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 take...
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| Main Authors: | , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
7 July 2021
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| In: |
Computers & chemical engineering
Year: 2021, Volume: 153, Pages: 1-16 |
| ISSN: | 0098-1354 |
| DOI: | 10.1016/j.compchemeng.2021.107435 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1016/j.compchemeng.2021.107435 Verlag, lizenzpflichtig, Volltext: https://www.sciencedirect.com/science/article/pii/S0098135421002131 
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| Author Notes: | Hans Georg Bock, Dominik H. Cebulla, Christian Kirches, Andreas Potschka |
| Summary: | 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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| Item Description: | Gesehen am 06.07.2022 |
| Physical Description: | Online Resource |
| ISSN: | 0098-1354 |
| DOI: | 10.1016/j.compchemeng.2021.107435 |