Methods to Predict Volume of Distribution

Area of Science:

• Pharmacokinetics and Drug Metabolism
• Computational Biology and Bioinformatics
• Translational Pharmacology

Background:

• Accurate prediction of drug disposition is essential for safe and effective drug development.
• Understanding volume of distribution informs first-in-human dosing and regimen design.
• Volume of distribution is a key pharmacokinetic parameter influenced by physiological and physicochemical properties.

Purpose of the Study:

• To review current methods for predicting drug volume of distribution.
• To compare the strengths and weaknesses of various predictive approaches.
• To identify areas for improvement in volume of distribution modeling.

Main Methods:

• Discussion of preclinical extrapolation methods.
• Overview of physiological and tissue composition-based models.
• Exploration of quantitative structure-activity relationships (QSAR).

Main Results:

• Multiple methods, including PBPK models, are used to predict volume of distribution.
• Key factors influencing predictions include permeability, transport, and experimental data accuracy.
• Current methods generally achieve an average fold error of 2-fold for volume of distribution predictions.

Conclusions:

• Composition-based physiologically based pharmacokinetic (PBPK) models are currently favored for predicting tissue:plasma partition coefficients and volume of distribution.
• Improved mechanistic understanding of drug distribution processes is needed.
• Advancements in modeling approaches will enhance prediction accuracy.