Introducing New Bioprocessing Technologies in the Era of COVID-19
May 26, 2020 | Biotechnology
Reading time: 2 minutes
To keep you updated on current Biotechnology industry news, Lab.Equipment has curated this article from GEN – Genetic Engineering and Biotechnology News for you:
Bioprocessing is undergoing dramatic changes as companies develop new manufacturing strategies; according to Artur Miguel Arsenio, PhD, head of product management at Sartorius Stedim Biotech. “The digitalization of several elements of our value chain is transforming the way we operate and meet our customers’ needs,” he told GEN. “With the end-to-end integration of systems and data, we are introducing bundling and cross-selling of multiple systems, including digital companions.”
A critical feature of the Bioprocessing 4.0 concept is the reduction of human error. “The increase of automation, remote diagnostics, real-time process monitoring and control can significantly reduce the need for manual tasks,” he stated, “thus decreasing the risks for an important source of contamination. Furthermore, automation and smart connected systems empower the performance of human workers on manual tasks, helping them to avoid errors and reducing risks.”
The company predicts that flexible automation integration will reduce the project effort for installing an upstream /downstream bioprocessing facility by 50–75% because activities are substantially reduced during the integration. The modular packages allow rapid and flexible deployment or change of various consumable configurations to allow process adaptation and quick system upgrades.
“Tailored configurations can be easily updated with a simple software change, even in a cGMP environment,” Arsenio continued. “These smart modular package units allow us to override manual set-up and running issues, significantly reducing human error during set-up and process runs.”
A better process understanding also helps to limit the number of actions dependent on humans (and options offered), further reducing opportunities for errors. Data analytics tools enable process optimization, further reducing the need for human intervention, and the quality by design strategy reduces the risk of failed batches due to... Want to read more? View the entire article in the Genetic Engineering and Biotechnology News (GEN) Blog.
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