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A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics

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Abstract

Background

The major aim of this study was to develop a strategy for predicting human pharmacokinetics using physiologically based pharmacokinetic (PBPK) modelling. This was compared with allometry (of plasma concentration-time profiles using the Dedrick approach), in order to determine the best approaches and strategies for the prediction of human pharmacokinetics.

Methods

PBPK and Dedrick predictions were made for 19 F. Hoffmann-La Roche compounds. A strategy for the prediction of human pharmacokinetics using PBPK modelling was proposed in this study. Predicted values (pharmacokinetic parameters, plasma concentrations) were compared with observed values obtained after intravenous and oral administration in order to assess the accuracy of the prediction methods.

Results

By following the proposed strategy for PBPK, a prediction would have been made prospectively for approximately 70% of the compounds. The prediction accuracy for these compounds in terms of the percentage of compounds with an average-fold error of <2-fold was 83%, 50%, 75%, 67%, 92% and 100% for apparent oral clearance (CL/F), apparent volume of distribution during terminal phase after oral administration (Vz/F), terminal elimination half-life (t½), peak plasma concentration (Cmax), area under the plasma concentration-time curve (AUC) and time to reach Cmax (tmax), respectively. For the other 30% compounds, unacceptable prediction accuracy was obtained in animals; therefore, a prospective prediction of human pharmacokinetics would not have been made using PBPK. For these compounds, prediction accuracy was also poor using the Dedrick approach. In the majority of cases, PBPK gave more accurate predictions of pharmacokinetic parameters and plasma concentration-time profiles than the Dedrick approach.

Conclusions

Based on the dataset evaluated in this study, PBPK gave reasonable predictions of human pharmacokinetics using preclinical data and is the recommended approach in the majority of cases. In addition, PBPK modelling is a useful tool to gain insights into the properties of a compound. Thus, PBPK can guide experimental efforts to obtain the relevant information necessary to understand the compound’s properties before entry into human, ultimately resulting in a higher level of prediction accuracy.

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Notes

  1. The use of trade names is for product identification purposes only and does not imply endorsement.

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Acknowledgements

The authors would like to thank Patrick Poulin, Alex MacDonald and Frank-Peter Theil for their assistance in this study. This work was supported by F. Hoffman La Roche. The authors have no conflicts of interest directly relevant to the content of this study.

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Authors and Affiliations

  1. Drug Metabolism and Pharmacokinetics, F. Hoffmann-La Roche Ltd, Basel, Switzerland

    Hannah M. Jones, Neil Parrott & Thierry Lavé

  2. Clinical Pharmacology, F. Hoffmann-La Roche Ltd, Basel, Switzerland

    Karin Jorga

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  1. Hannah M. Jones
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  2. Neil Parrott
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Correspondence to Hannah M. Jones.

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Jones, H.M., Parrott, N., Jorga, K. et al. A Novel Strategy for Physiologically Based Predictions of Human Pharmacokinetics. Clin Pharmacokinet 45, 511–542 (2006). https://doi.org/10.2165/00003088-200645050-00006

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