Creating a new sensing platform for detecting infectious diseases.

Designing a deployable and adaptable plasmonic sensing platform for infectious disease surveillance

NIH-funded research University of Cincinnati · NIH-11143641

This study is working on a new, easy-to-use testing system that can quickly and accurately detect infectious diseases like COVID-19 and its variants, helping to improve how we monitor and manage these illnesses.

Quick facts

Grant typeR01 grant
Study typeNIH-funded research
Funding institutionUniversity of Cincinnati NIH-funded
Lab location1 site (Cincinnati, United States)
Project IDNIH-11143641 on NIH RePORTER

What this research studies

This research focuses on developing a new, adaptable sensing platform that can accurately and cost-effectively test for infectious diseases, particularly the novel coronavirus and its variants. The project aims to improve upon existing diagnostic methods, such as PCR and lateral flow assays, which often struggle with either deployment ease or accuracy. By utilizing advanced techniques like catalytic surface-enhanced Raman scattering (SERS) and machine learning, the researchers hope to create a system that can detect multiple genetic biomarkers in liquid samples. This innovative approach aims to provide rapid and reliable results for better disease surveillance and management.

Who could benefit from this research

Good fit: Ideal candidates for this research include individuals who may be at risk for infectious diseases, particularly those related to the novel coronavirus.

Not a fit: Patients who are not at risk for infectious diseases or those who have already been diagnosed and treated may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more accurate and accessible testing for infectious diseases, improving public health responses.

How similar studies have performed: Other research has shown promise in developing advanced diagnostic platforms, but this specific approach using SERS and machine learning is relatively novel.

Where this research is happening

Cincinnati, United States

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.
Last reviewed 2026-06-09 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.