Using machine learning to predict how antibodies interact with antigens

Machine learning for identifying antigen-antibody interactions from massive sequencing data

['FUNDING_R01'] · UT SOUTHWESTERN MEDICAL CENTER · NIH-11105726

This study is exploring new ways to use computer technology to better understand how antibodies and antigens work together, which could help find new treatments and tests for immune-related diseases, making things easier and faster for patients.

Quick facts

Phase['FUNDING_R01']
Study typeNih_funding
SexAll
SponsorUT SOUTHWESTERN MEDICAL CENTER (nih funded)
Locations1 site (DALLAS, UNITED STATES)
Trial IDNIH-11105726 on ClinicalTrials.gov

What this research studies

This research focuses on utilizing advanced machine learning techniques to analyze large sequencing datasets in order to predict interactions between antibodies and antigens. By leveraging high-throughput sequencing technologies and innovative protein structure prediction models, the project aims to develop accurate and efficient methods for identifying these interactions. This could lead to the discovery of new therapeutic antibodies and the creation of diagnostic tools for immune-related diseases, ultimately improving patient care. The approach is designed to overcome the limitations of traditional experimental methods, which are often slow and expensive.

Who could benefit from this research

Good fit: Ideal candidates for this research include individuals with immune-related diseases who may benefit from improved diagnostic methods or new antibody therapies.

Not a fit: Patients without immune-related conditions or those who do not respond to antibody therapies may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to faster and more accurate diagnostic tools and new therapies for immune-related diseases.

How similar studies have performed: Previous research has shown promise in using machine learning for similar predictive tasks, indicating a potential for success in this novel application.

Where this research is happening

DALLAS, 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.

View on NIH RePORTER →

Last reviewed 2026-05-15 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.