Towards high-quality large-scale T cell receptor antigen specificity data: challenges and promises

TL;DR - This Nature Methods perspective argues that T cell receptor–antigen specificity research is constrained more by noisy, weakly validated data than by data volume. Better experimental validation, statistical filtering, and multimodal AI could enable reliable large-scale datasets for immunology and therapeutic research.

• High-throughput methods and databases have rapidly expanded available TCR–antigen specificity records.
• Many existing records lack strong validation or contain substantial noise, limiting their utility.
• Rigorous experiments and statistical quality controls are needed to produce high-confidence specificity labels.
• Multimodal AI may help integrate complementary evidence and improve TCR specificity data quality.