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Investigation of Factors Affecting the Performance of in silico Volume Distribution QSAR Models for Human, Rat, Mouse, Dog & Monkey
Author(s)
Simeon, Saw
Montanari, Dino
Gleeson, Matthew Paul
Date Issued
October 1, 2019
Type
Article
Abstract
Volume of distribution (Vdss) is a measure of how effectively a drug molecule is distributed throughout the body. Along with the clearance, it determines the half-life and therefore the drug dosing interval. A number of different pre-clinical approaches are available to predict the Vdss in human including quantitative structure activity relationship (QSAR) models. Vdss QSAR models have been reported for human and rat, but not important pre-clinical species including dog, mouse and monkey. In this study, we have generated Vdss QSAR model on the human and commonly used pre-clinical species, each of which differs in terms of size, chemical diversity and data quality. We discuss the model performance by species, assess the effect the domain of applicability and the relative merits of building chemical series-specific models. In addition, we compare the intrinsic variability of the experimental logVdss data (∼1.2 fold error) to in-vivo interspecies differences (∼2 fold error) and in silico based models (∼3 fold error). This prompted us to explore whether one species could be used to predict another, particularly where little data for that species is available. i. e. does the expansion in domain of applicability prove beneficial over and above any deterioration due to the use of response values from an alternative species.
Citation
Molecular Informatics, 38(10), 2019