AI Developments for T and B Cell Receptor Modeling and Therapeutic Design
Abstract
Artificial intelligence (AI) is accelerating progress in modeling T and B cell receptors by enabling predictive and generative frameworks grounded in sequence data and immune context. This chapter surveys recent advances in the use of protein language models, machine learning, and multimodal integration for immune receptor modeling. We highlight emerging strategies to leverage single-cell and repertoire-scale datasets, and optimize immune receptor candidates for therapeutic design. These developments point toward a new generation of data-efficient, generalizable, and clinically relevant models that better capture the diversity and complexity of adaptive immunity.
Fields of Study & Subjects
vaccines and immunoinformatics approaches
T-cell and B-cell Immunology
Machine Learning in Bioinformatics
Publication details
- Journal / source
- arXiv (Cornell University)
- Publication date
- 23 January 2026
- Document type
- Preprint