Prediction of human oral plasma concentration-time profiles using preclinical data: comparative evaluation of prediction approaches in early pharmaceutical discovery.
Empirically based methods remain one of our tools in human pharmacokinetic predictions. The Dedrick approach and the steady-state plasma drug concentration (C(ss))-mean residence time (MRT) approach are based on the assumption that concentration-time profiles are similar among species, including man, and that curves derived from a variety of animal species can be superimposed after mathematical transformation. In the Dedrick approach the transformation is based on the slope and intercept of the allometric relationship. The C(ss)-MRT approach is based on the implementation of measured animal and predicted human MRT and dose/volume of distribution at steady state (V(ss)). The aims of the present study were to compare the predictive performance of concentration-time profiles obtained by these approaches, to evaluate the prediction of individual pharmacokinetic parameters by these approaches and to further refine these approaches incorporating the experience from our previous work. A retrospective analysis using 35 proprietary compounds developed at Johnson & Johnson Pharmaceutical Research and Development was conducted to compare the accuracies of the Dedrick and C(ss)-MRT approaches for predicting oral concentration-time profiles and pharmacokinetic parameters in man. In the first step, input for the transformation was based on simple allometry. Then we assessed whether both methods could be fine-tuned by systematically incorporating correction factors (maximum life span potential, brain weight and plasma protein binding), depending on the interspecies relationship. In addition, for the C(ss)-MRT approach, we used formulas based on multivariate regression analysis as input for the transformation. Inclusion of correction factors significantly improved the profile predictability for the Dedrick and C(ss)-MRT approaches. This was mainly linked to an improved prediction of terminal elimination half-life (t(½)), MRT and the ratio between the maximum plasma concentration and the concentration at the last observed time point (C(max)/C(last)). No significant differences were observed between the Dedrick approach with correction factors, the C(ss)-MRT approach with correction factors and the C(ss)-MRT approach, based on the regression equations. Based on the dataset evaluated in this study, we demonstrated that human plasma concentration-time profiles and pharmacokinetic parameters could be predicted with the Dedrick and C(ss)-MRT approaches and that if correction factors were implemented, the predictions improved significantly. With the requirement of only a limited preclinical in vivo pharmacokinetic dataset, these empirical methods could offer potential in the early stages of drug discovery.