Lab-in-the-loop therapeutic antibody design with deep learning
Nathan C. Frey, Isidro Hötzel, Samuel Stanton, Ryan L. Kelly, Robert G. Alberstein, Emily K. Makowski, Karolis Martinkus, Daniel Berenberg, Jack J. Bevers, Tyler Bryson, Pamela Chan, Yongmei Chen, Alicja Czubaty, Tamica D’Souza, Henri Dwyer, , Vladimir Gligorijević
This paper introduces a machine learning framework for therapeutic antibody design that integrates computational methods with experimental validation, resulting in significantly improved binding affinity for multiple targets.
bioRxiv · Feb 19, 2025 · PreprintBioengineering