Innovative AI Technique Accelerates Discovery of Therapeutic Antibodies for Pandemic Readiness

Scientists at The Scripps Research Institute have introduced a groundbreaking approach that combines artificial intelligence (AI) with advanced imaging technologies to identify therapeutic antibodies more swiftly and accurately. Published in Science Advances, this novel method dramatically reduces the time required to find protective antibodies—from several weeks to less than a day—while supporting scalable research efforts that minimize data congestion. Such rapid and precise antibody identification is vital for developing treatments against infectious diseases like influenza and HIV, especially during emergent health crises.

This pioneering technique leverages AI to analyze the structural intricacies of immune responses. By integrating cryo-electron microscopy (cryo-EM)—which captures near-atomic resolution images of antibodies binding to their targets—and the AI-powered ModelAngelo tool that constructs molecular models, researchers can pinpoint the most promising therapeutic candidates efficiently. The innovative Structure-to-Sequence (STS) method builds upon prior work that mapped antibody responses within days, now enhanced by AI to streamline discovery.

According to senior author Andrew Ward, the approach marks a paradigm shift in antibody research. “Harnessing AI to interpret structural data allows us to identify potent therapeutic antibodies in hours, surpassing traditional methods’ success rates. This has profound implications for pandemic preparedness and rapid therapeutic development.”

Antibodies, essential components of the immune system, neutralize pathogens and have become primary agents in treating infections and cancers. However, current discovery processes are laborious, involving screening thousands of candidates to find those that effectively target specific locations on pathogens. This bottleneck has slowed vaccine and drug development, but the new AI-integrated method aims to overcome these hurdles.

The team demonstrated the practical potential of their approach by identifying antibodies that provided significant protection against influenza in animal studies. The rapid identification of such protective antibodies underscores the method’s potential for addressing urgent health threats.

Beyond influenza, this technology promises broad applications for emerging infectious diseases. Its speed and precision could revolutionize treatment development and response times during outbreaks. Ward highlighted, “Integrating AI with immune response analysis accelerates vaccine development and enhances our capacity to confront new pathogens swiftly.”

Collaborating with other laboratories, the team is now exploring how ModelAngelo can further optimize therapeutic antibody discovery. Ultimately, this method could bring life-saving treatments to patients faster than ever, bolstering global health defenses against future pandemics.

Source: https://medicalxpress.com/news/2025-09-ai-therapeutic-antibodies-boost-pandemic.html