dog) were available and/or the required in vitro data were missing, which meant some methods could not be properly evaluated. It is recommended to initially use the in vitro tissue composition-based equations to predict V(ss) in preclinical species and humans, putting the assumptions and compound properties into context. As in vivo data become available, these predictions should be reassessed and rationalized to indicate the level of confidence (uncertainty) in the human V(ss) prediction. The top three methods that perform strongly at integrating in vivo data in this way were the Oie-Tozer, the rat -dog-human proportionality equation, and the lumped-PBPK approach. Overall, the scientific benefit of this study was to obtain greater characterization of predictions of human V(ss) from several methods available in the literature. (C) 2011 Wiley-Liss, Inc. and the American Pharmacists Association J Pharm Sci 100: 4074-4089, 2011