An AI tool for extracting and visualizing knowledge about metabolites and infectious diseases
Official title: SBIR 136 - KITWARE: Viime Extract: An AI-powered Knowledge Graph Extraction System for Metabolomics
Funded at Kitware, INC. · NIH-11214910 · Data updated 2026-11-12
This study is creating a user-friendly web app called Viime Extract that uses smart technology to help people understand research about how our body's chemicals relate to infections, making it easier to explore and check important information.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Kitware, INC. NIH-funded |
| Lab location | 1 site (Clifton Park, United States) |
| Project start | September 6, 2024 |
| Project end | September 5, 2025 |
| Funding year | 2024 |
| Award (this year) | $299,999 |
| NIH project number | 75N93024C00035-0-9999-1 |
| Project ID | NIH-11214910 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals involved in metabolomics or infectious disease research, including scientists and healthcare professionals seeking to enhance their data analysis capabilities.
✕Less likely to help
Patients who are not engaged in research or do not have a background in metabolomics or infectious diseases may not benefit from this research.
What this research studies
This research develops Viime Extract, a web application that uses artificial intelligence to analyze research papers and data related to metabolomics and infectious diseases. By employing large language models, the system generates knowledge graphs that help visualize complex relationships in the data. Users can interact with the data through an intuitive interface, allowing for validation and correction of the extracted information. The application aims to streamline the process of data curation and enhance understanding of metabolomics in the context of infectious diseases.
Why it matters
Potential benefit: If successful, this research could significantly improve the way researchers and healthcare professionals access and understand complex data related to metabolites and infectious diseases.
How similar studies have gone: Other research has shown success in using AI and knowledge graphs for data analysis, indicating that this approach has potential for meaningful advancements in the field.
Where this research is happening
-
Kitware, INC.
Clifton Park, United States Active
Researchers
- Principal investigator: Baumes, Jeff — Kitware, INC.
- Study coordinator: Baumes, Jeff
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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.