Abstract

Robust design of a dead end filtration step and the resulting performance at manufacturing scale relies on laboratory data collected with small filter units. During process development it is important to characterize and understand the filter fouling mechanisms of the process streams so that an accurate assessment can be made of the filter area required at manufacturing scale. Successful scale-up also requires integration of the lab-scale filtration data with an understanding of flow characteristics in the full-scale filtration equipment. A case study is presented on the development and scale-up of a depth filtration step used in a 2nd generation polysaccharide vaccine manufacturing process. The effect of operating parameters on filter performance was experimentally characterized for a diverse set of process streams. Filter capacity was significantly reduced when operating at low fluxes, caused by both low filtration pressure and high stream viscosity. The effect of flux on filter capacity could be explained for a variety of diverse streams by a single mechanistic model of filter fouling. To complement the laboratory filtration data, the fluid flow and distribution characteristics in manufacturing-scale filtration equipment were carefully evaluated. This analysis identified the need for additional scale-up factors to account for non-uniform filter area usage in large-scale filter housings. This understanding proved critical to the final equipment design and depth filtration step definition, resulting in robust process performance at manufacturing scale.

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