Abstract

Volume of distribution and fraction unbound are two key parameters in pharmacokinetics. The fraction unbound describes the portion of free drug in plasma that may extravasate, while volume of distribution describes the tissue access and binding of a drug. Reliable in silico predictions of these pharmacokinetic parameters would benefit the early stages of drug discovery, as experimental measuring is not feasible for screening purposes. We have applied linear and nonlinear multivariate approaches to predict these parameters: linear partial least square regression and non-linear recursive partitioning classification. The volume of distribution and fraction of unbound drug in plasma are predicted in parallel within the model, since the two are expected to be affected by similar physicochemical drug properties. Predictive models for both parameters were built and the performance of the linear models compared to models included in the commercial software Volsurf+. Our models performed better in predicting the unbound fraction (Q2 0.54 for test set compared to 0.38 with Volsurf+ model), but prediction accuracy of the volume of distribution was comparable to the Volsurf+ model (Q2 of 0.70 for test set compared to 0.71 with Volsurf+ model). The nonlinear classification models were able to identify compounds with a high or low volume of distribution (sensitivity 0.81 and 0.71, respectively, for test set), while classification of fraction unbound was less successful. The interrelationship between the volume of distribution and fraction unbound is investigated and described in terms of physicochemical descriptors. Lipophilicity and solubility descriptors were found to have a high influence on both volume of distribution and fraction unbound, but with an inverse relationship.

Highlights

  • The extent of drug distribution determines the access of a drug to its sites of action and to other tissues, which might give rise to adverse effects

  • Erythropoietin is confined to the vascular space presenting a volume of distribution (Vd) of 4 L [1], while hydroxychloroquine with a Vd of 49 000 L strongly accumulates into the cells and tissues [2]

  • The recursive partitioning (RP) classification model was reasonably successful in classifying compounds with high ($1 L/kg) or low (0–0.3 L/kg) Volume of distribution at steady state (Vss), while it had difficulties to identify the compounds with moderate (0.3–1 L/kg) Vss

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Summary

Introduction

The extent of drug distribution determines the access of a drug to its sites of action and to other tissues, which might give rise to adverse effects. A primary parameter for drug distribution is the volume of distribution (Vd) that is defined as. Volume of distribution is an apparent volume that increases with elevated drug binding in the extravascular space of the body and not an anatomically defined volume. Extensive drug binding outside the blood vessels leads to increasing values of A/C ratio. As tissue binding of drugs varies considerably, volume of distribution displays a wide range of values. Volume of distribution at steady state (Vss) is measured at equilibrium, it describes the molecular tissue binding more reliably than other volume of distribution parameters that are dependent on the time after measurement. Vss depends on the access of the drug to the cells and tissues, its affinity to plasma proteins and tissue components, and number of binding sites in plasma and tissues

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