The broader impact/commercial potential of this PFI project is to develop a low-cost cortisol sensing technology for early detection of stress-related diseases. Cortisol is a biomarker used for stress evaluation in human subjects. Increased cortisol levels have been linked to stress-related diseases, including chronic fatigue syndrome, post-traumatic stress disorder, and neurodegenerative diseases including Alzheimer's disease, and multiple sclerosis. Therefore accurate measurement of cortisol in saliva, and sweat, is gaining increasing clinical significance to predict multiple physical and mental diseases. While existing laboratory techniques, such as ELISA and FIA, can provide precise cortisol measurements, they are generally too slow, where a rapid response or intervention is needed. The proposed technology overcomes significant limitations such as the necessity of having specified sample volume to perform a test, total testing time, and expensive optical detection unit. The substantial advantage of the proposed technology is to produce cortisol results within few minutes and can replace tedious laboratory-based techniques. This technology will create personalized behavioral intervention to regulate cortisol levels and prevent stress-related health problems for at-risk clinical populations. The proposed cortisol sensing technology will provide solutions to hospitals, diagnostic laboratories, and pharmaceutical industries, which increasingly rely on fast, sensitive, reproducible and fully automated technologies.
The proposed project aims to translate a sensor technology, developed under a previously funded NSF grant, into a low-cost, handheld sensing device to monitor the salivary cortisol levels in point-of-care (POC) monitoring. The FIU team has engineered recognition site of cortisol sensor using antibody- mimic, robust and easily industrially scalable electroactive imprinted polymers that allow to miniaturize device in easily deployable and portable format. In order to translate the sensor into the market, the project will be consolidated into two goals: (i) sensor stability and measurement repeatability, and (ii) reducing cost and size. To accomplish these goals FIU team will 1) develop of high-affinity and reagent-less MIP sensor for Cortisol using novel electroactive monomers and 2) Constructing a low-cost handheld/portable prototype for field use. The proposed cortisol sensor will be capable of sending real-time data from the sensor to the virtual server via a smartphone app. The real-time data will be populated and processed on the virtual machines and will be archived by the user on their personal computer or smartphone app. The project will fortify a cross-university collaboration between the areas of health science and engineering; resulting in interdisciplinary biomedical research training for students, postdoctoral researchers, and faculty.
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.
