Using AI to improve a database for pediatric HIV prevention products
Official title: Use of Artificial Intelligence/Machine Learning (AI/ML) to Enhance the STEP Pediatric Excipient Database
Funded at Advanced Bioscience Laboratories, INC. · NIH-11161819 · Data updated 2026-11-12
This study is working on improving a special database to help create better and safer HIV treatments for kids by using advanced technology, so that young patients can have access to new and effective ways to prevent HIV.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Advanced Bioscience Laboratories, INC. NIH-funded |
| Lab location | 1 site (Kensington, United States) |
| Project start | August 1, 2024 |
| Project end | July 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $1,193,090 |
| NIH project number | 75N93023D00001-0-759302400005-1 |
| Project ID | NIH-11161819 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are children at risk for HIV or those involved in pediatric HIV prevention programs.
✕Less likely to help
Patients who are not children or those who are not at risk for HIV may not receive any benefit from this research.
What this research studies
This research aims to enhance the STEP Pediatric Excipient Database by employing artificial intelligence and machine learning techniques. The project will focus on developing and testing new therapeutic and prevention products for HIV, particularly those suitable for children. By modernizing the database, the research seeks to streamline the process of product discovery and development, ultimately leading to safer and more effective treatments. Patients may benefit from improved access to innovative HIV prevention strategies tailored for pediatric populations.
Why it matters
Potential benefit: If successful, this research could lead to the development of safer and more effective HIV prevention products for children.
How similar studies have gone: Other research has shown success in using AI and machine learning to enhance medical databases and improve product development, indicating a promising approach.
Where this research is happening
-
Advanced Bioscience Laboratories, INC.
Kensington, United States Active
Researchers
- Principal investigator: Silvera, Peter — Advanced Bioscience Laboratories, INC.
- Study coordinator: Silvera, Peter
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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.