In my first semester as a graduate student, I got the opportunity of working with Prof. Ian Brooks on the Pathtracker project. Pathtracker is a project funded by the NSF and combines multiple branches of engineering involving Computer, biochemical and Electrical Engineering. I am currently working on this research project and it continues to be a great learning experience for me.
I have the responsibility of designing the front end of the application. Also, I have to design the information flow, forms for the doctors/veterinarians involved and developing prototypes for the application as well as the website.
The challenging thing with this research project for me is to develop an interface which is simple enough to be used in daily life at the same time does not leave any scope for error as it could result in life or death of a patient. Also, coming into this project I did not know much about biochemistry and healthcare, I had to adapt to the environment fairly quickly and make sure that my interface could communicate well with the users.
This Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) project will develop a mobile sensor technology for performing detection and identification of viral and bacterial pathogens. By means of a smartphone-based detection instrument, the results are shared with a cloud-based data management service that will enable physicians to rapidly visualize the geographical and temporal spread of infectious disease. When deployed by a community of medical users (such as veterinarians or point-of-care clinicians), the PathTracker system will enable rapid determination and reporting of instances of infectious disease that can inform treatment and quarantine responses that are currently not possible with tests performed at central laboratory facilities.
Polymerase Chain Reaction (PCR) and Loop-Mediated Isothermal Amplification (LAMP) currently represent the most sensitive and specific approaches for identification of viral or bacterial pathogens, with intense research focus directed towards miniaturization, acceleration, and automation of the protocol for amplifying disease-specific DNA sequences to easily-measured concentration. The plan is to apply the results of previously NSF-funded advances in photonic crystal enhanced fluorescence (PCEF) and smartphone fluorescence spectroscopy to implement PCR or LAMP assays within sub-µl liquid volumes for reduction in the assay amplification time to register a measurable fluorescent signal. Importantly, the detection approach enables >10x multiplexing of PCR (or LAMP) reactions within a chip that can be "swiped" through a custom handheld detection instrument that interfaces with the back-facing camera of a conventional smartphone in a manner that is similar to reading a credit card. A mobile device software application will guide the user through the assay process, interpret the results of the detection (including correlation of assay measurements with on-chip experimental controls), and communicate results to a cloud-based data management system along with other relevant information provided by the user. Importantly, the app will enable the user to view the results of tests performed by other users, with a mobile device interface that enables simple visualization of the locations, times, and circumstances surrounding positive/negative tests. The system will enable users to request customizable alerts when positive tests occur within the network of users, and to highlight confirmed positive cases when conventional laboratory tests can confirm results of positive field tests. The app will track outcomes and report statistics on system performance, including Receiver Operating Characteristic of assays.
While the system will initially be deployed in the context of equine infectious disease representing an opportunity to mitigate enormous economic losses associated with infectious disease in the horse industry, the developed technology will be equally applicable to humans, food animals, and companion animals. Considering the economic and health impact of ebola, HIV, tuberculosis, and malaria, when PathTracker is fully deployed within developing nations, the potential of the system to save lives by rapid delivery effective treatment, quarantine of infectious patients, and rapid identification/reporting of new cases is enormous.