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.



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