The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to create a functional prototype system for presumptive detection of illicit opioids and stimulants. This new technology could prevent some of the 45,000 fatal opioid overdoses per year in the US and reduce the chances of false drug arrests, which disproportionately affect certain minority populations. The technology uses a mobile phone app coupled with a paper test card and machine vision algorithms. The paper card runs twelve chemical tests on the sample at once, producing a color bar code that reveals the chemical composition of the sample. The mobile app will use machine vision software to read the results of the test. The system will be less likely to erroneously identify a harmless substance as an illicit drug than current commercially available presumptive drug tests and may be able to measure drug concentrations and identify multiple drugs present in mixtures. The latter are capabilities that the current presumptive tests do poorly, if at all.

The proposed project will develop a prototype illicit drug identification system for further commercial development. The paper card will be accessorized with a dose metering device and solvent reservoir to facilitate field use. The number of color tests on the millifluidic card will be increased by 50%, targeting opioids and stimulant drugs. Human ability to sense colors is subjective and may be affected by differences in color vision, so the analytical metrics of reading test card results “by eye” will be compared with the results of using principal component analysis, a neural network classification approach, or a generative adversarial network (GAN) approach. Harmless stimulant drugs will be used in field tests to evaluate different prototype card designs, and to demonstrate the potential of the mobile app + card system for geotemporal detection of a “product” responsible for an overdose outbreak. The team will use a business model canvas framework and regular group meetings to ensure that all participants receive training in entrepreneurship and that the research and development activities result in a commercializable system for detecting illicit drugs in field settings.

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.

Project Start
Project End
Budget Start
2020-10-01
Budget End
2022-03-31
Support Year
Fiscal Year
2020
Total Cost
$250,000
Indirect Cost
Name
University of Notre Dame
Department
Type
DUNS #
City
Notre Dame
State
IN
Country
United States
Zip Code
46556