Use of multivariate analysis for optimization of separation parameters and prediction of migration time, resolution, and resolution per unit time in micellar electrokinetic chromatography

Abstract

The optimization of separation parameters in chromatography for better separation and resolution of analytes continues to be a labor intensive procedure usually performed by a trial and error method. A multivariate analysis in the form of multilinear regression (MLR) is used to optimize separation parameters and predict the migration behavior, resolution, and resolution per unit time of achiral (4-chlorophenol, pentachlorophenol, clonazepam, and diazepam) and chiral (1,1'-binaphthyl 2,2'-dihydrogen phosphate (BNP), and 1,1'-bi-2-naphthol (BOH)) compounds in MEKC. Separations of achiral and chiral analytes were performed using an achiral (poly(sodium N-undecylenic sulfate)) molecular micelle and chiral (poly(sodium N-undecanoyl-L-leucylvalinate) or poly(sodium N-undecanoyl-L-isoleucylvalinate)) molecular micelle, respectively, at various operating temperatures, applied voltages, pH values, and molecular micelle concentrations in the BGE. The separation parameters were subsequently used as input variables for MLR models. The models were validated with independent samples. The root-mean-square percent relative error (RMS%RE) is used as a figure of merit for characterizing the performance of the migration time, resolution, and resolution per unit time models. The RMS%RE obtained for predicted migrated times, resolutions, and resolution per unit time of 4-chlorophenol, pentachlorophenol, clonazepam, diazepam, BNP, and BOH ranged between 8 and 19%. The same experimental procedure was used to optimize the separation parameters of six other chiral analytes of different compound class. The predicted migration times, resolutions, and resolution per unit time of the chiral as well as the achiral analytes compare favorably with the experimental migration times and resolutions, indicating versatility and wide applicability of the technique in MEKC.

Application of Fluorescence Spectrometry With Multivariate Calibration to the Enantiomeric Recognition of Fluoxetine in Pharmaceutical Preparations

“…This process uses net analyte signal (NAS) calculations defined as the part of measured signal that is unique for the considered enantiomer. The estimation of the figure of merit in PCR and PLS calibration models is enabled by NAS using described equations from earlier studies 34,35 and are not written in detail here.…”

Electrokinetic chromatography with polymeric pseudostationary phases

“…Multivariate analysis was used to predict and optimize migration times, resolution, and resolution/time using achiral and chiral polymeric PSPs [68]. The factors considered were PSP concentration, applied voltage, pH, and operating temperature.…”

Protein separations using polyelectrolyte multilayer coatings with molecular micelles in open tubular capillary electrochromatography

“…In recent studies, experimental design and multivariate analysis have been widely used to simultaneously optimize separation parameters, leading to higher resolution in relatively short analysis times [27,[39][40][41][42][43][44]. We have previously reported the use of experimental design and multivariate analysis for the optimization of separation parameters to predict the migration time, resolution, and resolution per unit time of several chiral and achiral analytes using micellar EKC [27]. Also, experimental design has been used to optimize the separation conditions of two different stationary phases for the separation of four basic peptides in OT-CEC [39].…”