Review of the cosolvency models for predicting solubility of drugs in water-cosolvent mixtures

The cosolvency models presented from 1960 to 2007 were reviewed and their accuracies for correlating and/or predicting the solubility of drugs in water-cosolvent mixtures were discussed. The cosolvency models could be divided into theoretical, semi-empirical and empirical models, the first group of models provide basic information from the solution, while the last group of models are good suitable for solubility correlation studies. The simplest cosolvency model, i.e. the log-linear model of Yalkowsky, provides an estimate of drug solubility in water-cosolvent mixtures using aqueous solubility of the drug, whereas the Jouyban-Acree model predicts the solubility with an acceptable error with the cost of one more data point (the solubility in neat cosolvent) which is required as input value in the prediction process. A number of error terms used in the literature was also discussed with a brief comments on the acceptable prediction error for pharmaceutical applications.