Scalable bioprocesses through advanced computational tools

Scale effects in bioprocesses can be challenging to predict accurately. These effects can cause significant issues during scale-up or scale-down of processes, lengthening development timelines or introducing uncertainty during manufacturing. Advanced computational tools such as computational fluid dynamics, population balance modelling, and data-driven modelling approaches can provide valuable insights into hydrodynamics, mass transfer, and biological responses across scales. By integrating these tools with experimental data, scalable and robust bioprocesses can be designed more efficiently. This session highlights how modern computational approaches support rational process development and de-risk bioprocess scale transitions.