Applicability of retention modelling in hydrophilic-interaction liquid chromatography for algorithmic optimization programs with gradient-scanning techniques

Abstract

Computer-aided method-development programs require accurate models to describe retention and to make predictions based on a limited number of scouting gradients. The performance of five different retention models for hydrophilic-interaction chromatography (HILIC) is assessed for a wide range of analytes. Gradient-elution equations are presented for each model, using Simpson’s Rule to approximate the integral in case no exact solution exists. For most compound classes the adsorption model, i.e. a linear relation between the logarithm of the retention factor and the logarithm of the composition, is found to provide the most robust performance. Prediction accuracies depended on analyte class, with peptide retention being predicted least accurately, and on the stationary phase, with better results for a diol column than for an amide column. The two-parameter adsorption model is also attractive, because it can be used with good results using only two scanning gradients. This model is recommended as the first-choice model for describing and predicting HILIC retention data, because of its accuracy and linearity. Other models (linear solvent-strength model, mixed-mode model) should only be considered after validating their applicability in specific cases.