The National Institute of Biomedical Imaging and Bioengineering awarded a $249,000 Project Grant (CFDA 93.286 - Discovery and Applied Research for Technological Innovations to Improve Human Health) to Northwestern University to develop machine learning-enabled microfluidic devices for the classification of extracellular vesicles (EVs) associated with ovarian cancer. The project aims to combine advanced nanofabrication, surface-enhanced Raman spectroscopy (SERS), and machine learning algorithms to improve the signal strength and spectral quality of EV SERS analysis. This will enable the development of two distinct microfluidic devices - one to capture EV subpopulations based on surface antigens, and another to separate EVs by size and analyze them using SERS-based barcoding. The project is expected to run from September 2024 to August 2027, contributing to advancing biomedical imaging and engineering technologies for early ovarian cancer detection and monitoring.
Generated 2/25/25, 4:25 AM