Predicting Neoantigen Immunogenicity from In Vivo Immune Editing
Timothy J. Sears, Ko-Han Lee, María Muñoz Pérez, Robert Rasmussen, Meghana S. Pagadala, Kairi Tanaka, Ajay Subramanian, Everett James Moding, Maurizio Zanetti, Hannah K. Carter
This paper introduces NEMo, a machine learning model that predicts neoantigen immunogenicity using in vivo immune editing data, showing improved stratification of progression-free survival across multiple clinical settings.
bioRxiv · Sep 18, 2026 · PreprintCancer Biology