Generally trained models to predict drug solubility in methanol plus water mixtures

Abstract

The aim of this study is to develop the trained versions of Yalkowsky and Jouyban-Acree models for the prediction of drug solubility in the binary aqueous mixtures of methanol (MeOH) at various temperatures. To provide a full predictive model, the Abraham solvation parameters of solutes are combined with the proposed models. The solubility data of 41 drug and/or drug-like compounds with different polarities and structural features covering the total drug-like space are fitted by these models. The generally trained models provide reasonable estimation of the solubility behavior of drugs and can be helpful in the pharmaceutical industry. (C) 2018 Published by Elsevier B.V.