The broader impact/commercial potential of this Partnerships for Innovation (PFI)– RAPID Project is to develop a diagnostic platform that is well-suited for widespread monitoring of infection during pandemics, such as the current COVID-19 threat. It consists of a low-cost mailer that can be used at home, returned in the mail in a safely-sealed, confidential envelope and quickly scanned upon receipt without opening to diagnose infection. These results can be relayed to the user immediately and a real-time outbreak map along with affected demographics can be produced. This approach off-loads the burden of diagnostics from health workers, eliminates the increased use of limited personal protective equipment, and provides a better response to outbreaks. Resources could be more efficiently allocated by local and federal governments, and workers could make more informed decisions on staying at home or going to work. Moreover, this project will train a team of four students to collaborate quickly together to meet the design constraints of an actual product based on technologies from their thesis work. Commercial impact beyond COVID-19 would be a highly modular platform that can be rapidly adapted to other current diagnostic needs (HIV, tropical diseases) as well as future pandemics.
The proposed project overcomes the current methods of COVID-19 detection which are limited by 1) healthcare workers having to collect samples, 2) shipment of biological specimens, and 3) bottleneck of assessment with current RT-PCR techniques. What is needed is a more rapid method of widespread genetic testing for epidemic control that overcomes these limitations. Here we propose a new sensor system that relies on embedded contact-free sensors and sensitive RNA detection and amplification in a low-cost, passive (no onboard power) solution that allows for the user to collect sample and safely carry or mail to a local scanner. In this work we will design genetic switches sensitive to COVID-19 RNA (aim 1), implement these switches on paper substrates with cell free protein production (aim 2), and integrate them with a resonant sensor RF transducer (aim 3). The project deliverable will be a working prototype that is tested in our collaborative labs, along with a first generation data visualization interface.
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.
