Database studies supporting filter performance
In addition to the above discussed studies addressing specific filter parameters, database studies have been performed by industry groups, contract testing labs and regulatory agencies with the goal of gaining a cross-industry view of the robustness of virus filters in real-word manufacturing processes. These individual studies established robust viral clearance (at least 4 logs LRV) despite changes in pressure (flow pause), feedstream solution conditions, virus stock quality, or filter type. It was also demonstrated that newer generation small virus retentive filters may provide a slightly higher median clearance value (5.0 vs 5.67 LRV, combining all generational data) and less variability compared to first generation small virus retentive filters (Lute 2015)(Figure 2). In addition to these studies, several companies have reported viral filter performance in various combinations of process parameters from internal commercial processes and viral clearance studies. These datasets provided strong evidence of robust removal of both parvovirus and retrovirus species with various commercial viral filters in varying combinations of processes and product types (Gefroh, Dehghani et al. 2014, Stuckey, Strauss et al. 2014, Stanley, Holmes et al. 2021). Tables 2-4 summarize key findings from these industry database studies.
Considerations for Performing Viral Filter Clearance Studies” To understand the capability of a purification process to remove viral contaminants, viral filter clearance validation should be conducted in a laboratory equipped for virologic work on a qualified scaled-down model of the production process in accordance with the principles of good laboratory practices. Considerations for viral filtration scale-down models include filter load/feed material, virus spiking strategies, prefilter use, and the potential impacts of process parameters. Scale-down models should represent the commercial production procedure as closely as possible (EMEA 1996, ICH 1998). This is achieved by performing scale-down studies using feed materials and process parameters that represent the manufacturing or worst-case conditions. The small scale model is typically qualified for use by demonstrating comparable process performance with at scale operation, including yield, pressure (during constant flow operation), or flow (during constant pressure operation). Therefore, the scale down qualification experiments are typically limited to brief confirmatory runs.