Smart Antibodies: Harnessing AI for Targeted Immunotherapy

AI-powered algorithms analyze massive datasets to predict antigen-antibody binding affinities and optimize antibody sequences with unprecedented speed and accuracy. Machine learning models simulate 3D structures, identify potential off-target effects, and suggest mutations that enhance efficacy or reduce toxicity. This convergence of immunology and AI accelerates drug discovery, enabling the design of antibodies that precisely target disease mechanisms, such as checkpoint inhibitors in cancer or neutralizing antibodies against viral pathogens.