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01.08.2011 | Original Research Article | Ausgabe 8/2011

Clinical Pharmacokinetics 8/2011

Prediction of Human Oral Plasma Concentration-Time Profiles Using Preclinical Data

Comparative Evaluation of Prediction Approaches in Early Pharmaceutical Discovery

Clinical Pharmacokinetics > Ausgabe 8/2011
An Van den Bergh, Vikash Sinha, Ron Gilissen, Roel Straetemans, Koen Wuyts, Denise Morrison, Luc Bijnens, Dr Claire Mackie
Wichtige Hinweise

Electronic Supplementary Material

Supplementary material is available for this article at 10.​2165/​11587230-000000000-00000 and is accessible for authorized users.


Background and Objectives: Empirically based methods remain one of our tools in human pharmacokinetic predictions. The Dedrick approach and the steady-state plasma drug concentration (Css)-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 Css-MRT approach is based on the implementation of measured animal and predicted human MRT and dose/volume of distribution at steady state (Vss). 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.
Methods: 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 Css-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 Css-MRT approach, we used formulas based on multivariate regression analysis as input for the transformation.
Results: Inclusion of correction factors significantly improved the profile predictability for the Dedrick and Css-MRT approaches. This was mainly linked to an improved prediction of terminal elimination half-life (t1/2), MRT and the ratio between the maximum plasma concentration and the concentration at the last observed time point (Cmax/Clast). No significant differences were observed between the Dedrick approach with correction factors, the Css-MRT approach with correction factors and the Css-MRT approach, based on the regression equations.
Conclusions: 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 Css-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.

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