Received for publication April 8, 2005.
Revised October 10, 2005.
Accepted for publication October 11, 2005.

Application of a generic physiologically-based pharmacokinetic model to the estimation of xenobiotic levels in rat plasma

Abstract

The routine assessment of xenobiotic in vivo kinetic behaviour is currently dependent upon data obtained through animal experimentation, although in vitro surrogates for determining key absorption, distribution, metabolism and elimination (ADME) properties are available. Here we present a unique, generic, physiologically-based pharmacokinetic (PBPK) model, and demonstrate its application to the estimation of rat plasma pharmacokinetics, following intravenous dosing, from in vitro data alone. The model was parameterized through an optimization process, employing a training set of in vivo data taken from the literature, and validated using a separate test set of in vivo discovery compound data. On average, the vertical divergence of the predicted plasma concentrations from the observed data, on a semi-log concentration-time plot, was approximately 0.5 log units. Around 70% of all the predicted values of a standardized measure of AUC were within threefold of the observed values, as were over 90% of the training set t predictions and 60% of those for the test set; however, there was a tendency to over-predict t for the test set compounds. The capability of the model to rank compounds according to a given criterion was also assessed: of the 25% of the test set compounds ranked by the model as having the largest values for AUC, 61% were correctly identified. These validation results lead us to conclude that the generic PBPK model is potentially a powerful and cost-effective tool for predicting the mammalian pharmacokinetics of a wide range of organic compounds, from readily-available in vitro inputs only.

Key words: computational models, computer modeling and simulation, in vitro-in vivo prediction, mathematical modeling, Monte Carlo simulations, pharmacokinetic modeling, physiologically-based modeling, physiologically-based pharmacokinetics

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