Mixed-integer optimal control for multimodal chromatography

Multimodal chromatography is a powerful tool in the downstream processing of biopharmaceuticals. To fully benefit from this technology, an efficient process strategy must be determined beforehand. To facilitate this task, we employ a recent mechanistic model for multimodal chromatography, which takes salt concentration and pH into account, and we present a mathematical framework for the optimization of chromatographic processes. This framework also includes the use of discrete process controls in order to cover a wider range of chromatographic applications. We describe a procedure to numerically solve the resulting nonlinear mixed-integer optimal control problems. We discuss results of computational experiments, covering the cases where one wants to optimize the yield of the product or the batch-cycle time under specified purity requirements. The results indicate that a good separation can be achieved in a two-component system and that both salt concentration and discrete pH play an important role within the purification process. (c) 2021 Elsevier Ltd. All rights reserved.

Automated summary

The study focuses on optimizing multimodal chromatography processes using a recent mechanistic model and mathematical framework, and finds that good separation can be achieved in a two-component system, with both salt concentration and discrete pH playing important roles in the purification process.