Control strategy for biopharmaceutical production by model predictive control

Abstract

The biopharmaceutical industry is rapidly advancing, driven by the need for cutting‐edge technologies to meet the growing demand for life‐saving treatments. In this context, Model Predictive Control (MPC) has emerged as a promising solution to address the complexity of modern biopharmaceutical production processes. Its ability to optimize operations and ensure consistent product yields has made it an attractive option for manufacturers in this sector. Furthermore, MPC's alignment with the Process Analytical Technology (PAT) initiative provides an additional layer of assurance, facilitating real‐time monitoring and enabling swift adjustments to maintain process integrity. This comprehensive review delves into the various applications of MPC, ranging from robust control to stochastic model predictive control, thereby equipping biotechnologists and process engineers with a powerful toolset. By harnessing the capabilities of MPC, as elucidated in this review, manufacturers can confidently navigate the intricate bioprocessing landscape and unlock this approach's full potential in their production processes.

UV‐based dynamic control improves the robustness of multicolumn countercurrent solvent gradient purification of oligonucleotides

“…Furthermore, this strategy ensures a more consistent product quality and, in turn, more safety for these pharmaceuticals. [26][27] It is worth pointing out that the UV-based control strategy Auto-Peak has a great potential to be implemented in MCSGP of any biomolecule. AutoPeak shifts the definition of the phase boundaries of MCSGP from the time to the UV domain and is not constrained by a certain chromatogram shape.…”