AI can forecast individual vaccine response before the shot is given

A collaborative effort led by Arizona State University analyzed blood from more than 4,000 volunteers, including both healthy subjects and those with immune-compromising conditions. Researchers measured antibodies to 185 viral, bacterial and autoimmune targets and fed the data into a deep-learning model. The algorithm identified specific pre-existing antibodies—dubbed sentinel antibodies—that were linked to strong COVID-19 vaccine responses.

Notably, some immunosuppressed participants still mounted vigorous immunity, while about 5% of healthy participants exhibited poor responses. The work, published in Cell Press Blue, demonstrates how AI can parse millions of immune signals to gauge “immune readiness.” If validated for other vaccines, the technique could help clinicians decide who may need extra doses or closer monitoring, moving vaccination toward a more personalized paradigm.