In this episode of On AIRR, Dr. Bjoern Peters, Professor at the La Jolla Institute for Immunology (LJI), explores how high-quality data serves as the foundation for advancing AI-based immunological predictions and diagnostics.
Originally from Germany, Dr. Peters began his academic journey in theoretical physics at Hamburg, focusing on quantum optics, before pivoting to biophysics during his PhD at Humboldt University. This shift was inspired by the challenge of understanding epitope presentation pathways and the limitations of epitope-prediction algorithms, which led him to work with Dr. Alessandro Sette at LJI to develop the Immune Epitope Database (IEDB) — the world’s largest resource for immune epitope data.
Throughout the conversation, Dr. Peters traces the evolution of epitope research, starting with his work on MHC-peptide binding predictions and expanding into broader immunological data collection. He emphasizes that high-quality datasets often outcompete algorithmic improvements and shares the story of how the IEDB was established to consolidate immune epitope data. The conversation explores the status of data standardization and use of ontologies in structuring biomedical data, particularly in immunology. Dr. Peters highlights how work done by the IEDB and the Adaptive Immune Receptor Repertoire Community (AIRR-C) in these areas is critical for advancing immunology and enabling prediction and diagnostics. Finally, the discussion covers challenges of predicting epitopes from immune repertoires, the growing interest in using AIRR sequencing for diagnostics, and the importance of rigorous, unbiased validation of prediction models for clinical applications.
Comments are welcome to the inbox of onairr@airr-community.org or on social media under the tag #onAIRR. Further information can be found here: https://www.antibodysociety.org/the-airr-community/airr-c-podcast.
The episode is hosted by Dr. Ulrik Stervbo and Dr. Zhaoqing Ding.
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