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 we have been accustomed to historically. The paucity of publicly accessible, high-quality measurements has been due, at least in large part, 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 results obtained using this approach using a dataset containing about 13,000 retention measurements, and describe an approach to sample introduction that improves upon the prior work. The dataset is comprised of 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 “out of control” measurements, 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 here 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 time (months) compared to the retention factor alone. While this work and dataset also highlights 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 of the data discussed in the manuscript are provided as Supplemental Information.