Prediction of volume of distribution at steady state in humans: comparison of different approaches

Abstract

Introduction: Reasonable prediction of volume of distribution at steady state (Vd_ss) in humans is required for screening drug candidates, evaluating drug safety, and estimating first-in-human doses.

Areas covered: This review summarizes methods for the prediction of human Vd_ss and tissue plasma partition coefficients (K_p). The methods reviewed includes allometric scaling, physiologically based models, correlation with animal Vd_ss and in silico models. The assumptions, equations, input data required, advantages, and limitations of each approach are discussed. Due to the variations among test datasets, some studies have reached inconsistent conclusions. Hence, a comprehensive comparison of various approaches using a large and exhaustive dataset is warranted to address the controversies in human Vd_ss prediction.

Expert opinion: Compared with allometric scaling, the Oie–Tozer method and correlations between human and animal Vd_ss are more accurate. All the three methods can be used for accurate predictions of human Vd_ss just prior to first-in-human studies. Although in vivo animal data are not required, tissue composition-based approaches and inter-tissue correlation of K_p provide reasonable predictive accuracies and are promising for physiologically based pharmacokinetic modeling. The in silico models are most suitable for high-throughput screening of compounds, which are at an early stage of development.

Keywords::

• allometric scaling
• in silico prediction
• physiologically based prediction
• tissue composition-based prediction
• tissue–plasma partition coefficient
• volume of distribution at steady state

Notes

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