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CHROMtalks - The Use of Machine Learning to Automate Method Development for LC Separations of Biopharmaceuticals

High-resolution LC and two-dimensional liquid chromatography (2D-LC) advance with a speed great than our capability to use these powerful techniques in regulated routine environments. One field where the demands of quick and effective method development are demanding is that of biopharmaceutical separations, where stringent regulations and large numbers of complex samples demand high efficiency of the method-development workflow. Automation is even more worthwhile for (prospective) new formulations, for example, oligonucleotides where advanced hyphenated separation technology must meet regulatory requirements. In this presentation, the recent developments in automated method development for biopharmaceutical separations will be presented in the form of a roadmap. The role of data-analysis strategies and machine learning to advance automation will be addressed.

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