Bioprocess Technologies and Engineering, BioPharmaceuticals Development, R&D, AstraZeneca, Gaithersburg, US.
Biotechnol Bioeng. 2023 Jun;120(6):1584-1591. doi: 10.1002/bit.28376. Epub 2023 Mar 27.
In the production of biopharmaceuticals depth filters followed by sterile filters are often employed to remove residual cell debris present in the feed stream. In the back drop of a global pandemic, supply chains associated with the production of biopharmaceuticals have been constrained. These constraints have limited the available amount of depth filters for the manufacture of biologics. This has placed manufacturing facilities in a difficult position having to choose between running processes with reduced number of depth filters and risking a failed batch or the prospect of plants going into temporary shutdown until the depth filter resources are replenished. This communication describes a modeling based method that leverages manufacturing scale filtration data to predict the depth filter performance with a reduced number of filters and an increased operational flux. This method can be used to quantify the acceptable level of area reduction before which the filtration process performance is affected. This enables facilities to manage their filter inventory avoiding potential plant shutdowns and reduces the risks of negative depth filter performance.
在生物制药生产中，通常采用深滤器和无菌过滤器来去除进料流中存在的残留细胞碎片。在全球大流行的背景下，与生物制药生产相关的供应链受到了限制。这些限制限制了可用于生物制品制造的深滤器的数量。这使得制造设施处于两难境地，要么选择使用减少数量的深滤器运行工艺，冒着批次失败的风险，要么面临工厂暂时停产的前景，直到深滤器资源得到补充。本通讯介绍了一种基于建模的方法，该方法利用制造规模过滤数据来预测在过滤过程性能受到影响之前，减少深滤器数量和增加操作通量的情况下的深滤器性能。该方法可用于量化在过滤过程性能受到影响之前可以接受的面积减少水平。这使设施能够管理其过滤器库存，避免潜在的工厂停机，并降低深滤器性能不佳的风险。
