Creating a knowledge graph to improve drug discovery for infectious diseases
SBIR 136 - PREDICTIVE: Knowledge Graphs for Infectious Diseases
This study is working on a smart system that gathers and organizes information about infectious diseases and their treatments to help find new ways to fight these illnesses, making it easier for doctors and researchers to discover better medicines for everyone.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Predictive, LLC NIH-funded |
| Lab location | 1 site (Raleigh, United States) |
| Project ID | NIH-11214917 on NIH RePORTER |
What this research studies
This research focuses on developing a structured knowledge base that integrates various data sources related to infectious diseases and their treatments. By utilizing advanced knowledge mining technologies, the project aims to create an Infectious Disease Knowledge Graph (IDKG) that organizes biomedical, chemogenomic, and clinical data. This knowledge graph will help identify biological pathways and potential drug targets, ultimately supporting the discovery of new treatments for infectious diseases caused by both known and emerging pathogens.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals affected by infectious diseases, particularly those caused by emerging pathogens.
Not a fit: Patients with non-infectious diseases or those not affected by emerging pathogens may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to the development of novel treatments for infectious diseases, improving patient outcomes.
How similar studies have performed: Other research has shown success in using knowledge graphs for drug discovery, indicating that this approach has potential for impactful outcomes.
Where this research is happening
Raleigh, United States
- Predictive, LLC — Raleigh, United States (Active)
Researchers
- Principal investigator: Tropsha, Alex — Predictive, LLC
- Study coordinator: Tropsha, Alex
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 below.