Development of Advanced Hyphenated Systems for Analytical Measurements

with Kevin Schug
Monday, November 18, 2024
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About This Meeting

 

Development of Advanced Hyphenated Systems for Analytical Measurements

 

Co-Sponsored by the North Jersey Chromatography Group

 

**Meeting will be held in the 3rd Floor Atrium of the Conference Center following the EAS Monday Reception**

 

Complex samples present myriad challenges in terms of removal and characterization of impurities, the presence of multiple target analytes of interest, and the potential for matrix effects. Modern analytical instrumentation has become more modular in nature, which allows for the creation of on-line and custom systems that can be used to increase efficiency, recovery, throughput, and analyte coverage for complex mixture analysis. Two examples of advanced hyphenated systems will be presented. The first will be a multi-modal liquid chromatography system designed for characterization of polymeric drug delivery modalities. In one injection, both polymer degradants and other small molecule components can be monitored. Restricted access media is used to segregate different components on-line prior to independently operated size exclusion and reversed phase separation channels. The second is a commercial on-line supercritical fluid extraction – supercritical fluid chromatography instrument. This instrument has a broad application base, but because the on-line hyphenation includes loading of the extract plug directly on the analytical column, optimization of extraction and separation conditions to achieve efficient analyte determination is challenging. Multivariate and advanced surrogate optimization procedures are being explored to create more effective means for method development. This work explores the interface between advanced data science procedures and analytical system optimization to better capitalize on the broad application base offered by supercritical fluid technologies. Both instrumental arrangements involve the use of mass spectrometric detection.

 

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