Optimization of the separation of anticonvulsant agents in mixed micellar liquid chromatography by experimental design and regression models

The chemometrics approach was applied for the optimization of separation of anticonvulsant agents in mixed micellar liquid chromatography (MLC). To optimize the separation of eight anticonvulsant agents, the effect of six experimental parameters on retention was investigated by means of multivariate analysis. The factors considered were the organic modifier concentration in the mobile phase, the length of the alkyl chain of the organic modifier, the concentration of sodium dodecyl sulfate (SDS) and Brij-35, pH of the mobile phase, and temperature. The experiments were performed according to a face centered cube response surface experimental design. Then, in order to optimize the separation, Pareto-optimality method was employed. The obtained regression models were characterized by both descriptive and predictive ability (R^2>=97.8% and R^2cv>=93.7%) and allowed the chromatographic separation of the anticonvulsant drugs with a good resolution and a total analysis time within 50 min.