Ryan Sharifi

Clinical Platform

TrialFinder.com

A patient-centered clinical trial discovery product built around fast search, structured eligibility flows, and scalable study data.

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TrialFinder.com product screenshot

What It Is

TrialFinder is a clinical trial finder platform that helps people discover relevant studies through a focused web experience instead of dense registry-style search.

Who It Is For

Built for patients, caregivers, and clinical research teams that need a clearer path from condition-based search to trial evaluation.

Problem

The Product Challenge

Clinical trial discovery is often fragmented, technical, and difficult to navigate. Users need to understand eligibility, location, and relevance quickly, while the product needs to handle structured medical data with reliability.

Role

My Contributions

  • Designed and implemented the core product experience across landing, search, filtering, and trial detail flows.
  • Built the full-stack foundation using Next.js for the interface and FastAPI-backed services for data access and application logic.
  • Modeled trial data in Supabase/PostgreSQL and shaped the UI around eligibility, condition, location, and study metadata.
  • Focused on responsive UX, clean information hierarchy, and a product feel suitable for a healthcare-adjacent platform.

Solution

What Was Built

Built a full-stack discovery experience with searchable trial data, filtering flows, matching-oriented UX, and product pages designed to make complex study information easier to scan and compare.

Architecture

Tech Architecture

Next.js powers the product UI, FastAPI handles backend application logic, and Supabase/PostgreSQL stores structured trial and user-facing product data. The system is organized around search, filtering, and detail-page retrieval so the interface can stay fast and clear as the dataset grows.

Next.js
FastAPI
Supabase
PostgreSQL
APIs

Highlights

Product Highlights

  • Condition and keyword-based trial search
  • Filtering flows for narrowing relevant studies
  • Structured trial detail pages with readable clinical information
  • Matching-oriented product flows for patient discovery
  • Responsive SaaS-style UI with healthcare-grade clarity

Outcome

Result And Learning

The project strengthened the product foundation for a scalable clinical discovery experience and clarified how complex medical data can be translated into a simpler patient-facing workflow.

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