Generally trained models to predict drug solubility in N-methyl-2-pyrrolidone plus water mixtures at various temperatures

Abstract

The trained versions of Yalkowsky and Jouyban-Acree models are proposed to predict solubility of drugs in binary aqueous mixtures of N-methyl-2-pyrrolidone (NMP) at various temperatures. To provide a full predictive model, the Abraham solvation parameters of solutes are combined with the Jouyban-Acree model and Jouyban-Acreevan't Hoff model. Since this investigation includes a number of compounds with different polarities and structural features, the results may provide accurate estimations of solubilization for most compounds of interest. The overall mean relative deviation (MRD) values for the back-calculated solubility of drugs in (NMP + water) solvent mixtures are 20.9-39.3% for the proposed models indicating that the generally trained models provided acceptable predictions and could be helpful in the pharmaceutical industry. (C) 2018 Elsevier B.V. All rights reserved.