Precision at Every Scale: Efficiency in AI-Driven De Novo Antibody Design

The precise de novo design of antibodies remains a therapeutic challenge. The AI platform, GaluxDesign, validated its capabilities through two strategies: prior work showed comprehensive exploration, and this study validates a high-efficiency, precision approach. GaluxDesign was applied to eight distinct epitopes across six therapeutic targets, synthesizing and testing a focused set of 50 de novo IgG candidates per epitope. This precision-scale campaign yielded a 10.5% binder rate (estimated EC ₅₀ < 100 nM), identifying target-specific binders for seven of eight epitopes. These novel antibodies exhibit therapeutically relevant properties, with sub-nanomolar to single-digit nanomolar dissociation constants (K _d ) confirmed for multiple candidates. These findings confirm that a high-efficiency, precision-scale workflow is a viable approach for generating novel, high-affinity therapeutic antibodies.