Modeling the effects of type and concentration of organic modifiers, column type and chemical structure of analytes on the retention in reversed phase liquid chromatography using a single model.

A previously proposed model for representing the retention factor (k) of an analyte in mixed solvent mobile phases was extended to calculate the k of different analytes with respect to the nature of analyte, organic modifier, its concentration and type of the stationary phase. The accuracy of the proposed method was evaluated by calculating mean percentage deviation (MPD) as accuracy criterion. The predicted vs. observed plots were also provided as goodness of fit criteria. The developed model prediction capability compared with a number of previous models (i.e. LSER, general LSER and Oscik equation) through MPD and fitting plots. The proposed method provided acceptable predictions with the advantage of modeling the effects of organic modifiers, mobile phase compositions, columns and analytes using a single equation. The accuracy of developed model was checked using the one column and one analyte out cross validation analyses and the results showed that the developed model was able to predict the unknown analyte retention and the analytes retentions on unknown column accurately.