QSPR modeling of pseudoternary microemulsions formulated employing lecithin surfactants: application of data mining, molecular and statistical modeling.

Data mining, computer aided molecular modeling, descriptor calculation, genetic algorithm and multiple linear regression analysis techniques were combined together to generate predictive quantitative structure property relationship (QSPR) models explaining the formation of lecithin-based W/O microemulsions. Ninety-four microemulsion phase diagrams were collected from five different references published over the past few years. Computer-based molecular modeling techniques were then applied on the components of the collected microemulsion systems to generate corresponding plausible three-dimensional (3D) structures. The resulting 3D models were utilized to calculate a group of molecular physicochemical descriptors. Thereafter, genetic algorithm and backward stepwise regression analysis were separately assessed as means for selecting optimal descriptor sets for statistical modeling. The selected descriptors were correlated with microemulsion existence areas employing multiple linear regression analysis. The resulting W/O models were statistically validated and found to be of significant predictive power. The models allowed better understanding of the process of microemulsion formation. Unfortunately, all QSPR modeling efforts directed towards O/W microemulsions failed completely.