Evolving neural network optimization of cholesteryl ester separation by reversed-phase HPLC

Cholesteryl esters have antimicrobial activity and likely contribute to the innate immunity system. Improved separation techniques are needed to characterize these compounds. In this study, optimization of the reversed-phase high-performance liquid chromatography separation of six analyte standards (four cholesteryl esters plus cholesterol and tri-palmitin) was accomplished by modeling with an artificial neural network–genetic algorithm (ANN-GA) approach. A fractional factorial design was employed to examine the significance of four experimental factors: organic component in the mobile phase (ethanol and methanol), column temperature, and flow rate. Three separation parameters were then merged into geometric means using Derringer’s desirability function and used as input sources for model training and testing. The use of genetic operators proved valuable for the determination of an effective neural network structure. Implementation of the optimized method resulted in complete separation of all six analytes, including the resolution of two previously co-eluting peaks. Model validation was performed with experimental responses in good agreement with model-predicted responses. Improved separation was also realized in a complex biological fluid, human milk. Thus, the first known use of ANN-GA modeling for improving the chromatographic separation of cholesteryl esters in biological fluids is presented and will likely prove valuable for future investigators involved in studying complex biological samples

Validation of an oil-in-water microemulsion liquid chromatography method for analysis of perindopril tert-butylamine and its impurities

This paper describes the development and validation of a microemulsion liquid chromatography (MELC) method for simultaneous determination of perindopril tert-butylamine and its impurities in bulk active substances and the pharmaceutical dosage form of tablets. An appropriate resolution with reasonable retention times was obtained for a microemulsion containing 0.24% (w/v) butyl acetate, 0.30% (w/v) ethyl acetate, 2% (w/v) sodium dodecyl sulfate, 7.75% (w/v) n-butanol, and 20.0 mM potassium dihydrogen phosphate, the pH of which was adjusted to 3.70 with 85% orthophosphoric acid. Separations were performed on a Nucleosil 120-5 butyl modified (C4), 250 × 4 mm, 5 μm particle size silica column at 40°C, with a mobile phase flow rate of 1.25 mL/min. UV detection was performed at 254 nm. The established method was subjected to method validation, and required validation parameters were defined. Robustness testing, an important part of method validation, was performed as well. Since robustness validation can be conducted using different experimental designs, the Plackett-Burman design was applied due to its possibility of testing many factors at the same time. The validated MELC method was found to be suitable for the simultaneous determination of perindopril tert-butylamine and its impurities in pharmaceuticals