Laska Michael E, Brooks Ralph P, Gayton Marshall, Pujar Narahari S
Biologics Development & Engineering, Merck Research Labs, West Point, Pennsylvania, USA.
Biotechnol Bioeng. 2005 Nov 5;92(3):308-20. doi: 10.1002/bit.20587.
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.
终端过滤步骤的稳健设计及其在生产规模下的性能依赖于使用小型过滤单元收集的实验室数据。在工艺开发过程中，表征和理解工艺流的过滤器污染机制非常重要，以便能够准确评估生产规模所需的过滤面积。成功放大规模还需要将实验室规模的过滤数据与对全尺寸过滤设备中流动特性的理解相结合。本文介绍了一个用于第二代多糖疫苗生产工艺的深层过滤步骤的开发和放大案例研究。针对多种工艺流，通过实验表征了操作参数对过滤器性能的影响。在低通量下运行时，由于过滤压力低和料液粘度高，过滤器容量显著降低。对于各种不同的料液，通量对过滤器容量的影响可以用一个单一的过滤器污染机理模型来解释。为了补充实验室过滤数据，仔细评估了生产规模过滤设备中的流体流动和分布特性。该分析确定需要额外的放大因子来考虑大型过滤器外壳中过滤面积使用不均匀的情况。这种理解被证明对最终的设备设计和深层过滤步骤定义至关重要，从而在生产规模下实现了稳健的工艺性能。
