Integration of immunogenicity risk assessment to facilitate a Quality by Design (QbD) approach to biologic discovery and development phases of therapeutic proteins enables mitigation of the clinical impact of immunogenicity. Systematic evaluation of potential immunogenicity risks enables optimal molecule design, selection of candidates, and adaptive CMC strategies, whilst maintaining developability and potency. A QbD approach accelerates development by avoiding cumbersome deimmunization procedures, and enables smooth regulatory interactions through the product lifecycle.

The Immunogenicity Database Collaborative (IDC) was established to address fragmented immunogenicity data and provide open-source resources for the industry. Following the release of IDC DB V1, a curated clinical dataset integrating therapeutic, sequence, and trial-level features, the initiative is expanding to V2 through coordinated working groups. This presentation will highlight V1 insights and progress toward V2, including the integration of nonclinical data, automated clinical data capture, and expanded annotation of clinical ADA impacts.

This talk reviews the evolving machine learning models for the prediction of TCR-pMHC interaction, assessing state-of-the-art methods and their performance on out-of-domain distributions. Key focus areas include the impact of feature representation, the size and diversity of available datasets, and the necessity of rigorous and independent benchmarking. We will discuss in detail the generalization of existing models to unseen epitopes and the selection of unbiased negative data as major challenges in the field.

The B Cell Immunogenicity Risk Assessment (BIRA) working group is an open forum advancing risk assessment of the B cell component of unwanted immune responses to biologics. Associated with the European Immunogenicity Platform (EIP) and the American Association of Pharmaceutical Scientists (AAPS), BIRA has established a collaborative framework to assess current knowledge, identify gaps, and harmonize concepts and terminology of B cell immunogenicity risk assessment. This presentation will provide an overview of BIRA’s objectives and progress to date.

In the context of the FDA's roadmap for advancing New Approach Methodologies (NAMs), which identifies unwanted immunogenicity as a priority area, the following will be presented: (1) An integrated framework for risk-assessment combining in-silico, in-vitro, and ex-vivo NAMs. (2) Examples of the successful use of NAMs in immunogenicity risk-assessment. (3) Design of platform-specific immunogenicity assessment strategies for emerging novel modalities. (4) The unmet need for standardized tools and reference reagents.

The therapeutic peptide field is expanding rapidly, driven by high target specificity, selectivity, favorable safety profile, and market demand. To date, generic complex peptides have largely been limited to synthetic manufacturing, regardless of the reference product’s origin. As FDA considers broadening the 505(j) pathway, this presentation explores key risk differences between synthetic and recombinant peptides and reviews available non-clinical strategies, highlighting strengths and gaps in immunogenicity risk assessment for recombinant peptides in the generic space.

Positive control selection is critical to ensuring neutralizing antibody assays generate robust, interpretable data suitable for regulatory decision-making. Poorly chosen controls can mask assay limitations, obscure clinically relevant neutralization, and introduce risk as programs advance. This presentation highlights practical strategies for selecting and qualifying biologically relevant positive controls that reflect biological relevance, improve assay performance, and reduce development risk, ultimately strengthening confidence in immunogenicity assessments across biologics.