Application and outcomes of an immunogenicity risk assessment strategy aimed at optimizing portfolio performance. Immunogenicity risk assessments can be used to optimize individual projects or portfolios to acceptable immunogenicity risk levels. ADA responses vary widely in clinical trials, with the presence of ADA itself a risk factor for clinical impact. Whilst ‘predicting immunogenicity’ might seem impossible, forecasting incidence of ADA formation in first-in-human trials helps to prepare teams for potential consequences. I review a risk assessment methodology, highlighting case studies to demonstrate application at the portfolio level.

Over the last several years there has been exponential increase of antibody-drug conjugates in various stages of development. Several novel ADC formats being explored include unnatural antibodies (bispecifics, probodies, etc.) as well as novel payloads (immune stimulators, protein degraders, etc.). It is important to understand the immunogenicity risk of these novel ADCs and their clinical relevance. Better understanding of potential immunogenicity of these novel ADCs should help in their clinical development.

Testing of biotherapeutics across species typically induces an Anti-Drug Antibody (ADA) response. When the therapeutic is a monoclonal antibody (mAb), these ADA are generally directed against the constant regions of the mAb, but may be against other epitopes. The impact of these ADA on PK, PD, and the toxicity profile of the therapeutic mAb, as well as novel ways to mitigate their formation, will be examined.

In vitro assays are widely used preclinically during the development of biologics to assess immunogenicity liabilities and select candidates. However, there is considerable diversity in assay format among companies and no alignment on the analysis methods. Here we will discuss the recent progress of a cross-industry work to develop common reference biologics for preclinical immunogenicity risk assessment, a critical first step toward assay standardization and harmonization.

Immunogenicity can compromise the safety and/or efficacy of therapeutic protein products, and is a priority issue for regulatory agencies. In addition to poor patient outcomes, the social and economic costs associated with neutralizing antibodies are considerable. In this presentation, I survey the immunogenicity of approved therapeutic proteins, discuss strategies for clinical management of immunogenicity, and identify challenges associated with circumventing the immune responses to approved protein therapeutics.

In vitro assays are a requirement for characterizing the immunogenicity risk of impurities in generic peptide candidates submitted for ANDA consideration to the FDA in lieu of clinical immunogenicity assessment. Guidance issued in 2021 has led to a maturing of the science and assays supporting these ANDA submissions today. Here, we review an industry perspective on applying these assays for generic peptides and possibly for other classes of drugs.

As the landscape of biologic therapeutics continues to evolve with new and intricate innovations, it is imperative to conduct a thorough assessment of immunogenicity risks and devise a clinical strategy to mitigate potential immunological adverse events. An integral component of this risk assessment involves evaluating the presence of pre-existing antibodies (pre-ADAs). This presentation will introduce a multi-platform approach for detecting and characterizing pre-ADAs, complemented by a detailed case study.

We develop machine learning models to optimize in parallel multiple drug-like properties of biologics while minimizing liabilities including immunogenicity. We apply these to the bacterial enzyme IdeS to design a therapeutic for chronic autoantibody-mediated diseases, and demonstrate the success of this approach via in vivo and in vitro assays. We also illustrate its generalizability by applying it to deimmunize a wide array of clinically approved biologics in silico. Finally, we present a general mathematical framework enabling this process to be applied to virtually any protein in silico, using only the protein sequence as input.

HLA antigen presentation is the cornerstone of adaptive immunity. My talk will describe our journey towards accurate prediction of HLA antigen presentation. I will demonstrate how the end result has unprecedented accuracy across all three HLA-II loci, and how this reveals an earlier underappreciated contribution of DRB345, DQ and DP to the immunopeptidome. Further, I will showcase how these loci share a critical role when interpreting MAPPs data and predicting immunogenicity.

Immunogenicity mitigation is a multifactorial design challenge. As a proof-of-concept study, we sought to reduce MHC-II presentation of an immunogenic monoclonal antibody. While T cell antigenicity was reduced, this correlated with improvements in developability (self-association and polyspecificity) rather than elimination of MHC II epitopes. This prompted an expanded analysis of over 100 clinically evaluated antibodies that confirmed a correlation between self-association and polyspecificity with dendritic cell uptake and immunogenicity risk.

Effective preclinical prediction of immunogenicity risk is an ongoing challenge for biologics development. A key driver of a clinically impactful anti-drug antibody response is the interaction between antigen-specific B cells and CD4 T cells in the germinal center. We developed a novel B-T cell co-culture assay that can flag molecules with both T and B cell epitopes, identifying those most likely to drive a clinically impactful immune response.