Numerical methods to predict the solubility of @entity10517 in mixed solvents have been proposed. A minimum number of 3 solubility data points in sub-binary solvents has been employed to calculate the solvent-solute interaction terms of a well established colsolvency model, i.e. the combined nearly ideal binary solvent/Redlich-Kister model. The calculated interaction terms were used to predict the solubility in binary and ternary solvent systems. The predicted solubilities have been compared with experimental solubility data and the @entity5494 ( @entity5494 ) has been computed as a criterion of prediction capability. The overall @entity5494 for 25 @entity10517 data sets in binary solvents is 0.40%. In order to provide a predictive method, which is based fully on theoretical calculations, the quantitative relationships between sub-binary interaction terms and physicochemical properties of the solvents have been presented. The overall @entity5494 value for 41 binary data sets is 9.19%. The estimated binary interaction terms using a minimum number of data points and the quantitative relationships have then been used to predict @entity10517 solubility data in 30 ternary solvent systems. The produced @entity5494 values are 3.72 and 15.79%, respectively. To provide an accurate correlation for solubility in ternary solvent systems, an extension to the combined nearly ideal multicomponenet solvent/Redlich-Kister (CNIMS/R-K) model was proposed and the corresponding overall AMPD is 0.38%.

Solubility prediction of XXXX in mixed solvents using a minimum number of experimental data.

@entity10517 :: ('MESH:C034020', 'Chemical') :: ['anthracene'] @entity5494 :: ('MESH:D010262', 'Disease') :: ['APMD', 'absolute percentage mean deviation']
@entity10517 :: (MESH:C034020,Chemical) :: ['anthracene']
