One of our team members volunteered in the clinical research department of a hospital. During that stint, he found that the a lot of the organizational systems doctors used weren't very efficient and standardized. We decided we wanted to address a specific part of the problem by creating a tool that makes providing revolutionary healthcare easier for both doctors and patients.
What it does
TrialTracer is currently a web-based app that takes in several inputs from the user such as their gender and condition and provides them with a comprehensive list of applicable clinical trials. In addition, we also provide the user with a built in map that pins the locations of all the applicable clinical trials.
How we built it
First we acquired a csv file containing a sample data set of clinical trials. We used the Pandas API from Python to read in the data and filter the clinical trials. Then we used a Google Maps API to generate our google map. The Google Maps API takes in a csv file the python program outputs and enters in location data attached to other relevant data you can acquire by clicking on the pins. Finally, we put together all the back end programming with Flask, a Python based web builder.
Challenges we ran into
We ran into several roadblocks along the way. In reading the file, we struggled to find a clean way to read in the data and return everything we needed. Initially, we coded our filter program in MATLAB, but we realized that integrating MATLAB into a web-based app would be a lot more work than finding a different language. So, under recommendation from a friend, we switched our language and implemented the Pandas API. Our next problem was putting together the Google Maps program. One of our team members wrestled with a lot of technical difficulties that prevented certain parts of his code from functioning.
Accomplishments that we're proud of
As a novice team with relatively little experience in Computer Science, I think we're pretty proud of everything we've done. Because it was all our first hackathon, we're glad we were able to produce a working prototype of our product.
What we learned
This project has been a huge learning experience for us all. We dealt with a lot of coding that we had never done before. A lot of our time was spent learning how to use new APIs such as Pandas and Google Maps, code in unfamiliar languages, and discovering new and powerful tools.
What's next for TrialTracer
TrialTracer is currently only a small sample of the potential for the tool. There so many ways we can make our search tool more robust and available to the user, whether that is the patient or the doctor. The front-end of our product would also need a lot of work if we were to continue down the web-based app approach. However, in order to monetize our product, we think it would be nice to integrate our tool into currently existing software that doctors use. So we would be selling our tool to either tech companies that cater to the healthcare system or straight to hospitals that want to make their clinical trials more widely available.