Innovations in Modeling in Liquid Chromatography

As part of method development efforts for reversed phase liquid chromatographic analyses, it is often desirable to model the dependence of the retention factor (k) on the mobile phase composition for target solutes. There is a plethora of models available for this purpose, describing the retention factor dependence on the mobile phase composition as a function of two or more parameters. Two models that we have found to be particularly useful for a wide range of solutes are the classic linear solvent strength (LSS) model, as well as the model proposed by Neue and Kuss (NK). The fitting parameters for the LSS model are kw and S, and the fitting parameters for the NK model are kw, S1 and S2. Recent work has shown that using the kw parameter (i.e., the extrapolated retention factor at a mobile phase composition of 100% water/buffer) can be problematic, especially when fitting gradient data and/or obtaining parameters for large molecules such as proteins and polymers. In this presentation we will show that reparameterization of the LSS and NK models with a kref parameter, corresponding to an mobile phase composition at a new reference point, instead of kw, is advantageous. We will demonstrate the effectiveness of this approach with a series of polyethylene glycol and polypropylene glycol polymers (MW range 300-2500 Da) and proteins (MW range 12-66 kDa), and show that it is critical to select the appropriate reference mobile phase composition for each solute to obtain the most precise parameters for use in simulation programs and in method development efforts.