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Binary separation control in preparative gradient chromatography using iterative learning control
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DOI：10.1016/j.chroma.2022.463078.png)
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Abstract
En 中文
Purification of biopharmaceuticals has shifted toward continuous and integrated processes, in turn bringing along a need for monitoring and control to maintain a desired separation between the target pharmaceutical and any impurities it may carry. In this study, a cycle-to-cycle control of the retention volumes of two compounds in a chromatographic, ion exchange purification step was developed, allowing the process to maintain the desired retention volumes in the separation. The controller made use of a model-based, multivariate iterative learning control (ILC) algorithm that used a quadratic-criterion objective function for optimal set point control, along with feed-forward control based on direct model inversion for preemptive control of set point changes. The model was calibrated using 3 experiments, allowing for fast setup. The controller was tested by introducing three different disturbances to a sequence of otherwise identical ion exchange separation processes: a change in the salt concentration of the elution buffer, a change in set point, and a change in the pH of the elution buffer. It was capable of correcting for all disturbances within at most 3 cycles, proving its efficacy. The successful application of ILC for separation control in biopharmaceutical purification paves the way for the development of further ILC-based control strategies within the field, as well as combination with other control strategies. (c) 2022 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )
Keywords:
Preparative chromatography
Ion-exchange
Separation control
Iterative learning control
Feed-forward control
Model-based control
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