Optimize bioprocess performance with high-fidelity CFD simulation

Pharmaceutical manufacturers face constant pressure to improve efficiency, reduce costs and accelerate drug delivery. This solution brief explores how high-fidelity Computational Fluid Dynamics (CFD) simulation helps organizations optimize large-scale bioprocesses, including a real-world use case showing a 12% improvement in product yield and an estimated $20 million in additional annual revenue on a 20,000L bioreactor.

The challenge: large-scale bioprocess optimization requires more than traditional testing

Optimizing a 20,000L bioreactor requires managing simultaneous, nonlinear interactions between oxygen transfer rates, mixing performance, shear stress and cell viability. Design of Experiments (DOE) approaches and physical trials are expensive and time-consuming at production scale. When equipment configurations and media formulations are already fixed, opportunities for physical experimentation are limited and the cost of a process failure is significant.

The solution: reduce the need for physical trials with AI-powered simulation

Computational Fluid Dynamics (CFD) simulation builds a high-fidelity digital model of your bioreactor, capturing the complex interactions between agitation, aeration and impeller configuration. Engineers can explore hundreds of operating scenarios virtually, reducing reliance on physical trials and minimizing disruption to production. Combining multiphysics modeling with advanced optimization algorithms allows teams to identify favorable operating conditions with greater speed and confidence than physical testing alone.

Key takeaways

What process engineering leaders will learn from this brief:

• Why traditional DOE and physical trials are insufficient for large-scale bioprocess optimization
• How multiphase CFD modeling captures oxygen transfer, shear rates and mixing dynamics simultaneously
• How to use simulation to evaluate operating scenarios without disrupting production
• How simulation-based development strengthens regulatory and manufacturing decision making

Read the solution brief to learn more.