Developing a tool to analyze biological data for understanding health risks
Official title: Research and development of an adverse outcome pathway-focused mechanistic inference tool for 'omics data using semantic knowledge graphs
Funded at Sciome, LLC · NIH-10761637 · Data updated 2026-11-12
This study is working on a new tool that helps us understand how different stressors can impact your health by looking at how your body reacts at various levels, making it easier to see the risks linked to these stressors.
Quick facts
| Grant type | Sbir 1 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Sciome, LLC NIH-funded |
| Lab location | 1 site (Research Triangle Park, United States) |
| Project start | September 1, 2023 |
| Project end | August 31, 2025 |
| Funding year | 2023 |
| Award (this year) | $249,943 |
| NIH project number | 1R43ES035677-01 |
| Project ID | NIH-10761637 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals exposed to environmental stressors or those with conditions that may be influenced by biological factors.
✕Less likely to help
Patients who are not exposed to relevant stressors or do not have conditions related to the biological pathways being studied may not benefit from this research.
What this research studies
This research focuses on creating a tool that uses advanced data analysis techniques to understand how certain stressors can lead to health problems. By mapping biological information and events that occur at different levels of organization in the body, the tool aims to provide a clearer picture of how these stressors affect health. The approach involves integrating various biological databases and using deep learning to interpret complex data, making it easier to assess risks associated with different exposures.
Why it matters
Potential benefit: If successful, this research could enhance the ability to predict health risks from environmental and biological stressors, leading to better prevention strategies.
How similar studies have gone: While the concept of adverse outcome pathways is established, the specific integration of semantic knowledge graphs and deep learning in this context is a novel approach.
Where this research is happening
-
Sciome, LLC
Research Triangle Park, United States Active
Researchers
- Principal investigator: Shah, Ruchir — Sciome, LLC
- Study coordinator: Shah, Ruchir
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.