Recorded live at the 4th Antwerp TCR meeting, this special panel episode brings together three leading experts in T-cell receptor (TCR) biology and computational immunology to explore one of the field's most challenging questions: Can we predict which epitopes a given TCR recognizes, and what would that unlock for medicine?
Joining the discussion are:
Dr. Hannah Meyer (Cold Spring Harbor Laboratory), whose research focuses on thymic selection and the mechanisms that shape a safe and functional T-cell repertoire.
Prof. Kilian Schober (Friedrich-Alexander-Universität Erlangen-Nürnberg), a physician-scientist studying antigen-specific T-cell responses in infection, autoimmunity, and cancer.
Prof. Hashem Koohy (University of Oxford), who applies computational and machine learning approaches to uncover the principles governing T-cell antigen recognition.
Together, they discuss why TCR–epitope prediction remains one of immunology's grand challenges, despite rapid advances in AI and structural biology.
Key topics covered include:
Why predicting TCR specificity is uniquely difficult, particularly because of HLA/MHC diversity
Diagnostic value of epitope-TCR prediction across infectious disease, autoimmunity, and cancer
How cross-reactivity links infectious disease, autoimmunity, and cancer immunology
Why the biggest obstacle may be a lack of data rather than a lack of algorithms
The difference between predicting and truly decoding TCR–epitope recognition
New experimental and computational approaches
What a future blood-test-based diagnostic platform might look like, and what it will take to get there
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