George W. Kasun

IgDesign: In vitro validated antibody design against multiple therapeutic antigens using inverse folding

IgDesign designs antibody CDRs using deep learning and validates them in vitro, showing high success rates and improved affinities for multiple therapeutic antigens.

Unlocking de novo antibody design with generative artificial intelligence

Deep generative models combined with high-throughput screening design de novo anti-HER2 antibodies without further optimization, yielding nanomolar binders functionally comparable or superior to trastuzumab.

Antibody optimization enabled by artificial intelligence predictions of binding affinity and naturalness

Language models trained on high-throughput affinity data predict KD of unseen antibody variants across three orders of magnitude, and a "naturalness" score can be optimised alongside affinity.