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Poster Presentation

The Development of a Virtual Liquid Chromatography Method Development Tool

06 June 2023, 10:30 a.m. to 12:30 p.m. - 1:30 to 2:30 p.m.

Authors: Elaina Gairloch, Melinda Urich

Presenters: Elaina Gairloch

The development and optimization of liquid chromatography (LC) separations can be time-consuming and costly, often requiring a number of steps including literature research, column selection, method scouting, method development, and method optimization. In an effort to eliminate these steps, an instrument-free, software modeling tool that gives users the ability to select compounds from a database and instantly model a separation on different column phases was developed.
Optimization of the model can be performed while maintaining critical pair separations by adjusting for instrument/system effects (e.g., dwell volume and extra column volume), mobile phase preferences, number of gradient steps, and more. The initial database consists of a Drugs of Abuse (DoA) library containing approximately 250 compounds with plans to continually expand the utility.
A modeled chromatogram and instrument-ready conditions are automatically generated and can be further optimized by users. During software development, the acceptance criteria for retention time agreement between wet-lab and modeled values was set at +/- 15 seconds. This range was chosen because it represents a typical MRM window. In the most complex portion of the verification, 704 retention time data points were collected in total for the 25 compounds used in the evaluation. Only 13 data points exceeded the+/- 15 second window with no compounds missing acceptance criteria by more than five seconds, giving an overall pass rate of 98.2%.
For LC method developers, novices, and experts who either lack the expertise, or the time, to develop separations quickly and accurately, this free tool can be used to deliver a fast, no-cost starting point for method development and optimization. This novel, virtual method development software can improve turnaround time, increase throughput to existing methods, and offer an on-demand consultative user experience.

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