Research Project
10005833
The PROTEOMETER; A Continuous Upstream Process Monitoring Engine PHS 398 SPECIFIC RESEARCH PLAN I. PROJECT SUMMARY. The global market for therapeutic monoclonal antibodies (T-mAbs) was $105 billion in 2018; twelve times the size of the clinical diagnostics market. Beyond their economic impact, mAbs have become a major force in medicine. This proposal addresses the fact that mAb proteoform variants of diminished activity and immunogenicity can be generated, but not monitored during production. The FDA has stressed the need to detect and remediated this problem since 2004 without success1. Proteoform specific analytics are not available for continuous monitoring of proteoforms in a fermentor. Novilytic is proposing herein a new analytical engine for continuous upstream process (CUSP) monitoring. The CUSP Proteometer being developed will have two analytical sectors working in parallel to extract samples from a fermentor, resolve mAb proteoforms, quantify them every 15- 30 min, and assess aberrant mAb proteoform production. Deviation in proteoform ratio will be sensed by the Proteometer, signaling of a potential aberrant will trigger in-depth bottom-up analyses. Aberrant proteoform suspects will be trypsin digested at 70 oC in an immobilized enzyme reactor, the effluent split by affinity selection into glycopeptide and non-glycopeptide fractions, and the fractions examined in PTM specific ways. PTM bearing peptide variants will be quantified and identified with multiple columns. More than 300 unattended analyses will be run during a two week mAb production campaign. The CUSP Proteometer data management system will blockchain code mAb structural and environmental data in relational source, time, protocol, and equipment performance blocks; enabling federal regulatory agencies to establish data authenticity, mAb quality throughout manufacturing, and potential aberrants. Having rapidly confirmed the safety and quality of a mAb lot it can be released by the FDA in ?real-time?. Additionally, these digital histories can be built into a library and used to identify and remediate process weaknesses, enhance process analytics, and improve manufacturing as mandated by the FDA.
