Abstract
Retention prediction models for reversed-phase liquid chromatography (RPLC) have been extensively studied owing to the fact that RPLC remains the most widely used chromatographic technique especially in the field of pharmaceutical and biomedical analyses. However, RPLC is not always the method of choice for the analysis of some compounds that have high polarity. Hydrophilic interaction chromatography (HILIC) has been gaining interest in the last few years as an alternative option to RPLC for the analysis of polar and hydrophilic analytes. HILIC is a variant of normal-phase liquid chromatography, but utilizes water in a water-miscible organic solvent as the eluent in conjunction with a hydrophilic stationary phase. The present review aims to summarize recent contributions on the development of retention prediction models for a group of basic analytes, namely, the adrenoreceptor agonists and antagonists, on different polar stationary phases. The use of multiple linear regression and artificial neural networks in model building is highlighted.
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