Immunogenicity risk assessment and in silico tools
Multiple factors can lead to immunogenicity. These include intrinsic factors like the sequence and structure of a given protein and the post translational modifications that can occur during the process (Jiskoot, Rispens, & Kijanka, 2019). In addition, risk factors also include those from unwanted impurities that can carryover from purification during drug manufacturing, liabilities due to formulations and excipients and devices as well as how the drug gets administered (Jiskoot et al., 2019). To understand the sequence-based risk of residual proteins associated with the API, multiple algorithm-based tools were used. The EpiMatrix algorithm evaluate the ability of processed peptides (9-mer sequences) in a protein to bind with the 8 most prevalent MHC alleles that represent over 98% of the human population (Bailey-Kellogg et al.; Goey, Bell, & Kontoravdi, 2018; Jawa et al.). Multiple high-density T-cell epitopes or clusters were assessed using the ClustiMer tool. Additionally, the epitopes that could be processed and presented were further analyzed in the JanusMatrix to determine which predicted epitopes may be cross-react with epitopes derived from the human genome on the basis of conservation of T cell receptor (TCR)-facing residues. ClustiMers with JanusMatrix scores greater than 1 were excluded from the analysis based on the assumption that the auto-reactive TCR containing cells were eliminated during T cell development (Bailey-Kellogg et al.).