ECE Researchers receive NSF Grant to Develop a Multi-modal Biosensing Platform

A team of ECE faculty members led by Assistant Professor Umer Hassan (PI) have received a new NSF award for the project titled " Multi-Modal Data-Driven Platform for Multiplexed Cellular Antigen Classification using Nano-electronic Barcoded Particles for Whole Blood Applications."

This project includes Associate Professor Mehdi Javanmard as a co-PI. The total award amount for this three-year project is $500,000. The project seeks to develop the next generation biosensing platform equipped with multi-modal sensing and novel nano-barcoded particles to perform reconfigurable biomarker selection in whole blood samples. Human blood cells play a critical role in immune system activation in response to infections. Concentration of these immune cells in whole blood and their membrane receptor densities may change in different diseases and their pathogenesis. The heterogeneity of the cellular classification needs to be quantified to provide a personalized diagnostics and patient monitoring system in hospital settings. The biosensing platform will be integrated with multi-modal sensing including electrical and optical which will allow to correct for inherent device-device variation to improve the sensor performance. Immune cells conjugated with functionalized nano-barcoded particles will be quantified in sync by impedance detector and smartphone attachment. Further, the proposed biosensor will be equipped with real-time data analysis using machine learning to enable a reconfigurable system for resource optimization and biomarker selection. The proposed sensor will enable multiplexed cellular antigen classification from a drop of whole blood with time to result (TOR) of less than 30 minutes. Sensors will be benchmarked with patient samples collected from the Robert Wood Johnson Medical Hospital. This cross disciplinary project will train undergraduate and graduate students in areas of sensors, systems and bionanotechnology.

More details on the project can be found at the NSF page here

Congratulations to Umer and Mehdi!