Robustness Testing of Microemulsion Liquid Chromatographic Separation of Simvastatin and its Impurities

Abstract

Liquid chromatography employing the microemulsion as eluent was applied for the analysis of simvastatin and its six impurities. Previously, the optimized and validated method was tested to prove the method's capability to perform during the small changes of important parameters. In this paper, influence of parameters tipical for microemulsion liquid chromatography (MELC) on the method's robustness was presented. For the results evaluation, and presentation, two statistical methods were applied. In order to designate the most convinient one, multiple regression (MR) and artificial neural networks (ANN) were applied and compared. A set of experiments was defined by the central composite design (CCD). Indepedent variables (SDS, n-buthanol and diisopropyl ether content) and dependent variables (retention factors of investigated substances) were the framework for both, MR and ANN. This study demonstrated that MR and radial basis function ANN are useful tools in understanding the effects of the investigated factors on the chromatographic system and definition of the robustness limits.