(301c) Parvovirus-Retentive Filter Performance and Removal Mechanisms during Process Interruptions

Parvovirus retention by some commercially available membrane filters can significantly decline when flow is stopped and restarted during processing. These process interruptions can be a normal part of the filtration process or they can be unanticipated and their impact may not have been evaluated during viral clearance validation. Mitigation of the risk of decreased viral removal includes careful selection of the filter, operating parameters, process controls, and validation strategy. Each of these approaches necessitate an improved understanding of the underlying physical phenomena. However, due to differences in membrane structure and chemistry, the results and underlying governing phenomena can vary between different filters.

In this study, experimental data were generated with a commercial parvovirus-retentive filter which previously had not shown a significant decrease in virus retention following process interruptions. A wide range of parameters related to the operating conditions, the nature of the flow stoppage, and the membrane filter were evaluated. Custom single-layer devices enabled quantification of the impact of process interruptions which had been limited in previous work with standard two-layer devices. The results were compared to a new, simplified mechanistic model of virus retention during flow interruptions, which is based on the principle of size exclusion and accounts for properties of the membrane structure. The model results were consistent with the experimental data, predicting that the decreased clearance associated with flow stoppages is largely independent of the membrane pore size distribution, but may be sensitive to the membrane morphology (i.e. the effective number of separation layers). Both the model and experimental data confirmed that for the single-layer, asymmetric membrane studied, only small decreases (<0.5 logs) occur in virus retention following a process interruption for a wide range of operating parameters. This increased understanding and the experimental data are important tools that can support the development and justification of risk mitigation strategies.