Developing software to design better antibodies for treating diseases
Official title: Rapid structure-based software to enhance antibody affinity and developability for high-throughput screening: Aiming toward total in silico design of antibodies
Funded at Dnastar, INC. · NIH-11072991 · Data updated 2026-11-12
This study is working on new software that helps scientists design better medicines called monoclonal antibodies, making it faster and cheaper to find the best treatments for patients.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Dnastar, INC. NIH-funded |
| Lab location | 1 site (Madison, United States) |
| Project start | May 1, 2020 |
| Project end | April 30, 2026 |
| Funding year | 2025 |
| Award (this year) | $1,030,000 |
| NIH project number | 5R44AI155254-06 |
| Project ID | NIH-11072991 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals with conditions that could be treated with monoclonal antibodies, including autoimmune diseases and infections caused by the novel coronavirus.
✕Less likely to help
Patients who do not have conditions treatable by monoclonal antibodies may not benefit from this research.
What this research studies
This research focuses on creating advanced software that uses computational methods to enhance the design of therapeutic monoclonal antibodies. By improving the prediction of how antibodies interact with specific proteins, the project aims to speed up the drug development process and reduce costs. The software will help identify the most effective antibodies early in the development phase, allowing researchers to concentrate on the best candidates. This innovative approach leverages artificial intelligence and advanced algorithms to transform antibodies with lower binding affinities into those with significantly higher affinities.
Why it matters
Potential benefit: If successful, this research could lead to faster and more effective treatments for diseases by improving the development of therapeutic antibodies.
How similar studies have gone: Other research has shown promise in using computational methods for antibody design, indicating that this approach could lead to significant advancements in the field.
Where this research is happening
-
Dnastar, INC.
Madison, United States Active
Researchers
- Principal investigator: Blattner, Frederick R — Dnastar, INC.
- Study coordinator: Blattner, Frederick R
Related research
Other NIH-funded projects on the same topics.
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Developing software to analyze and predict antibody structures and targets.
This study is working on new software that helps understand the different antibodies your body makes when fighting infections or getting vaccinated, which could lead to better treatments and personalized care for conditions like autoimmune diseases.
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.