Transferability of global retention models in reversed-phase liquid chromatography for natural products

Abstract

Considerable progress has been made in enhancing resolution in reversed-phase liquid chromatography for the analysis of complex samples, particularly within the field of natural products, through the application of global retention models using multi-linear gradients. Global models effectively differentiate solute retention effects from those originating from the column and solvent, offering predictive capabilities comparable to conventional individual retention models, without the requirement for standards for all compounds. While conventional individual models result in higher accuracy, they frequently demand standards that are unavailable for natural product samples. Moreover, the creation of individual models can be time-consuming due to the need for repetitive work for additional compounds. Experimental validation of global models has demonstrated that the accuracy is enough for the prediction of complex chromatograms. Through a carefully designed experimental work, this study reports the correct determination of global parameters for column and solvent, with excellent consistency across various medicinal plant samples. The successful transfer of predictions and optimisation of resolution across diverse plant species (lemon balm, peppermint, and pennyroyal) is confirmed. This highlights the applicability of predictions using global models across botanical varieties.