Computer-aided design space identification for screening of protein A affinity chromatography resins.

Autor: Sachio S; Sargent Centre for Process Systems Engineering, Imperial College London, SW7 2AZ, UK; Department of Chemical Engineering, Imperial College London, SW7 2AZ, UK., Likozar B; Department of Catalysis and Chemical Reaction Engineering, National Institute of Chemistry, Ljubljana 1001, Slovenia., Kontoravdi C; Sargent Centre for Process Systems Engineering, Imperial College London, SW7 2AZ, UK; Department of Chemical Engineering, Imperial College London, SW7 2AZ, UK., Papathanasiou MM; Sargent Centre for Process Systems Engineering, Imperial College London, SW7 2AZ, UK; Department of Chemical Engineering, Imperial College London, SW7 2AZ, UK. Electronic address: maria.papathanasiou11@imperial.ac.uk.
Jazyk: angličtina
Zdroj: Journal of chromatography. A [J Chromatogr A] 2024 May 10; Vol. 1722, pp. 464890. Date of Electronic Publication: 2024 Apr 08.
DOI: 10.1016/j.chroma.2024.464890
Abstrakt: The rapidly growing market of monoclonal antibodies (mAbs) within the biopharmaceutical industry has incentivised numerous works on the design of more efficient production processes. Protein A affinity chromatography is regarded as one of the best processes for the capture of mAbs. Although the screening of Protein A resins has been previously examined, process flexibility has not been considered to date. Examining performance alongside flexibility is crucial for the design of processes that can handle disturbances arising from the feed stream. In this work, we present a model-based approach for the identification of design spaces, enhanced by machine learning. We demonstrate its capabilities on the design of a Protein A chromatography unit, screening five industrially relevant resins. The computational results favourably compare to experimental data and a resin performance comparison is presented. An improvement on the computational time by a factor of 300,000 is achieved using the machine learning aided methodology. This allowed for the identification of 5,120 different design spaces in only 19 h.
Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Maria M Papathanasiou reports financial support was provided by Engineering and Physical Sciences Research Council. Cleo Kontoravdi & Maria M Papathanasiou reports financial support was provided by Engineering and Physical Sciences Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024. Published by Elsevier B.V.)
Databáze: MEDLINE
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