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Automated data generation improves monitoring and control in bioreactors, suggesting enhanced efficiency in biopharmaceutical production.
The biopharmaceutical industry is transitioning towards more efficient and cost-effective production methods, driven by the need for more affordable treatments. Process intensifications techniques, such as perfusion are the means by which the biopharmaceutical industry is trying to lower costs, enhance productivity and product quality, and reduce facility footprints. The dynamic nature of perfusion processes presents considerable challenges for real-time monitoring and control, requiring the advancement of process analytical technologies (PAT) with at-line, in-line, or on-line capabilities. Raman spectroscopy has emerged as a pivotal technology, providing real-time, noninvasive measurements of multiple analytes simultaneously, contingent upon the availability of sufficient data for calibration modeling. This study outlines the implementation of an automated data generation workflow for Raman calibration modeling within a high-throughput perfusion miniature bioreactor system, specifically the Ambr 250 HT Perfusion. Additionally, we demonstrate the effectiveness of Raman calibration models in monitoring various cell culture parameters within perfusion cultivations, spanning multiple cell lines and monoclonal antibody products. Finally, we present the feasibility of a Raman-based bleed-rate control system and how it compares to the conventional cell counter-based approach.
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Machleid et al. (2026) studied this question.
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