TrialSights

Navigate the future of clinical trials with real-time insights and smart biotech investing—powered by Sonar AI made by Perplexity. Clarity, exploration, and data-driven decisions in one platform.

Comment

TrialSights

Inspiration

In the biotech and vaccine research space, critical information is often scattered across research papers, clinical trial databases, and market analysis reports. Most sources are overwhelmingly text-heavy and difficult to navigate.

We wanted to create a unified platform where anyone—be it a researcher, investor, or a curious learner—could easily explore both the research and business sides of vaccines and treatments. That's where TrialSights comes in.

What it does

TrialSights is a web application that allows users to search for any disease, condition, or vaccine—such as "malaria" or "COVID-19 mRNA"—and instantly access both clinical research details and market insights in a single place.

Features include:

  • A smart, AI-powered search experience using the Sonar API by Perplexity
  • 13+ dynamic, auto-scaling graphs showing clinical trial phases, funding history, sponsoring organizations, and more
  • Clean summary sections and detailed breakdowns for both trial data and market outlook
  • A sleek and responsive UI for fast and intuitive exploration

How we built it

  • Frontend & Backend: Built entirely with Next.js, leveraging its powerful API routes and server-side capabilities
  • Data Source & AI Layer: Integrated with the Sonar API to handle natural language queries and return structured research + market data
  • Data Visualization: Used Recharts to create interactive, adaptable charts and visual summaries
  • Deployment: Deployed on Vercel for a seamless and scalable hosting experience

Challenges we ran into

  • Parsing and organizing Sonar API's response into a structured, user-friendly format
  • Designing a responsive layout that works well with varying amounts and types of data
  • Dynamically rendering different chart types based on what data is available for a given query

Accomplishments that we're proud of

  • Achieving tight integration between an LLM-powered backend and a dynamic frontend interface
  • Turning complex trial and funding data into simple, visual insights
  • Building an experience that feels useful, fast, and visually appealing—all within a short timeframe

What we learned

  • Working with LLM APIs in production environments and transforming their output into usable formats
  • Implementing chart components that can dynamically adapt to new data structures
  • Using Next.js not just for static frontends but also for managing backend logic and data handling

What's next for TrialSights

  • Adding advanced filters like location, trial phase, and sponsor organization
  • Enabling multi-query comparison for deeper analysis
  • Expanding language support to allow global users to access insights in their native languages
  • Incorporating AI-generated summaries of related research papers with source links

Built With

Share this project:

Updates