Next generation sequencing (NGS) is an advanced technology for rapid and broad detection of viral adventitious agents that can enhance the safety and accelerate the timelines of development of vaccines and other biologics. With the recent publication of the ICH Q5A(R2) guideline (https://www.ich.org/page/quality-guidelines), NGS is being internationally recognized as an alternative viral adventitious agents detection method for replacing the in vivo animal assays and PCR assays, and for replacing or supplementing the in vitro cell culture assays. The availability of the WHO reference viruses for qualification and validation of NGS can facilitate implementation of the technology for adventitious virus testing at different manufacturing stages to assure virus safety of the final product. Additionally, CBER’s comprehensive Reference Virus Database, which is made publicly available by the University of Delaware, can facilitate detection of known and novel viruses. However, NGS data analysis can be further enhanced by developing adventitious and endogenous virus detection pipelines and web-based tools for large data analysis, and unnecessary follow up of signals can be reduced by the development of strategies to help distinguish nonviral and viral sequences. Furthermore, NGS results can vary due to the type and complexity of the biological material being tested, which generally includes vaccine seed or vector virus preparations, cell banks, and unprocessed bulk harvest. This can be due to the use of different protocols for sample preparation of cell-free, cell-based, or mixed samples, and the different level of host cell nucleic acids that can be present in these sample types. Interestingly, different manufacturing platforms and conditions may produce different levels of host nucleic acids in the bulk harvest. This project proposes to optimize NGS virus detection in a high complexity unprocessed bulk harvest material to facilitate its routine use as an alternative method for viral adventitious agents detection. Additional efforts will optimize the bioinformatics analysis, including revising the RVDB pipeline to improve database updating and further refinement of the RVDB database through improvements to the annotation of nonviral sequences, identification of endogenous retroelements, and performance/usage improvements in the web application. Additionally, the adventitious virus detection strategy developed in our previous project PC3.1-305, will be finalized and the pipeline made publicly available. The work is funded by the NIIMBL Global Health Fund and involves international collaborations involving Office of Vaccines Research and Review in the Center for Biologics Evaluation and Research, U.S. Food and Drug Administration, Millipore Sigma, GSK, and the University of Delaware.
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Federal Stakeholder: Food and Drug Administration
GlaxoSmithKline, LLC
MilliporeSigma/EMD Serono
University of Delaware