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Improved assay development of pharmaceutical modalities using feedback-controlled liquid chromatography optimization.
- Source :
-
Journal of chromatography. A [J Chromatogr A] 2024 May 10; Vol. 1722, pp. 464830. Date of Electronic Publication: 2024 Mar 24. - Publication Year :
- 2024
-
Abstract
- Development of meaningful and reliable analytical assays in the (bio)pharmaceutical industry can often be challenging, involving tedious trial and error experimentation. In this work, an automated analytical workflow using an AI-based algorithm for streamlined method development and optimization is presented. Chromatographic methods are developed and optimized from start to finish by a feedback-controlled modeling approach using readily available LC instrumentation and software technologies, bypassing manual user intervention. With the use of such tools, the time requirement of the analyst is drastically minimized in the development of a method. Herein key insights on chromatography system control, automatic optimization of mobile phase conditions, and final separation landscape for challenging multicomponent mixtures are presented (e.g., small molecules drug, peptides, proteins, and vaccine products) showcased by a detailed comparison of a chiral method development process. The work presented here illustrates the power of modern chromatography instrumentation and AI-based software to accelerate the development and deployment of new separation assays across (bio)pharmaceutical modalities while yielding substantial cost-savings, method robustness, and fast analytical turnaround.<br />Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br /> (Copyright © 2024. Published by Elsevier B.V.)
Details
- Language :
- English
- ISSN :
- 1873-3778
- Volume :
- 1722
- Database :
- MEDLINE
- Journal :
- Journal of chromatography. A
- Publication Type :
- Academic Journal
- Accession number :
- 38608366
- Full Text :
- https://doi.org/10.1016/j.chroma.2024.464830