Achieving optimal advanced process control in bioproduction
Model Predictive Control (MPC) “stands out as a beacon of advanced control” in continuous manufacturing, through its ability to enhance efficacy within bioproduction, research suggests.
According to a paper published in Bioprocess Control, as an advanced process control method, Model Predictive Control (MPC) can optimise biomanufacturing operations and ensure consistent product yields. With biological systems becoming increasing complex, alongside expanding demand for precision in drug development and manufacturing, advanced process control methods that can ensure consistent product yields and high-quality outputs in bioproduction are becoming vital, the researchers acknowledged.
A delicate balance
MPC has been applied in various industrial sectors, such as aeronautics, since the 1970s, according to the paper.
Yet applying MPC in bioproduction has historically been limited, due to the unique challenges inherent in biological systems, such as their “high sensitivity… to process conditions, including temperature, pH, and substrate concentrations”, as well as the need for advanced sensors capable of measuring critical quality attributes (CQAs).
However, MPC can significantly enhance the effectiveness of continuous biomanufacturing. Model-based predictive controllers applications such as continuous upstream and downstream bioprocessing “holds great potential”, the authors noted.
Critically, in bioproduction, MPC offers a promising solution to ensure the final product meets the required specifications, the paper stated. It offers “a framework for identifying ideal operating conditions and deriving the process to these set points in the most feasible way while ensuring optimal control within constraints.”
A promising solution for optimised bioproduction
Eslami et al. highlighted several benefits of MPC:
- Trajectory tracking and obstacle avoidance capabilities can optimise cell growth in bioreactors while avoiding contamination
- Optimisation of downstream processing, such as purification and separation, while maintaining product quality within the constraints of the process
- Using MPC in autonomous systems can be adapted to control and optimise complex bioprocesses, where high levels of automation and decision-making under constraints are required.
The authors considered that within Integrated Continuous Bioprocessing (ICB), MPC holds great potential in bioproduction. With the biopharma sector progressively favouring continuous manufacturing approaches such as ICB, MPC offers “a beacon” of advanced control.
Eslami et al. eloquently concluded: “Imagine the continuous crafting of monoclonal antibodies, or the melding of MPC with the ever-evolving world of artificial intelligence (AI). And when we think of MPC intertwining with hybrid modelling, it paints a picture of a future where control and predictability in biomanufacturing reach unprecedented heights.
“We anticipate that the global shift towards sustainable processes will drive the increased utilisation of MPC in bioprocess units, enabling the handling of sluggish systems with inaccurate forecasting models. Based on our observations, we expect a significant growth in the number of MPC applications due to existing disciplines and emerging trends.”
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