Microfluidics-enabled directed affinity reagent engineering for fast, sensitive diagnostics

NIH RePORTER · NIH · R21 · $216,592 · view on reporter.nih.gov ↗

Abstract

PROJECT SUMMARY/ABSTRACT Near-patient detection and quantification of specific proteins in bodily fluids can enable medical professionals to offer timely and effective care that improves outcomes. In protein biomarker detection, a tradeoff exists between assay sensitivity and time to result. Affinity reagents are key components of microfluidic devices that enable protein analysis at the point of care. At present, affinity reagents are selected on the basis of equilibrium binding constants, which are most predictive of assay performance on hours-long timescales. The proposed project will develop transformative kinetic screening methods and devices that allow engineering of affinity reagents that can offer sensitive detection on the timescales of seconds to minutes, and use the reagents to enable frequent, convenient monitoring of cytokine panels to improve care for rheumatoid arthritis patients. This project leverages the collective cross-disciplinary expertise of faculty at MIT from the Departments of Chemical Engineering and Electrical Engineering and Computer Science. The team's synergistic expertise in protein engineering for diagnostics (Sikes) and design, fabrication and application of microfluidics and BioMEMS for point-of-care diagnostic tests (Voldman) will be collectively focused on developing new kinetic screening devices for engineering superior affinity reagents, and translating the new capability into an impactful on-site assay for inflammatory cytokines. Specific Aim 1 is to create novel microfluidic devices that can be used to select for fast-binding affinity reagents. Specific Aim 2 is to establish and validate new library screening processes uniquely enabled by the devices. Specific Aim 3 uses fast- binding affinity reagents to create a near-patient cytokine assay that maintains the required sensitivity without requiring a laboratory, which can enable more frequent testing and more individualized care for rheumatoid arthritis.

Key facts

NIH application ID
10527811
Project number
1R21EB032607-01A1
Recipient
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Principal Investigator
Hadley D Sikes
Activity code
R21
Funding institute
NIH
Fiscal year
2022
Award amount
$216,592
Award type
1
Project period
2022-08-15 → 2024-05-31