Designing antibodies using advanced computer methods
Deep learning based antibody design using high-throughput affinity testing of synthetic sequences
This study is working on a faster and cheaper way to create and test new antibodies that could help treat diseases like cancer and infections, using advanced computer technology to find the best options more quickly.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Massachusetts Institute of Technology NIH-funded |
| Lab location | 1 site (Cambridge, United States) |
| Project ID | NIH-10833458 on NIH RePORTER |
What this research studies
This research focuses on creating a new method for quickly designing and testing antibodies that can be used for treating diseases like cancer and infections. By utilizing advanced computer technology, the researchers aim to display millions of antibody sequences and test them efficiently, which could save time and reduce costs compared to traditional methods. The project combines molecular dynamics and machine learning to refine antibody designs based on testing data, ultimately aiming to identify the most effective antibodies with fewer experiments. This innovative approach seeks to improve the effectiveness and efficiency of antibody development.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals affected by cancer or infectious diseases who may benefit from new antibody therapies.
Not a fit: Patients who do not have cancer or infectious diseases may not receive direct benefits from this research.
Why it matters
Potential benefit: If successful, this research could lead to faster and more effective treatments for various diseases, including cancer and infectious diseases.
How similar studies have performed: Other research has shown promise in using computational methods for antibody design, indicating potential success for this innovative approach.
Where this research is happening
Cambridge, United States
- Massachusetts Institute of Technology — Cambridge, United States (Active)
Researchers
- Principal investigator: Gifford, David K — Massachusetts Institute of Technology
- Study coordinator: Gifford, David K
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page below.