Solvent-strength selectivity refers to the variation of band spacing by changing the %-organic in the mobile phase (ion-pair or reversed-phase HPLC). A review of the literature has been combined with new experimental data to illustrate the general potential of this approach for HPLC optimization. It appears that most samples exhibit significant changes in band spacing method development based on solvent-strength optimization plus computer simulation (DryLab software) are given for illustration. For relatively simple mixtures (10 or fewer components), it appears that solvent-strength optimization compares favorably with other methods such as mapping the organic-solvent selectivity of methanol, acetonitrile, tetrahydrofuran, and water.

A personal-computer program (DryLab G) is described for the simulation of reversed-phase gradient-elution separations. After two experimental gradient runs are carried out initially, this program allows the user to develop a final separation by varying gradient conditions (gradient time, initial and final %-organic in the mobile phase, gradient shape), column dimensions, flowrate and particle size. This approach takes advantage of “solvent-strength selectivity”, as reported recently [28] for isocratic separations. Method development using this procedure can result in better separations with much less effort. Examples of its validation and application are presented.

A general model for describing gradient elution separations of peptides and proteins by reversed-phase high-performance liquid chromatography (HPLC) has been presented previously. This model has now been modified so that it can be applied to any of the four HPLC methods used for separating biological macromolecules: reversed-phase, ion-exchange, hydrophobic-interaction and size-exclusion chromatography, carried out in either an isocratic or gradient elution mode. The role of sample molecule structure and the particular column used has been further studied, so that previous empirical parameters for different column/sample choices can now be estimated from three physical properties of the sample and the column: (a) sample molecular weight, (b) native vs. denatured sample, (c) column packing pore diameter. This eliminates much of the empiricism of our preceding model, and minimizes the number of experimental runs now required in order to apply the model in practice

Application of DryLab 4-5 (the first DryLab program to model retention effects) to the problem of column-to-column reproducibility, adjusting conditions to minimize retention differences.

Computer simulation uses two experimental HPLC runs to allow prediction of sample retention as a function of mobile phase composition or gradient conditions. The general approach is rigorous, but it is assumed that reversed-phase retention obeys the relationship log k' = log kw - S 0. Small deviations in this relationship can lead to error in predicted retention times. We have studied this error empirically for several different reversed-phase systems. This provides a basis for partially correcting these errors, and suggests recommendations for avoiding significant errors during computer simulation.Further work on improving the accuracy of DryLab I and DryLab G predictions, verification of this approach.