This article is an ongoing series showcasing some of the best hacks we encountered through the Hack the North competition. To view more of these projects, please checkout the full list of hacks using the Dropbase API
With the COVID-19 vaccines now being rolled out across the world, the vaccines first needed to undergo clinical trials to ensure their efficacy and safety. In order to do so, governments are required to find willing volunteers to participate in studies to test the drugs. In many cases, these clinical trials fail not because the drug itself fails, but rather because the researchers are unable to gather a large enough group of volunteers to conduct their study on.
For Columbia Computer Science student Ivan Chau, UIUC Computer Engineering student Kyle Li, University of Pennsylvania Bio Engineering student Savan Patel and University of Pennsylvania Computer Science student Adarsh Rao, they wanted to find a better way to connect volunteers to the studies. Having participated in many hackathons as a team in the past, the team of four came into Hack The North already well acquainted with the strengths of each team member, and hoped to use the experience as a way to tackle a new industry, and learn new technologies along the way. Through the Hack the North weekend, they created ClinicConnect, a web application aimed at connecting volunteers to clinical trials.
When the team visited clinicaltrials.gov, which is the US site that allows volunteers to sign up for clinical trials, they realized that the process was cumbersome and oftentimes confusing to users. They also wanted a way that could better connect users with trials that were within close geographic proximity, something that the current government solution failed to do effectively. Essentially, they wanted to improve the usability of the site and make it a more effective solution for connecting patients with clinical trials they qualified for in their area.
For the team, they took raw CSV files from the clinicaltrials.gov website, and transformed them into a live Dropbase database. The team also created additional features by calculating the distances between the locations of trials and the location of the user, allowing the user to find the trials that are the closest to their current location. This feature was build using the Google Geocoding API, and the team also built live maps that users could visualize the locations of the trials.
The software they developed also allowed patients to filter results by certain parameters, such as age, gender, study phase, and disease states. Combined with the locational data, this allows patients to find the studies that best match their specific conditions and find the studies in which they qualify for. The software also allowed for autofilled email responses to the organizers of trials, to indicate to your interest in their study. To learn more about the project, check out the video the team put together:
For the team, the easiest way to ingest the data was to take the CSV files provided by the clinical trials website, and find a way to onboard that data into a live database. The ClinicConnect team realized that Dropbase would be able to quickly and efficiently perform this task for them, and would leave them with a Postgres database which they could call using the postgREST API to populate their frontend. Ivan and Savan, who worked closely with the Dropbase software, also appreciated the ability to use the pandas Python library to create custom data cleaning and processing functions in order to clean up the CSV data they ingested.
The next thing the ClinicConnect team hopes to accomplish is the inclusion of other forms of studies into the software, such as behavioural studies and other academic research/focus groups. They also hope that by creating partnerships directly with the host of the clinical trials' website, that they can further automate the population of data for ClinicConnect by allowing Dropbase to automatically pull new trials on a regular basis.