AI-powered blood biosensors for precise immune monitoring
Official title: Machine Learning-Assisted Integrated Optofluidic Nanoplasmonic Biosensing for Precision Immune Profiling and Monitoring
Funded at Auburn University at Auburn · NIH-11144419 · Data updated 2026-11-12
This project builds fast, AI-enhanced blood tests to read immune signals for people with autoimmune disease, cancer, infection, allergy, or transplant concerns.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Auburn University at Auburn NIH-funded |
| Lab location | 1 site (Auburn, UNITED STATES) |
| Project start | September 1, 2019 |
| Project end | August 31, 2029 |
| Funding year | 2025 |
| Award (this year) | $382,203 |
| NIH project number | 5R35GM133795-07 |
| Project ID | NIH-11144419 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates would be people with autoimmune diseases, cancer, recent infection, allergy issues, or transplant patients who are willing to provide blood samples for testing.
✕Less likely to help
People without immune-related conditions or whose care does not rely on cytokine monitoring are unlikely to benefit directly from this work.
What this research studies
From the patient perspective, researchers are creating tiny optofluidic nanoplasmonic sensors that can detect many immune signaling proteins (cytokines) from whole blood or serum. The sensors will be combined with machine learning to recognize patterns of immune activity and turn raw signals into clear results. Work includes improving the materials and capture probes for better sensitivity and testing the system on real blood samples to track immune changes. The goal is a point-of-care tool that helps clinicians monitor immune status more quickly and precisely.
Why it matters
Potential benefit: If successful, this could give patients faster, more detailed immune monitoring that helps guide treatment decisions and spot worsening inflammation earlier.
How similar studies have gone: Related biosensor platforms have shown promising lab and early clinical results, but combining high-performance nanoplasmonic sensors with machine learning for point-of-care cytokine profiling is still an emerging approach.
Where this research is happening
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Auburn University at Auburn
Auburn, United States Active
Researchers
- Principal investigator: Chen, Pengyu — Auburn University at Auburn
- Study coordinator: Chen, Pengyu
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.