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RETROSPECTIVE EVALUATION OF LOW PH VIRAL INACTIVATION AND VIRAL FILTRATION DATA FROM MULTIPLE COMPANY COLLABORATION Shengjiang Shawn Liu, Ph.D.* and Helene Brough** * Head and Principal Scientist, Pathogen Safety Department, Bay Pharmaceuticals, Berkeley, CA 94710 [email protected] ** Associate director, Manufacturing Science and Technology, Shire [email protected]
Contribution Member Companies of BPDG Viral Safety Consortium
§ Joint research study on behalf of the BioPhorum Development Group (BPDG) viral safety consortium formed by viral safety experts from 10 companies including
• John Mattila (Regeneron Pharmaceuticals Inc.), • Mike Clark (AbbVie Inc.), • Shengjiang Liu (Bayer Corporation), • John Pieracci (Biogen), • Thomas R. Gervais (Bristol-Myers Squibb), • Eileen Wilson, Olga Galperina (GlaxoSmithKline plc), • Xinfang Li (ImmunoGen Inc.), • David Roush (Merck, Sharp and Dohme, Inc.), • Konstantin Zoeller (Novartis Pharma AG), • Helene Brough (Shire plc.).
§ The authors thank Justin Weaver (Alexion Inc.), Tom Klimek (Eisai Inc.), Norbert Schuelke
(Takeda Pharmaceuticals Co. Ltd.) for careful review of the paper.
§ This paper has been accepted for publication in the PDA Journal. (insert DOI if we have it)
§ The BioPhorum Operations Group (BPOG) is a cross industry collaboration that aims to share and develop operational best practices in the areas of drug substance manufacturing, process development, fill finish, IT, Technology Road Mapping, Supply Partner Phorum.
§ Established in 2008, the BPOG community currently comprises more than 1600 active participants from 30 companies.
§ Subject matter experts from BPOG member companies come together to develop common solutions to current and future industry challenges, facilitating the sharing of knowledge in biopharmaceutical manufacturing, accelerating the thinking and practices within the industry.
Risk-based Viral Clearance Approach on Viral Clearance Validation
§ Considerable resources are spent on viral clearance studies § Historic data sets required to enable generic viral clearance claims or reduced
testing in viral clearance studies § Difficult for one company alone to generate critical amounts of data to allow
statistical evaluation
To address above limitations, critical amounts of data from 10 companies have been collected for statistical evaluation of low pH viral and viral filtration. Approach § Building a database (Blinded, GLP compliant data) § Statistical evaluation § Review Results and Discussion § Conclusion
Other (1) 34 (1) “other” = products not restricted to IgG1 or IgG4 monoclonal antibodies, such as non-Fc fusion recombinant proteins, non-disclosed recombinant proteins, and IgG2 isotype monoclonal antibodies.
Model viruses Number of data points
XMuLV 138
SuHV-‐1 (PRV) 21
HSV-‐1 3
Condi;ons
pH 3.40-‐3.95
Timepoints, min 0 to up to 240
Temperature, oC 2-‐8°C, 15±1°C and ≥16°C
Protein Concentra#on (g/L) (2) 3.5-‐28.8 g/L
Buffer System acetate, citrate, and “other” (3)
Analy#cal Assay Plaque or TCID50 (2) If reported as range, average was taken for evaluation (3) “other” = non-disclosed buffers and others present in low numbers (e.g., N≤12), such as formate, glycine, HEPES, succinate and phosphate.
§ Mean clearance of virus during low pH inactivation as a function of time for pseudorabies (left), retrovirus not conforming to ASTM E2888-12 (1) (center), and retrovirus conforming to E2888-12 (right)
Pseudorabies Retrovirus-E2888 Retrovirus+E2888
§ Experiments considered to adhere to ASTM standard included: • hold temperature ≥ 15 °C • hold time ≥ 30 minutes • pH ≤ 3.6 throughout the hold • protein concentration ≤ 25 g/L
(1) ASTM E2888-12, Standard Practice for Process for Inactivation of Rodent Retrovirus by pH, ASTM International, West Conshohocken, PA, 2012, www.astm.org .
§ One-way analysis of virus Log Reduction Factor (LRF) vs temperature for retrovirus (left) and pseudorabies (right). Comparison of mean LRF (95% confidence) shows no statistically significant difference between 15±1°C and ≥16°C, while clearance at 2-8°C is significantly lower (p<0.0001)
§ One-way analysis of retrovirus LRF vs protein concentration (left), pH (center), and virus load (right). The mean is presented as bold black line while the least squares regression is grey (95% confidence).
§ There is a statistically significant trend for pH and virus load (p<0.001), while protein concentration is not significant (p=0.41).
§ One-way analysis of parvovirus removal by PES filters (top) and RC filters (bottom) including the mean (black) and a fit line with 95% shaded confidence interval (grey).
§ Logistic fit of infectious parvovirus for PES (left) and RC (right) filters indicates RC filters are susceptible to virus breakthrough when challenged with load over 0.6 log10 per cm2
§ Logistic regression fits the probability of a categorical outcome (e.g., residual infectivity detected) to a continuous factor (e.g., virus load log10PFU/cm2)
§ Viral clearance data sharing among biotechnology firms has resulted in comprehensive data sets for viral inactivation and viral filtration • Conducive to statistical review • Facilitates scientific discussions for a risk-based approach to process
characterization
§ The low pH inactivation data set shows • Pseudorabies (SuHV-1) is more readily inactivated under conditions that are
effective for retrovirus o This observation may form the foundation for assessing XMuLV alone (the current scope of
the ASTM std. E2888-12) as a sufficient model for low pH inactivation
• Reduced inactivation kinetics at 2-8°C highlight the importance of product specific characterization for recombinant proteins that cannot tolerate room temperature processing
§ The viral filtration data set shows • Small virus filters reliably reduce viral infectivity below assay detection limit for
retroviruses, herpesviruses, and picornaviruses o Reovirus clearance was effective in all cases o For parvovirus validation, the database shows performance is insensitive to many process
parameters o Viral clearance test artifacts such as virus challenge could have important effects on viral
clearance
• This analysis provides further rationale for viral filtration validation studies with parvovirus models only, representing worst case viral safety claims