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

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.