Immunogenicity is one of the most serious problems facing the design of new biologics. In a nutshell, immunogenicity is when the patients immune system mounts a response against the introduced biologic. There are a number of reasons this can happen, such as contamination of the biologic (for example, deamidation can create isoaspartic acid "residues" on biologic, triggering an immune response). See this detailed FDA review:
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commented
6 years ago
Immunogenicity is one of the most serious problems facing the design of new biologics. In a nutshell, immunogenicity is when the patients immune system mounts a response against the introduced biologic. There are a number of reasons this can happen, such as contamination of the biologic (for example, deamidation can create isoaspartic acid "residues" on biologic, triggering an immune response). See this detailed FDA review:
https://www.fda.gov/downloads/Drugs/DevelopmentApprovalProcess/SmallBusinessAssistance/UCM408709.pdf
It seems likely that deep learning could help model immunogenicity. Are there any public reports of data available?