The urgent demand for vaccine development and manufacturing due to COVID-19, all while maintaining controlled strategies, has placed immense pressure on bioreactor operations to increase yield with less risk and waste.
TORONTO, Ontario (PRWEB) January 28, 2021
Bioreactor processes in pharma manufacturing include some of the most evolving and complex technologies available in the production of mRNA, plasmid DNA, monoclonal antibodies and a multitude of other vaccine types and medicinal products. The urgent demand for vaccine development and manufacturing due to COVID-19, all while maintaining controlled strategies, has placed immense pressure on bioreactor operations to increase yield with less risk and waste.
To this end, pharma manufacturing teams have been mandated with improving bioreactor process consistency, maximizing productivity, and increasing right first time (RFT) critical process parameters (CPPs). Teams also need the ability to accurately modify and control process parameters to achieve tailored products to specific requirements and the quality target product profile (QTPP).
The complexity of bioreactor data that influence these KPIs — which include hundreds of simultaneous parameters — poses significant analytical and data management challenges. This requires a new approach to optimize actionable steps and to alarm operators of deviations or anomalies. The Aizon Bioreactor Application is the industry’s first AI-driven analytical and GxP data management application designed specifically for bringing smart manufacturing to the bioreactor.
Join Raul Alba, PhD, PMP, Biotech Solutions Expert, Aizon, in a live webinar on Wednesday, February 17, 2021 at 11am EST (4pm GMT/UK) to hear about bioreactor yield prediction and optimization with powerful automated AI options and management of bioreactor data to preserve GxP compliance and accessibility under FAIR and ALCOA+ principles.
For more information, or to register for this event, visit Smart Manufacturing Meets the Bioreactor: Driving More Value and Consistency from Bioprocessing.
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