A Microfluidic-CMOS Cross-cut Approach Enabling Tri-Modal Biorecognition for Highly Accurate Viral Diagnostics

nsf_101x102.jpg

Assistant Professor Mehdi Javanmard is the recipient of a new NSF award for the project titled "A Microfluidic-CMOS Cross-cut Approach Enabling Tri-Modal Biorecognition for Highly Accurate Viral Diagnostics." This is a three year $450,000 collaborative effort between Rutgers University (Mehdi Javanmard, PI) and Princeton University (Kaushik Sengupta, PI). Rutgers' share for this award is $225,000.

As part of this project, Mehdi and his team will develop a finger-stick sized instrument whose purpose is to rapidly diagnose viral infections in blood. The proposed point-of-use device can be utilized for rapidly screening subjects at airports, emergency rooms, or other crowded areas where the potential to spread viral disease is high. The proposed innovation is based on miniaturization of sample, reagent, and buffer handling in microfluidics using low power electronically actuated micro-valves, reconfigurable electroosmotic pumps, and multiplexed detection of fluorescence-labeled proteins and nucleic acids in silicon ICS with integrated nanoplasmonic filters that remove the necessity of complex optical scanners, lenses, collimators. The platform is envisioned to be generic and reconfigurable and the pre-functionalized cartridges can be swapped out for different infectious diseases. Specifically, the proposed research aims to investigate and develop multi-modal detection capability through electronically actuated fluidic valves and pumps enabling on-chip immunoassays for protein detection and on-chip nucleic acid purification, amplification, and hybridization for viral load determination as well as light guiding, packaging and additive manufacturing techniques for enabling a sample-to-answer platform.

Congratulations on this success, Mehdi!