Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Journal of Cheminformatics
Alex A FreitasTaravat Ghafourian

Abstract

Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), in...Continue Reading

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Citations

Nov 7, 2015·Environmental Health Perspectives·Peter P EgeghyTimothy J Buckley
Dec 21, 2018·Current Topics in Medicinal Chemistry·Emilio S PetitoMatthew J Sykes
May 25, 2016·American Journal of Industrial Medicine·Mihaela StoiaSimona Oancea
Aug 8, 2017·Aging·Diogo G BarardoAlex A Freitas
Feb 27, 2021·British Journal of Clinical Pharmacology·Mason McCombMurali Ramanathan
May 7, 2021·CPT: Pharmacometrics & Systems Pharmacology·Chika OgamiHiroyuki Hosono
Oct 1, 2019·Current Pharmacology Reports·Kimberly HoltKen Korzekwa

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Methods Mentioned

BETA
MDA

Software Mentioned

M5P
MOE ( Molecular Operating Environment )
QSPkR
Tree
M5
PEOE
REPTree
WEKA
Bagging
ACDlabs logD

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