AUTHOR=Santuari Luca , Bachmann Salvy Marianne , Xenarios Ioannis , Arpat Bulak 

TITLE=AI-accelerated therapeutic antibody development: practical insights

JOURNAL=Frontiers in Drug Discovery

VOLUME=4

YEAR=2024

URL=https://www.frontiersin.org/journals/drug-discovery/articles/10.3389/fddsv.2024.1447867

DOI=10.3389/fddsv.2024.1447867

ISSN=2674-0338

ABSTRACT=<p>Antibodies represent the largest class of biotherapeutics thanks to their high target specificity, binding affinity and versatility. Recent breakthroughs in Artificial Intelligence (AI) have enabled information-rich <italic>in silico</italic> representations of antibodies, accurate prediction of antibody structure from sequence, and the generation of novel antibodies tailored to specific characteristics to optimize for developability properties. Here we summarize state-of-the-art methods for antibody analysis. This valuable resource will serve as a reference for the application of AI methods to the analysis of antibody sequencing datasets.</p>