srvc-EHSR: Smart, reusable ML-powered reviews for environmental and health data
Official title: srvc-EHSR: Sysrev Version Control - Environmental and Health Related Systematic Reviews
Funded at Insilica, LLC · NIH-11327354 · Data updated 2026-11-12
A software platform helps researchers quickly create and run customized reviews of environmental and health data using machine learning, saving time and money for researchers and regulators.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Insilica, LLC NIH-funded |
| Lab location | 1 site (Bethesda, UNITED STATES) |
| Project start | January 1, 2024 |
| Project end | April 30, 2027 |
| Funding year | 2026 |
| Award (this year) | $1,005,398 |
| NIH project number | 5R44ES035359-03 |
| Project ID | NIH-11327354 on NIH RePORTER |
Who could benefit from this research
✓Could help
Not applicable (this is a software platform for researchers; no direct patient enrollment required).
✕Less likely to help
No direct patient participation or benefit; the work is tool development for research and regulatory use.
What this research studies
This grant supports building a cloud-based or on-site software tool that lets researchers define what to include in environmental and health risk reviews through easy natural-language commands. The system uses modular components for data extraction and summary statistics so new ML features can be added without rebuilding the whole codebase. It aims to reduce the cost and time spent on document reviews that inform chemical and product safety decisions, enabling faster access to important findings. The platform will be usable by academia, industry, and government regulators to streamline EHRRA workflows.
Why it matters
Potential benefit: If successful, patients benefit indirectly through faster and more accurate safety assessments of chemicals and products.
How similar studies have gone: Similar ML-assisted document review tools exist but this project emphasizes customizable, interoperable DR and ML components for EHRRAs.
Where this research is happening
-
Insilica, LLC
Bethesda, United States Active
Researchers
- Principal investigator: Luechtefeld, Thomas — Insilica, LLC
- Study coordinator: Luechtefeld, Thomas
Related research
Other NIH-funded projects on the same topics.
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A platform to improve environmental and health-related risk assessments using machine learning.
This study is creating an easy-to-use online tool that helps researchers quickly and accurately check the safety of environmental chemicals, making their work faster and less expensive.
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An AI platform to organize and integrate environmental health data
This study is creating a user-friendly online tool that uses smart technology to help researchers easily find and organize important information about environmental health and safety, making it quicker and cheaper to test products like cosmetics and everyday items for safety.
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.