The influence of stationary phase on pressure-induced retention, selectivity and resolution changes in RP-LC

Characterization of a high throughput approach for large scale retention measurement in liquid chromatography

Many contemporary challenges in liquid chromatography-such as the need for "smarter" method development tools, and deeper understanding of chromatographic phenomena-could be addressed more efficiently and effectively with larger volumes of experimental retention data than are available. The paucity of publicly accessible, high-quality measurements needed for the development of retention models and simulation tools has largely been due to the high cost in time and resources associated with traditional retention measurement approaches. Recently we described an approach to improve the throughput of such measurements by using very short columns (typically 5 mm), while maintaining measurement accuracy. In this paper we present a perspective on the characteristics of a dataset containing about 13,000 retention measurements obtained using this approach, and describe a different sample introduction method that is better suited to this application than the approach we used in prior work. The dataset comprises results for 35 different small molecules, nine different stationary phases, and several mobile phase compositions for each analyte/phase combination. During the acquisition of these data, we have interspersed repeated measurements of a small number of compounds for quality control purposes. The data from these measurements not only enable detection of outliers but also assessment of the repeatability and reproducibility of retention measurements over time. For retention factors greater than 1, the mean relative standard deviation (RSD) of replicate (typically n=5) measurements is 0.4%, and the standard deviation of RSDs is 0.4%. Most differences between selectivity values measured six months apart for 15 non-ionogenic compounds were in the range of +/- 1%, indicating good reproducibility. A critically important observation from these analyses is that selectivity defined as retention of a given analyte relative to the retention of a reference compound (kx/kref) is a much more consistent measure of retention over a time span of months compared to the retention factor alone. While this work and dataset also highlight the importance of stationary phase stability over time for achieving reliable retention measurements, we are nevertheless optimistic that this approach will enable the compilation of large databases (>> 10,000 measurements) of retention values over long time periods (years), which can in turn be leveraged to address some of the most important contemporary challenges in liquid chromatography. All the data discussed in the manuscript are provided as Supplemental Information.

Development of tandem-column liquid chromatographic methods for pharmaceutical compounds using simulations based on hydrophobic subtraction model parameters

The liquid chromatography (LC) analysis of small molecule pharmaceutical compounds and related impurities is crucial in the development of new drug substances, but developing these separations is usually challenging due to analyte structural similarities. Tandem-column LC (TC-LC) has emerged as a powerful approach to achieve alternative separation selectivity compared to conventional single column separations. However, one of the bottlenecks associated with use of tandem column approaches is time-consuming column pair screening and selection. Herein, we compared critical resolution (R_c) in single column vs. TC-LC separations for a given set of small molecule pharmaceutical compounds and developed a column selection workflow that uses separation simulations based on parameters from the hydrophobic subtraction model (HSM) of reversed-phase selectivity. In this study, HSM solute parameters were experimentally determined for a small molecule pharmaceutical (Linrodostat) and ten of its related impurities using multiple linear regression of their retentions on 16 selected RPLC columns against in-house determined HSM column parameters. R_c values were calculated based on HSM database column parameters for a pool of about 200 available stationary phases in both single-phase column (2.1 mm i.d. × 100 mm) or tandem column paired (two 2.1 mm i.d. × 50 mm) formats. Four column configurations (two single and two tandem) were predicted to achieve successful separations under isocratic HSM separation conditions, with a fifth tandem pair predicted to have a single co-elution. Of these five potential candidates, one tandem pair yielded compete baseline resolution of the 11-component mixture in an experimental separation. In this specific case, the tandem column pairs outperformed single-phase columns, with better predicted and experimental R_c values for the Linrodostat mixture under the HSM separation conditions. The results reported in this study demonstrated the enormous selectivity potential of TC-LC in pharmaceutical compound separations and are consistent with our previous study that examined the potential of tandem column approaches using purely computational means, though there is room for substantial improvement in the prediction accuracy. The proposed workflow can be used to prioritize a small number of column combinations by computational means before any experiments are conducted. This is highly attractive from the point of view of time and resource savings considering over 200,000 different tandem column pairings are possible using columns for which there are data in the HSM database.