CHOPPI: A web tool for the analysis of immunogenicity risk from host cell proteins in CHO-based protein production

Authors


  • Competing Interests: Anne S. De Groot and William D. Martin are senior officers and majority shareholders at EpiVax, Inc., a privately-owned immunoinformatics and vaccine design company located in Providence, RI USA. Lenny Moise and Frances Terry are employees at EpiVax, in which Lenny Moise holds stock options. These authors acknowledge that there is a potential conflict of interest related to their relationship with EpiVax and attest that the work contained in this research report is free of any bias that might be associated with the commercial goals of the company. In addition to his role as a faculty member at Dartmouth, Chris Bailey-Kellogg is co-founder and CTO of Stealth Biologics, LLC, a therapeutic protein design company. Dartmouth has worked with him to manage all potential conflicts of interest arising from his commercial affiliation, and he likewise affirms that this paper presents work free of any bias.

ABSTRACT

Despite high quality standards and continual process improvements in manufacturing, host cell protein (HCP) process impurities remain a substantial risk for biological products. Even at low levels, residual HCPs can induce a detrimental immune response compromising the safety and efficacy of a biologic. Consequently, advanced-stage clinical trials have been cancelled due to the identification of antibodies against HCPs. To enable earlier and rapid assessment of the risks in Chinese Hamster Ovary (CHO)-based protein production of residual CHO protein impurities (CHOPs), we have developed a web tool called CHOPPI, for CHO Protein Predicted Immunogenicity. CHOPPI integrates information regarding the possible presence of CHOPs (expression and secretion) with characterizations of their immunogenicity (T cell epitope count and density, and relative conservation with human counterparts). CHOPPI can generate a report for a specified CHO protein (e.g., identified from proteomics or immunoassays) or characterize an entire specified subset of the CHO genome (e.g., filtered based on confidence in transcription and similarity to human proteins). The ability to analyze potential CHOPs at a genomic scale provides a baseline to evaluate relative risk. We show here that CHOPPI can identify clear differences in immunogenicity risk among previously validated CHOPs, as well as identify additional “risky” CHO proteins that may be expressed during production and induce a detrimental immune response upon delivery. We conclude that CHOPPI is a powerful tool that provides a valuable computational complement to existing experimental approaches for CHOP risk assessment and can focus experimental efforts in the most important directions. Biotechnol. Bioeng. 2014;111: 2170–2182. © 2014 The Authors. Biotechnology and Bioengineering Published by Wiley Periodicals, Inc.

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