Dynamic Scheduling and Control of a Single Column Chromatography Process for Integrated Continuous Bioprocessing

Abstract

Integrated continuous bioprocesses (ICBs) offer significant advantages for biotherapeutic manufacturing, including enhanced efficiency, reduced costs, and improved product accessibility. However, the adoption of ICBs is hindered by challenges in maintaining robust operation of the downstream processes amidst upstream variability. This study presents a mixed-integer nonlinear programming (MINLP) formulation for adaptive scheduling and control of a single-column bind-elute chromatography process that is integrated with a time-varying bioreactor harvest and a surge vessel. The control system leverages dynamic models, a rolling horizon implementation and a feedforward harvest forecast to optimize the chromatography loading flow rate and duration while ensuring compliance with critical process constraints. Case studies demonstrate the controller's ability to adapt the chromatography process and maintain robust operation under static and dynamic upstream harvest conditions. This framework represents a significant step toward the broader adoption of ICBs by utilizing the surge vessel as a degree of freedom to implement a variable loading flow rate strategy. Future work will explore experimental validation and extensions to multicolumn systems and alternative chromatography modalities.

Keywords: Dynamic Optimization, Rolling Horizon Scheduling and Control, Integrated Continuous Bioprocessing, Continuous Chromatography