ClearPath Trial

• 

  workflow

Optimizing Site Selection and Jumpstarting Study Design

A major challenge in clinical trials is finding the right research sites, which, if poorly done, can lead to costly recruitment delays. Sponsors (biotech/medtech companies) need to select sites in areas with a high concentration of eligible patients, but getting access to the real-world data to identify these locations and high-performing research sites can be prohibitively expensive ($75K to $5M/yr [1]). In addition, significant manpower is spent on designing the study.

[1] https://www.cbinsights.com/research/pharma-real-world-data-vendors-cost/

What it does

Our solution simulates this crucial data using publicly available Medicare information, allowing us to provide an affordable, data-driven analysis for selecting the most optimal clinical trial sites. It then produces a preliminary protocol which include crucial information such as inclusion and exclusion criteria.

How we built it

We divided the workflows among the team members and later combined them in one person's account.

Challenges we ran into

Due to time constraints, we were unable to download the required patient (SEER/Medicare). So we have used an LLM to generate mock data as a temporary measure. Obtaining the actual data in a production environment will be straightforward and cost-effective, at which point it will replace the simulated data.

Accomplishments that we're proud of

In just half a day, we built the framework that can reduce the cost of clinical trials significantly.

What's next for ClearPath Trial

The next step is to replace the current placeholder data with real patient data and optimize the protocol output. This will allow the system's workflow to be utilized in a real-world setting.

Built With

• javascript
• n8n
• python