Prediction of volume of distribution in humans: analysis of eight methods and their application in drug discovery.

The performance of eight different methods to predict human volume of distribution (VDss) using a large data set (N > 100) was evaluated. The accuracy was assessed by the end points % within two-fold and absolute average fold error (AAFE). The ability to rank order was accessed by the sigma and bias was examined using average fold error. Significance of observed differences was established using statistical permutation testing. The Rodgers-Lukova equation, a tissue composition model, for acids and single species scaling based on rat for other ion classes showed the best results in absence of non-rodent data. The semimechanistic oie-Tozer model based on all thee preclinical species showed the best performance overall (81% within two-fold, AAFE 1.55, sigma 0.62). This was not statistically significantly better at the 95% confidence level than the same model based on two preclinical species or single species scaling from monkey. Thus, the use of primates appears difficult to justify when the sole goal is to extrapolate human volume of distribution.