A Biomanufacturing Digital Twin for Consistent N‐1 Seed Bioreactor Transfers for Commercial Monoclonal Antibody Production

Process consistency in biomanufacturing, particularly for commercial products, is critical for achieving consistent yield and product quality. The N-1 seed bioreactor stage, where cells grow before the transfer to a production bioreactor, often faces variability in final viable cell density (VCD), which leads to variable seeding densities in the production bioreactor and subsequent variability in total protein output per batch. In this study, we address the challenge of precise batch transfer by developing an upstream, stage-specific, level-2 digital twin (digital shadow). Here we show that a cell growth process model predicts growth accurately and updates forecasts using off-line and in-line measurements, enabling precise determination of the final sample time. Deployment of this seed transfer digital twin led to all N-1 to production transfers falling within acceptable limits and resulted in statistically significant increases in harvest yield relative to historical batches. This improvement is attributed to significantly higher on-target accuracy of final N-1 VCDs and significantly higher working volumes in the production bioreactors. Our findings demonstrate that such digital twins ensure consistent cell density during transfer, improve overall upstream process consistency, and lay a foundation for more advanced process control strategies.