Mixing is a common operation in the preparation of optimal formulations for monoclonal antibodies. Mixing can fail due to inadequate mixing or overmixing, leading to poor dose uniformity and protein agglomeration. Additional challenges occur during dilution mixing of fluids featuring different densities and viscosities. Maintaining optimal mixing conditions is crucial due to the high cost of failure. Secondary biopharm manufacture mixing systems are often single-use and come in different shapes and sizes with proprietary impellers. Running experiments with any available equipment is not feasible or cost-effective due to high processing and raw material cost. Simulations can be employed to assess equipment parameters (power per volume (P/V), shear, etc.), ensuring homogeneity and minimizing product quality degradation. In this contribution, we show how computational fluid dynamics (CFD) was used to identify optimal operating conditions for different monoclonal antibodies and mixing equipment at GSK to accelerate right-first-time decisions during process development and scale-up.
Learning Objectives:
Understand how computational fluid dynamics (CFD) can be used to identify optimal operating conditions for different monoclonal antibodies and mixing equipment
Understand the importance of engineering parameters (power per volume (P/V), shear, etc.), over equipment parameters
Undrestand importance of scale out and scale up of mixing operations and in ensuring homogeneity and minimizing product quality degradation