480g Development of a ‘Cycle to Cycle' Control for the Mcsgp-Process for a Monoclonal Antibody Variant Separation

Cristian Grossmann1, Manfred Morari1, Massimo Morbidelli2, and Guido Ströhlein3. (1) Automatic Control Laboratory, ETH Zurich, Zurich, Switzerland, (2) Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zurich, Wolfgang-Pauli-Str. 10, HCI F 133, Zurich, 8093, Switzerland, (3) ChromaCon AG, Technoparkstr. 1, Zürich, 8005, Switzerland

The MCSGP process is a new continuous chromatographic process specifically designed for the purification of proteins and peptides. Due to its counter-current purification principle, the performance increase with respect to the batch process can be up to 10x in productivity and more at even higher yields [1]. Various successful applications of the MCSGP-technology have been reported, e.g. the purification of monoclonal antibodies from high-titer supernatants with ion-exchange resins and the purification of polypeptides.

However, optimum MCSGP operation is a challenge and the current practice is to operate the MCSGP units at sub-optimal conditions to guarantee robustness. As a result, control and automation of MCSGP is of great interest in order to exploit the full economic potential of this process. An automatic control algorithm for MCSGP units that guarantees an optimal, robust operation with product purities in specification is a challenging problem because of the complex dynamics involved in this process, i.e. its cyclic and hybrid nature due to the inlet/outlet port switching with strong nonlinearities and delays in the feedback information.

In this work, a control algorithm based on previous work[2] is developed for the MCSGP-technology. The flow rates as well as the salt gradients have been chosen as manipulated variables. The suitability of the controller is proven using the separation of three monoclonal antibody variants as model system for the simulations.

[1] http://www.chromacon.biz/PressRelease_MCSGPpeptides_Novartis.pdf

[2] Grossmann, C., Erdem, G., Morari, M., Amanullah, M., Mazzotti, M., Morbidelli, M., ‘Cycle to cycle' optimizing control of simulated moving beds. AICHE J, Volume: 54, Pages: 194-208, Published: 2008