Enabling Bioprocess Upscaling Prediction Through Hybrid Modelling and Transfer Learning Under Small-Data Scenarios.
Accurate prediction of bioprocess scale-up is critical for accelerating the deployment of novel and sustainable biomanufacturing systems. However, this remains challenging as multi-scale data is expensive to generate and mechanistic understanding is often incomplete, leading upscaling decisions to rely heavily on empir...