Implementation and use of gradient predictions for optimization of reversed-phase liquid chromatography of peptides. Practical considerations

The options in the implementation of gradient theory for optimization work are critically reviewed and evaluated for the case of the reversed-phase liquid chromatography of peptides. Various models are covered together with methods for the determination of model parameters. Approaches for calculating retention times and band widths from experimental data are discussed. Different kinds of extrapolation are compared with interpolation. This study was aimed at finding the best compromise between number of experiments, accuracy of predictions and simplicity of calculations. Implementation and the use of gradient predictions can be simple, and practical recommendations are given.