The American Chemical Society Subdivision of Chromatography and Separations Chemistry sponsored two poster awards om 2021 with a prize of $250 each.
Multidimensional GC Poster Award 2021
Caitlin Cain, University of Washington
Development of an enhanced total ion current chromatogram algorithm to improve untargeted peak detection
Caitlin Cain graduated from Virginia Commonwealth University in 2019 with B.S. degrees in Chemistry and Forensic Science. She is currently pursuing a Ph.D. in Chemistry at the University of Washington under the guidance of Dr. Robert Synovec. Her studies focus on advancements in chemometric methods for comprehensive two-dimensional gas chromatography. She is a recipient of the National Science Foundation’s Graduate Research Fellowship and plans to continue her work as a postdoctoral research fellow and ultimately professor.
Description of Poster
Peak detection methods for comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry are often performed on the total ion current chromatogram (TIC). Despite detecting many of the most abundant peaks, a large fraction of peaks remains undetected in the standard TIC due to their signals residing below the limit of detection. Therefore, an untargeted peak detection method termed the “enhanced TIC algorithm” was developed to utilize the entire mass spectral dimension and find peaks obscured by the background noise. The enhanced TIC was shown to discover 33-64 % more peaks through amplification of low analyte signals. Both the traditional and enhanced TIC were compared to statistical overlap theory (SOT), with the enhanced TIC providing results more consistent with SOT at lower signal-to-noise. Ultimately, the developed algorithm demonstrates a distinct benefit in peak discovery that improves data analysis efforts for multidimensional chromatography.
Multidimensional LC Poster Award 2021
Devin Makey, University of Michigan
Enabling Two-Dimensional Liquid Chromatography for Analysis and Purification of Pharmaceuticals via Computer-Assisted Method Development Software
Devin Makey received his bachelor’s degree in chemistry from Gustavus Adolphus College. He is currently pursuing his PhD in analytical chemistry at the University of Michigan. His primary research interests involve multidimensional separations of biomolecules and pharmaceuticals using liquid chromatography, ion mobility, and mass spectrometry. In addition to separation science, Devin is also passionate about music. He enjoys playing the trumpet and is a student in the organ department at Michigan.
Description of Poster
Two-dimensional liquid chromatography (2D-LC) is quickly becoming a powerful tool for achieving the peak capacity and selectivity needed to resolve complex mixtures seen in the pharmaceutical industry. However, time-consuming method development and optimization processes present a bottleneck that has prevented 2D-LC from being widely implemented across pharma. In this work, a systematic approach was presented that uses ACD/Labs computer-assisted method development software to dramatically simplify 2D-LC method development. Retention models for 1D and 2D conditions were built from a minimal number of multifactorial modeling experiments (2 × 2 or 3 × 3 parameters: gradient slope, column temperature, and different column and mobile phase combinations) and were used to select optimal chromatographic conditions. See the recent publication in Analytical Chemistry for more information (DOI: 10.1021/acs.analchem.0c03680).