Predicting antibody sequences to fight new viruses quickly

Rapid response for pandemics: single cell sequencing and deep learning to predict antibody sequences against an emerging antigen

NIH-funded research Keck Graduate Inst of Applied Life Scis · NIH-10845715

This study is working on a new way to quickly find antibodies that can fight off new viruses, which could help patients get faster and better treatments for viral infections.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionKeck Graduate Inst of Applied Life Scis NIH-funded
Lab location1 site (Claremont, United States)
Project IDNIH-10845715 on NIH RePORTER

What this research studies

This research focuses on developing advanced computational methods to predict antibody sequences that can effectively bind to new viral proteins. By utilizing deep learning techniques and analyzing structural features of antigens, the project aims to generate potential antibody candidates within 24 hours of identifying a new virus. Patients may benefit from faster and more effective treatments for emerging viral infections as this technology could lead to the rapid development of targeted therapies. The research involves complex modeling and data analysis to enhance our understanding of immune responses.

Who could benefit from this research

Good fit: Ideal candidates for this research are individuals at risk of or infected with emerging viral infections.

Not a fit: Patients with established viral infections that do not require new antibody treatments may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to the rapid development of effective antibody treatments for new viral infections, improving patient outcomes during pandemics.

How similar studies have performed: While the approach of using deep learning for antibody prediction is innovative, similar methodologies have shown promise in other areas of immunology, suggesting potential for success.

Where this research is happening

Claremont, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-13 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.