RETROSPECTIVE EVALUATION OF LOW PH VIRAL INACTIVATION AND VIRAL FILTRATION DATA FROM MULTIPLE COMPANY COLLABORATION

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1 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 shengjiang.liu@bayer.com ** Associate director, Manufacturing Science and Technology, Shire hbrough@shire.com

2 OUTLINE 1. INTRODUCTION 2. LOW PH VIRAL INACTIVATION 3. VIRAL FILTRATION 4. CONCLUSION April 16 2

3 OUTLINE 1. INTRODUCTION 2. LOW PH VIRAL INACTIVATION 3. VIRAL FILTRATION 4. CONCLUSION April 16 3

4 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) April 16 4

Introduction to BioPhorum Operations Group The BioPhorum Operations Group (BPOG) is a cross industry collaboration that aims to share and develop operational best practices in the areas of drug

5 Introduction to BioPhorum Operations Group 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. BioPhorum website April 16 5

6 Viral Risk & Clearance in Biological Manufacturing Upstream Process Downstream Low ph Endogenous retrovirus-like particles Calicivirus Parvovirus Adventitious viruses S. Liu (2015) IBC-BDP Week, Huntington Beach, CA April 16 6

7 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 April 16 7

8 OUTLINE 1. INTRODUCTION 2. LOW PH VIRAL INACTIVATION 3. VIRAL FILTRATION 4. CONCLUSION April 16 8

9 Materials and Methods A total of 162 data points analyzed Protein Molecules Subclass An#bodies IgG1 102 IgG4 26 Other (1) 34 Number of data points (1) other = products not restricted to IgG1 or IgG4 monoclonal antibodies, such as non-fc fusion recombinant proteins, nondisclosed recombinant proteins, and IgG2 isotype monoclonal antibodies. Condi;ons ph Model viruses XMuLV 138 SuHV- 1 (PRV) 21 HSV Timepoints, min 0 to up to 240 Temperature, o C Protein Concentra#on (g/l) (2) 2-8 C, 15±1 C and 16 C g/l Buffer System acetate, citrate, and other (3) Analy#cal Assay Plaque or TCID50 Number of data points (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. April 16 9

Results and Discussion (I) Pseudorabies Retrovirus-E2888 Retrovirus+E2888 retrovirus ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected Mean

10 Results and Discussion (I) Pseudorabies Retrovirus-E2888 Retrovirus+E2888 retrovirus ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected Mean clearance of virus during low ph inactivation as a function of time for pseudorabies (left), retrovirus not conforming to ASTM E (1) (center), and retrovirus conforming to E (right) 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 E , Standard Practice for Process for Inactivation of Rodent Retrovirus by ph, ASTM International, West Conshohocken, PA, 2012, April 16 10

11 Results and Discussion (II) Retrovirus Pseudorabies ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected 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) April 16 11

Results and Discussion (III) Protein Concentration ph Virus Load ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected One-way analysis of retrovirus

12 Results and Discussion (III) Protein Concentration ph Virus Load ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected 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). April 16 12

13 OUTLINE 1. INTRODUCTION 2. LOW PH VIRAL INACTIVATION 3. VIRAL FILTRATION 4. CONCLUSION April 16 13

14 Materials and Methods A total of 392 data points analyzed Protein Molecules Subclass An#bodies IgG1 207 IgG4 72 Other (1) 113 Number of data points Size Virus Enveloped Number of data points Small : nm PPV, MMV No 148 Medium: nm Reo3, EMCV No 52 Large : >100nm PRV, HSV- 1, X- MuLV Yes 192 (1) The other category includes non- Fc fusion recombinant proteins, non- disclosed recombinant proteins, and IgG2 isotype April 16 14

15 Materials and Methods Condi;ons Polyethersulfone (n=150) Membrane Type Regenerated cellulose filters (n=242) Virus Load Range (log 10 ) ph Volumetric Loading (L/m 2 ) 127-2, ,321 Protein Concentra#on (g/l) Mass Loading (g/m 2 ) 271-7, ,935 Opera#ng pressure (psi) April 16 15

16 Results and Discussion (I) ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected Average log 10 reduction for model viruses by PP7-LRV4 filter class Statistical ranges Horizontal line in the center of the diamond represents group mean Height of the diamond represents 95% confidence interval of the group mean April 16 16

17 Results and Discussion (II) PES PES RC RC ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected 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). April 16 17

18 Results and Discussion (III) PES RC ( ) indicates virus infectivity reduced below detection limits ( ) indicates infectious virus detected 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 cm 2 Logistic regression fits the probability of a categorical outcome (e.g., residual infectivity detected) to a continuous factor (e.g., virus load log 10 PFU/cm 2 ) April 16 18

19 OUTLINE 1. INTRODUCTION 2. LOW PH VIRAL INACTIVATION 3. VIRAL FILTRATION 4. CONCLUSION April 16 19

20 Conclusion 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. E ) 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 Data set supports ASTM Std. E April 16 20

21 Conclusion 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 April 16 21

22 April 16 22

Ensuring Compliance: Regulatory guidance for virus clearance validation

Application Note Ensuring Compliance: Regulatory guidance for virus clearance validation Introduction To assure virus safety of biological therapeutics, regulatory guidance advocates an approach in which