Nano-scale virus removal filters have been used for over 20 years to effectively reduce and eliminate the risk of viral contamination in biopharmaceutical APIs. By utilizing what is thought to be a size-exclusion mechanism, virus filtration is largely credited with a consistent and non-destructive form of broadly effective viral clearance for the biotherapeutics of today. As filters of this type have demonstrated a viral capacity that is linearly scalable with surface area and total viral challenge, more evidence has accrued in favor of this size-exclusion mechanism having the primary role, leading to the development of an intelligent study design strategy that has potential to demonstrate viral clearance success. By understanding that these filter types have a viral capacity for any given process; limiting the total viral challenge during the viral clearance study is an important consideration to achieving robust viral clearance (&gt; 4 Log Reduction Value) . Since certain filtration artifacts such as low pressure, process pause, and feed solution effects have been shown to minimally impact virus removal capability, it will be valuable to understand if the impacts of these effects can be minimized. By utilizing intelligent study design, this study does successfully demonstrate that the impact of these effects can be mitigated significantly, if not completely, when using a wide variety of virus removal filters. By using a range of small-virus filter types, with differing membrane materials and pore sizes, and under a host of varying process parameters; this study shows that robust viral clearance is achieved under a range of challenging process conditions when intelligent study design is implemented. Furthermore, the observed success of this strategy goes further to add to the current body of knowledge confirming the primary size-exclusion mechanism.

Understanding the impacts of viral clearance artifacts in nanofiltration

251st National Meeting (2016)

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