Automated chiral method screening. Evaluation of generated chromatographic data sets to further optimize screening efficiency

Abstract

We set up an automated screening process to routinely test 10 chiral supercritical fluid chromatography (SFC) methods - five columns combined with two co-solvents - as part of a chiral separation lab workflow. Proprietary software tools enabled automated method screening of racemates, parallel evaluation of the resulting chromatograms for enantiomer separation and report generation. This process is largely automated and resulted in an efficient and reliable lab process with a minimum requirement for human intervention. Screenings were conducted on a test set of 756 racemates that were selected with focus on structural variation and on 2667 proprietary samples from lab routines. Statistical analysis revealed that up to 92% of the tested racemic mixtures could be successfully separated with at least one of the tested conditions of the screening. Process efficiency was further increased by identification of optimal method screening sequence, re-definition of the optimal column set and project-specific adaptations considering reduced structural variation of the analytes. This study illustrates the usefulness of consistent chromatographic data sets to accelerate and facilitate the identification of chiral methods to separate enantiomers by automated processing and statistical analysis.