Comparing Mechanistic and Preclinical Predictions of Volume of Distribution on a Large Set of Drugs

Purpose Volume of distribution at steady state (V is a fundamental pharmacokinetic (PK) parameter driven predominantly by passive processes and physicochemical properties of the compound. Human Vd(ss) can be estimated using in silico mechanistic methods or empirically scaled from Vd(ss) values obtained from preclinical species. In this study the accuracy and the complementarity of these two approaches are analyzed leveraging a large data set (over 150 marketed drugs). Methods For all the drugs analyzed in this study experimental in vitro measurements of LogP, plasma protein binding and pKa are used as input for the mechanistic in silico model to predict human Vd(ss) . The software used for predicting human tissue partition coefficients and Vd(ss) based on the method described by Rodgers and Rowland is made available as supporting information. Results This assessment indicates that overall the in silico mechanistic model presented by Rodgers and Rowland is comparably accurate or superior to empirical approaches based on the extrapolation of in vivo data from predinical species. Conclusions These results illustrate the great potential of mechanistic in silico models to accurately predict Vd ss in humans. This in silico method does not rely on in vivo data and is, consequently, significantly time and resource sparing. The success of this in silico model further suggests that reasonable predictability of Vd(ss) in predinical species could be obtained by a similar process.