Skip to main navigation Skip to search Skip to main content

PFI-RP: The rapid and specific detection of infectious pathogens using ultrathin porous membranes as sensors

Project: Research

Abstract & Details

Description

Award ID: 2234394

The broader impact/commercial potential of this Partnerships for Innovation - Research Partnerships(PFI-RP) project derives from the advancement of a technology for the rapid detection of infection from a small quantity of body fluid such as saliva, urine, or blood. Requiring no electronics or external reader, the proposed membrane-based sensor technology is expected to achieve the same low costs as current lateral flow assays, but with greater sensitivity. Importantly, as the first assay to require specific pathogen size and affinity for positive indications, this approach may detect active infections which is not currently done by any assay. The low-cost assessment of active infection would be impactful for quarantine management, particularly in low-resource settings where the societal burden of lost work or school is especially high. Related applications may include rapid tests that distinguish between viral and bacterial sources of illness, which could be particularly useful for the rapid assessments of the cause of sore thoughts in children. A major emphasis in this PFI-RP is to broaden participation by including faculty and undergraduates at PUI institutions as full participants in the research and development efforts. Entrepreneurship and industry will be well-represented in both classroom training and in bi-weekly meetings of the PFI-RP team. This PFI-RP project will advance a novel membrane-based sensor for the detection of infectious agents in biofluids based on both their size and surface antigens. Current rapid assays only detect the presence of molecular components of pathogens and cannot distinguish between their infectious and non-infectious states. The project plan focuses on two developments needed for commercial viability beyond the teams existing proof-of-principle studies: 1) The integration of the membrane-based sensor into a hand-operated microfluidic device with an obvious colorimetric readout, and 2) The demonstration that membrane ensing can be generalized for detection of different pathogens/variants by optimizing pore size and antigen recognition. To accomplish these objectives, the PFI team put together a multi-institutional team including academia and industry. This team will fabricate versatile microfluidic devices using PET laminates (PETL) and other low-tech materials to create a device simple enough to be operated in the home. In parallel studies, the design principles needed to detect both large and small pathogens with high sensitivity and specificity will be established. Success in both tasks are expected to result in prototypes and workflows enabling the rapid detection of a range of infectious agents in a simple-to-use test format. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Program Director: Mara E. Schindelholz
StatusActive
Effective start/end date09/15/2308/31/26

Lead and Sub-Awardee Organization(s)

Funding

  • Other Programs (Technology): $549,649.00

Active Fiscal Year

  • FY2024
  • FY2023
  • FY2026
  • FY2025

Start Fiscal Year

  • FY2023

TIP Programs

  • Other Programs (Technology)

Key Technology Areas

  • Biotechnology
  • (confidence score: 100%)

Technology Foci

  • Synthetic Biology
  • (confidence score: 100%)

Congressional District at Award

  • District n. 25 of New York

Current Congressional District

  • District n. 25 of New York

United States

  • New York

Core Based Statistical Area (CBSA)

  • Rochester, NY

County

  • County: Monroe, NY

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine