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Real-time control executed by in-line sensing

Biopharmaceutical productivity and flexibility can be increased by combining single-use technology, in-line sensors, and automated process control. In this study we combined these tools to enhance process control by feedback loops, further reducing manual handling and increasing process robustness.

Here, we demonstrate the flexibility of using the single-use Xcellerex™ XDR10 bioprocessing system, an integrated in-line sensor for real-time monitoring and automated in-process control. First, the in-line InCyte probe was used to monitor the viable cell density and control a steady state perfusion via an automated feedback loop controlling the pump for cell bleeding. Viable cell density data was processed with Wonderware™ automation software to accomplish a steady state perfusion by cell bleeding. Second, we combined N-IR in-line monitoring with a feedback loop for glucose control to obtain a fully automated control of this nutrient. At the same time, we received real-time data for lactate, viable cell density, and IgG concentration. The N-IR spectroscopy data was processed in real time, and predicted nutrient concentrations were communicated to the Wonderware software, which controlled a pump on the XDR system.

In summary, our data supports use of in-line sensors for better process control in upstream applications. With the thoughtful configuration of sensors and automation software to control multiple process parameters, the XDR system offers flexibility and enhanced in-process control.

Helena A.M. Öhrvik
Scientist, R&D BioProcess, Cytiva

Helena Öhrvik is Scientist at Cytiva in R&D. After receiving her Ph.D. in Pharmacology in Uppsala, Sweden, she moved to North Carolina, US, to do her post-doctoral training at Duke University. Her research involved the expression and regulation of recombinant membrane bound proteins in cell cultures. Since Helena joined Cytiva, she has focused mainly on continuous processes, including perfusion, and new inline technologies for the bioprocess field.