REPTOR: Using machine learning to find new antibody treatments
REPTOR: accelerating antibody discovery and improving hits with machine learning
This project is creating new software to help scientists discover better antibody treatments for autoimmune diseases more quickly.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Abterra Biosciences, INC. NIH-funded |
| Lab location | 1 site (San Diego, United States) |
| Project ID | NIH-11194970 on NIH RePORTER |
What this research studies
Current methods for finding new antibody treatments are often slow and may miss important options. This project aims to develop advanced software that uses high-throughput sequencing to improve how we find these antibodies. The software will make it easier to incorporate detailed genetic information into existing discovery methods, speeding up the process and increasing the chances of finding effective treatments. It will also help improve existing antibody candidates by learning from the body's natural immune responses.
Who could benefit from this research
Good fit: Patients with autoimmune diseases or other conditions that could be treated with antibody therapies might indirectly benefit from this research.
Not a fit: Patients whose conditions are not treated with antibody therapies would likely not see a direct benefit from this specific software development.
Why it matters
Potential benefit: If successful, this work could lead to faster development of more effective antibody therapies for patients with autoimmune diseases and other conditions.
How similar studies have performed: While traditional antibody discovery methods are decades old, newer single-cell approaches are gaining traction, and this project aims to integrate large-scale data in a novel way that has previously been challenging.
Where this research is happening
San Diego, United States
- Abterra Biosciences, INC. — San Diego, United States (Active)
Researchers
- Principal investigator: Castellana, Natalie — Abterra Biosciences, INC.
- Study coordinator: Castellana, Natalie
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.