Smart blood test for tick-borne infections
SCH: Machine LEarning & MicrofluiDics for Multimodal Sensing of TiCk-bOrne Diseases(MEDICO)
This project develops an easy-to-use blood test using microfluidics and machine learning to find Lyme disease, babesiosis, and anaplasmosis early.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | West Virginia University NIH-funded |
| Lab location | 1 site (Morgantown, United States) |
| Project ID | NIH-11166627 on NIH RePORTER |
What this research studies
You would give a small blood sample that is run through a tiny-chip device that uses microfluidic sorting and dielectrophoresis to separate and sense infected blood cells. The device uses very sensitive 3D sensors and a custom readout circuit to capture detailed electrical signals from cells. A machine-learning program then looks for patterns in those signals to identify Lyme disease, babesiosis, anaplasmosis, and possible coinfections. The system is being designed for minimal user steps so it could be used in clinics or near-patient settings.
Who could benefit from this research
Good fit: Ideal candidates are people with recent tick exposure or symptoms suggestive of Lyme disease, babesiosis, or anaplasmosis who can provide a blood sample.
Not a fit: People whose infections are not present in the bloodstream, who cannot give a blood sample, or whose condition requires different diagnostic methods may not benefit from this test.
Why it matters
Potential benefit: If successful, this could enable faster and more accurate detection of tick-borne infections so treatment can start sooner.
How similar studies have performed: Related microfluidic and AI-based diagnostics have shown promise for infection detection, but combining DEP, 3D sensors, and ML specifically for tick-borne diseases is novel and largely untested in patients.
Where this research is happening
Morgantown, United States
- West Virginia University — Morgantown, United States (Active)
Researchers
- Principal investigator: Srivastava, Soumya K — West Virginia University
- Study coordinator: Srivastava, Soumya K
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.