Generally trained models to predict solubility of drugs in carbitol + water mixtures at various temperatures

Abstract

The trained versions of Jouyban-Acree and Yalkowsky models are proposed employing solubility data sets of 11 drugs in carbitol + water mixtures at various temperatures. Using these models, the solubility of a drug in the mono-solvents, the Abraham solvation parameters and log P value of the drug, its solubility in the binary solvent mixtures at various temperatures could be predicted. The mean percentage deviations for the correlated data were 137 and 20% respectively for the Yalkowsky and Jouyban-Acree models. é 2016 Elsevier B.V.