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Maximizing The Performance And Efficiency Of Your Sterilizing-Grade Filtration

Source: MilliporeSigma

By Kimberly Steffen and Sal Giglia, MilliporeSigma

Maximizing The Performance And Efficiency Of Your Sterilizing-Grade Filtration

For biomanufacturers, sterility assurance is a critical part of any process. To achieve this goal, sterilizing-grade filters have traditionally been used at multiple points in purification processes. However, as science and technology have advanced, so have the filtration options. Instead of the one-size-fits-all sterilizing-grade filter, you can now design a filtration train tailored to the specific needs of your application or unit operation. Selecting the right filter is the first step in reaping the benefits of today’s filters; optimizing their performance efficiency is key to maximizing the benefits for the lifetime of your process. 

Being able to depend on this performance efficiency means having confidence that your filters will always be able to reach a defined throughput or capacity in the set process time and, at the same time, provide the expected levels of microbial retention. Delivering this performance relies on your filter supplier having highly-controlled membrane manufacturing processes. Ideally, the filter supplier will also have a sound understanding of the fundamental mechanisms of filtration to provide guidance on both filter selection and how to maximize filter performance under your process conditions.

Optimizing the performance of sterilizing filters in a process is often shaped by the facility fit, which might constrain the operating conditions. For example, existing equipment may limit the process to either constant flow or constant pressure operations; in these cases, filtration processes can be designed and optimized to accommodate these limitations. Similarly, the scale of production or facility setup will determine whether cartridge filters must be used in stainless-steel housings or whether the process can accommodate a more flexible single-use system. These types of decisions influence multiple aspects of process design and optimization.