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.