Among many operating parameters that control cell culture environment, appropriate mixing and aeration are crucial for cells to meet oxygen demand in aerobic microbial and mammalian production processes. A model-based manufacturing facility fit approach was applied to define agitation and air flow rates during cell culture process scale-up from laboratory to manufacturing, of which computational fluid dynamics (CFD) was the core modeling tool. The realizable k-ε turbulent dispersed Eulerian two-fluid model was used to simulate gas-liquid flow in the bioreactor and predict volumetric oxygen transfer coefficients ( kLa), where the simulation was performed in the basal medium and the resulting kLa was adjusted using modification factors for surfactants such as Pluronic F68 and Antifoam C. The CFD prediction of kLa resulted in adequate agreement with the empirical values in 15,000-L and 25,000-L bioreactors. The model was then applied to define a range of agitation and bottom air flow rates for meeting cellular oxygen demand and mitigating risks of cell damage and safety hazards. The recommended operating conditions led to the completion of five manufacturing runs with a 100% success rate. The model-based approach reduced the required number of at scale development batches and hence enabled seamless scale-up, shortened timelines, and cost savings in cell culture process technology transfer.

Significant amounts of soluble product aggregates were observed in the low-pH viral inactivation (VI) opertion during an initial scale-up run for an IgG4 monoclonal antibody (mAb IgG4-N1). Being earlier in development, a scale-down model did not exist, nor was it practical to use costly Protein A eluate (PAE) for testing the VI process at scale, thus, a computational fluid dynamics (CFD)-based high molecular weight (HMW) prediction model was developed for troubleshooting and risk mitigation. It was previously reported that the IgG4-N1 molecules upon exposure to low pH tend to change into transient and partially unfolded monomers during VI acidification (i.e., VIA) and form aggregates after neutralization (i.e., VIN) (Jin et al. 2019). Therefore, the CFD model reported here focuses on the VIA step. The model mimics the continuous addition of acid to PAE and tracks acid distribution during VIA. Based on the simulated low-pH zone (≤ pH 3.3) profiles and PAE properties, the integrated low-pH zone (ILPZ) value was obtained to predict HMW level at the VI step. The simulations were performed to examine the operating parameters, such as agitation speed, acid addition rate, and protein concentration of PAE, of the pilot scale (50-200L) runs. The conditions with predictions of no product aggregation risk were recommended to the real scale-up runs, resulted in 100% success rate of the consecutive 12 pilot-scale runs. This work demonstrated that the CFD-based HMW prediction model could be used as a tool to facilitate the scale up of the low-pH VI process directly from bench to pilot/production scale.