What's Happening?
Biomanufacturers are striving to achieve end-to-end continuous bioprocessing, a method that promises increased efficiency and reduced costs. However, a significant barrier remains in the form of interface mismatches between different unit operations.
According to Moo Sun Hong, PhD, assistant professor at Seoul National University, the integration of technologies such as perfusion culture, multicolumn chromatography, continuous viral inactivation, and continuous filtration into a seamless manufacturing process is challenging. The primary issue is the lack of coordination between upstream and downstream processes, which operate on different dynamics. This results in flow-rate and residence-time mismatches, often necessitating the use of surge tanks or hold steps. The study highlights that while continuous processing offers advantages like process intensification, it also introduces vulnerabilities such as measurement latency and uncertainty around residence time distribution.
Why It's Important?
The ability to implement continuous bioprocessing effectively could revolutionize the biomanufacturing industry by enhancing productivity and reducing costs. However, the current challenges in integrating various unit operations into a cohesive system could hinder these potential benefits. The mismatch in flow rates and residence times between upstream and downstream processes can lead to inefficiencies and increased operational costs. Addressing these issues is crucial for manufacturers to fully realize the benefits of continuous processing, which include improved process robustness and product quality. The development of integrated control strategies and the use of technologies like process analytical technology (PAT) and digital twins are essential to overcoming these challenges.
What's Next?
To address the challenges of interface mismatches, biomanufacturers are encouraged to adopt a systems approach that evaluates transitions from batch to continuous processing based on integrated techno-economic, sustainability, and operational performance metrics. This involves designing interfaces and control strategies that enable a fully-connected, automated, continuous manufacturing platform. The implementation of control strategies based on PAT and digital twin technology is vital for real-time monitoring and predictive modeling. Additionally, further automation and control architectures should be developed to connect sensors, control systems, and data repositories across the integrated process train.
