(43b) Model for Assessing Sensitivity of Biologics to Fluid Forces during Formulation and Filling | AIChE

(43b) Model for Assessing Sensitivity of Biologics to Fluid Forces during Formulation and Filling

Authors 

Geer, D. J. - Presenter, Merck & Co, Inc.
Ford, K. J. - Presenter, Merck and Co., Inc.
Keung, A. - Presenter, Stanford University
Shi, L. - Presenter, Merck & Co., Inc.
Shelukar, S. D. - Presenter, Merck and Co., Inc.
Hunke, W. A. - Presenter, Merck and Co., Inc.
Reynolds, S. D. - Presenter, Merck and Co., Inc.


High shear during formulation and filling has the potential to damage biological products which can lead to potency loss. In this study, various methods have been developed to assess the impact of fluid forces during the manufacture of biologics. These methods were based on a bench-scale testing system to identify the root-causes responsible for damage during the formulation and filling process train. The methods were integrated into a model system that can be used to determine the level of shear sensitivity prior to process development, scale up, and facility design. The model system was developed by considering the multi-dimensional turbulent flow regimes that are typically encountered in commercial manufacturing. Turbulent flow conditions were replicated at the bench-scale using a rheometer, homogenizer, and a flow system in a recirculation loop. The rheometer and homogenizer assays were found to be useful for obtaining quantitative data while minimizing the amount of materials required for testing during early process development. For products deemed sensitive to shear, the recirculating flow system was used to predict the damage that might occur at the commercial scale by considering shear, power input and energy dissipation as process variables for scale-up. CFD (FLUENT) is currently being used to simulate the various flow conditions for scaling variables to the commercial scale. The utility of this model to minimize shear during process optimization, equipment configuration and facility design is being validated. A validated model will ultimately: (i) reduce time spent on development work for new products; (ii) establish a level of risk tolerance during scale-up; (iii) increase the effectiveness of scale-up studies during late stage development and most importantly; (iv) ensure product quality.