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 of 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— 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. New Pharma 4.0 technologies are now available to gain efficiencies in bioreactors while still maintaining GxP requirements. Emerging technologies like AI, ML, cloud, and IIoT help manufacturers fully use, monitor, analyze, understand, and control the upstream manufacturing process.
Aizon is leading a webinar, “Smart Manufacturing and Bioprocessing – Driving More Value and Consistency from your Bioreactors.” This webinar will help leaders and innovators involved in achieving business value and optimizing processes based on data-driven insights. Learn how these emerging technologies can be implemented in your environments and can even integrate with classical statistics to consider all the relevant factors and variables in the system and draw insights and make predictions that would have otherwise been missed, enabling manufacturing production and quality teams to achieve their goals.
We will discuss:
- Bioreactor yield prediction and optimization, with powerful automated AI options and phased contextualization, tuned specifically for delivering relevant bioreactor intelligence for value return
- Deep process knowledge and batch optimization including accelerated root cause analysis (RCA) and suggested actions for batch redirection
- Advanced anomaly detection for prediction of issues and potential failures, allowing operating engineers to react before the problems occur; scale this capability to any number of sites
- Management of bioreactor data to preserve GxP compliance and accessibility under FAIR and ALCOA+ principles
We will also review how bioreactor advanced analytics are compatible with continuous manufacturing as a seamless path for your future Pharma 4.0 initiatives.