Use of live digital twin (shadow) soft sensor to monitor membrane degradation in continuous manufacturing single pass tangential flow filtration

Abstract

Digital twins (DT) are sophisticated mathematical models representing real-world physical processes, equipped with predictive capabilities that adapt alongside the physical system. The successful implementation of DT in bioprocessing offers numerous advantages, including enhanced understanding of processes, accelerated overall development timelines, and effective monitoring of critical process parameters (CPPs). A comprehensive end-to-end DT can facilitate informed control decisions and forecast how disturbances within the process may affect the final output, accelerating the overall development timelines while optimizing process efficiency and productivity. Tangential flow filtration (TFF) is a standard methodology in bioprocessing, commonly employed to concentrate and exchange buffers for bioproducts. The advancement of continuous process technologies has led to the emergence of alternative TFF methods, notably single-pass tangential flow filtration (SPTFF), which streamlines the process by eliminating the need for stream recirculation. Here, we present the development of a live DT of the SPTFF concentration step within the downstream continuous manufacturing line for a monoclonal antibody (mAb) process. A live DT, equipped with a state estimation tool, was implemented via the Siemens' gPROMS Digital Applications (gDAP) platform. The DT demonstrated the ability to monitor changes in membrane resistance, a typical process parameter that is not directly measured. This parameter is crucial for SPTFF control, as it allows for the constant setting of the concentration factor (CF) by adjusting the retentate flow rate based on the measured resistance and calculated transmembrane pressure (TMP). This achievement illustrates the potential of DT as effective tools for accurately tracking the complete state of the bioprocess.