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.