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  Swipe right on the trials you would like to partake in.

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  Keep track of your CliniCrushes.

CliniCrush: Find your perfect match.

💡 Inspiration

Finding the right clinical trial can feel like solving a puzzle. Traditional platforms overwhelm patients with complex interfaces and medical jargon. CliniCrush reimagines this process into something familiar and engaging, using a gamified swipe-based interface to match users with clinical trials.

🧠 What it does

CliniCrush is a web-based prototype that simplifies clinical trial discovery. Users input their medical conditions, location, age, and preferences to receive tailored trial recommendations. The interface allows users to:

• Swipe right on trials they’re interested in.
• Swipe left to dismiss trials.
• View details for comprehensive trial information, including eligibility and compensation.

Matched trials are saved locally for easy reference and follow-up.

🛠️ How we built it

CliniCrush was developed with a robust tech stack:

• Frontend: React 19 with TypeScript and React Bootstrap for responsive UI.
• Backend: Flask API interfacing with ClinicalTrials.gov and Google Maps API for real-time trial data and geocoding.
• Caching: Leveraged server-side and client-side caching to improve performance by minimizing redundant API calls and optimizing load times.
• Matching Algorithm: A custom ranking system assigns point values to trials based on:
  • Condition Relevance — 50 points
  • Gender Eligibility — 15 points
  • Age Eligibility — 15 points
  • Proximity to User — 20 points
  • Compensation Offered — 10 points

This ensures users see the most relevant trials first.

💪 Challenges we faced

• Real-time proximity calculation: Implementing accurate geolocation and distance metrics.
• User-friendly design: Balancing simplicity with the need to display detailed medical information.
• Performance optimization: Implementing effective caching strategies to reduce latency and enhance responsiveness.

🏆 Accomplishments

• Gamified the clinical trial discovery process with a swipe-based interface.
• Designed a sophisticated matching algorithm to prioritize user relevance.
• Integrated geolocation to highlight nearby trials.
• Enabled local storage of matched trials for easy follow-up access.
• Implemented caching to reduce API load and improve performance.

📚 What we learned

• The value of streamlined user experiences in healthcare applications.
• Techniques for presenting complex medical data in a simple, digestible format.
• Effective methods for geolocation and distance-based trial filtering.
• Importance of caching in optimizing web application performance.

🔮 What's next for CliniCrush

• In-app enrollment: Allow users to directly apply to clinical trials.
• Messaging portal: Enable direct communication with trial coordinators.
• Notifications: Add reminders for appointments and trial updates.
• Enhanced health profiles: Include scannable QR codes for sharing medical details with providers.
• Social sharing: Let users share trials with family, caregivers, and providers.

👥 Target users

• Patients exploring treatment options beyond standard care.
• Individuals with rare or difficult-to-treat conditions.
• Caregivers and healthcare providers assisting patients.
• Anyone interested in contributing to medical research.

CliniCrush revolutionizes clinical trial discovery by turning it into an engaging, user-friendly experience. By improving accessibility and personalization, we aim to connect more patients with life-changing medical opportunities while advancing healthcare research.

Built With

• flask
• google-geocoding
• node.js
• python
• react
• typescript