Team ADB

Bispecific antibodies represent one of the most promising classes of biologic therapeutics, capable of engaging two molecular targets simultaneously and enabling new treatment strategies across oncology, immunology, and other complex disease areas. However, their engineering remains challenging due to structural constraints, limited predictability of dual-target interactions, and the need to optimize stability, specificity, and manufacturability.

At Team ADB, our mission is to address these challenges through the development of an AI-powered platform for the sterically guided design of bispecific antibodies. By integrating machine learning, computational structural biology, bioinformatics, and immunology, our platform will incorporate three-dimensional steric constraints directly into the design process, reducing reliance on large-scale experimental screening.

We aim to make the identification of viable bispecific antibody candidates more efficient, thus shortening development timelines and expanding the range of accessible target combinations.