Clinical Search Index

Clinical Search Index

Motivation

The medications developed in clinical trials today are the therapies that have the potential to drive new treatments and potential cures over the next 5 to 10 years - from addressing the spectrum of huge diseases such as diabetes and autism, to rare diseases with no treatments such as ALS. The success of clinical trials are important to not only big stakeholders like pharmaceutical companies, researchers, physicians, but also ordinary people like taxpayers and special interests. Approximately $10 billion is spent funding clinical trials every year, yet there lacks a functional query tool that makes the results and successes of these expenditures transparent. Even with very specific tools such as clinicaltrials.gov, finding the right clinical trial can be extremely frustrating. Failures in clinical trials are hardly ever reported, with approximately 10% of studies ever published. Of these 10%, most are difficult to find and locate on the clinicaltrials.gov website.

What It Does

CSI is a functional query tool that displays the best clinical trials (both ongoing and complete) in the nation around any disease. Given search parameter such as age, gender, and health status, CSI searches for:

  • clinical trials that our user would be eligible for by state. Finding the right clinical trial can be time-consuming, so we used parameters tin the study design of each research study to narrow down the best clinical trials going on in every single state

  • clinical trials ordered by rank and reputation of the sponsor. Since a large number of clinical trials are completed without any results, we penalized sponsors who did not publish the results of their clinical trials.

How We Built It

We used Django as our back-end framework, with Javascript as out front-end. In Python, we scraped every single webpage in http://clinicaltrials.gov into a SQL server database, which communicates with our Django back-end.

Challenges We Ran Into

Django has a high learning curve, and some problems we ran into include: * implementing the search functionality on the clinical trials database * getting the UI to communicate with the back-end * scraping the page sources of clinicaltrial.gov for more information that the Clinical Trials API does not give out

Accomplishments That We're Proud Of

This is our first Django project. As a team, we have an eclectic background in stacks such as Android, Flask, Meteor, and Raspberry Pi, but at this hackathon, we wanted to develop with something we haven’t seen before. In addition to using the Clinical Trial API, we’re proud of writing our own python tool that scrapes the the page sources of clinicaltrial.gov. None of us have had experiences developing UI before, so we’re proud of getting more experience with javascript, HTML, and CSS.

What's Next For The Galvanic Stress Response

We hope to scale CSI further by giving our website more functionality, in which users could query for pharmaceuticals, and learn more about a disease just from the CSI website.

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