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  • project

Horizon Trial

  • UX Research
  • UI Design
  • Development
  • Website
  • Web Application

Client

  • Horizon Trial

Industry

  • HealthTech

Services

  • UX Research
  • UX Research
  • UI Design
  • Development
  • Website
  • Web Application

Years

  • 2025
  • About project
  • Details

01

Project Details
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Horizon Trial is a Canadian health-tech startup revolutionizing the clinical trial industry through artificial intelligence and machine learning. The platform connects patients, physicians, and contract research organizations (CROs) by automating the process of matching eligible participants with suitable clinical trials and novel treatments. Designed to accelerate research and improve patient access to life-saving therapies, Horizon Trial bridges a critical gap between medical innovation and those who need it most.

  • Difficulties
  • Difficulties

02

Project Problems
Globally, 85% of clinical trials struggle with patient recruitment. Researchers rely on outdated methods like government listings and manual outreach, which lead to long delays, high costs, and low participation rates. Meanwhile, patients seeking new therapies often lack visibility into relevant trials — especially those not publicly listed. This disconnect between patients, physicians, and research organizations prevents life-saving treatments from reaching the market faster.
  • Obstacles
  • Barriers

03

Project Challenges
The primary challenge was creating a digital ecosystem that could intelligently analyze eligibility data, match patients, and deliver real-time insights to CROs while maintaining full compliance with Canadian privacy standards. The system needed to process complex medical data without overwhelming users — from physicians to patients with minimal technical experience. Achieving that balance between technical sophistication and human simplicity became central to Horizon’s design.
  • Approaches
  • Innovations

04

Project Solutions
We developed Horizon Trial as an AI-driven matching platform that enables patients and healthcare providers to connect seamlessly with ongoing clinical research opportunities. The machine learning engine scans public and private databases to identify suitable trials based on medical history, location, and eligibility criteria. Physicians receive instant updates on new treatments for their patients, while CROs gain access to a refined, pre-qualified participant pool. The platform’s dual revenue model — monthly subscriptions for physicians and match-based fees for CROs — ensures long-term scalability. Ultimately, Horizon Trial transforms clinical trial recruitment into a faster, more transparent, and patient-focused process.
  • process
  • our flows

05

Design Process
A structured approach to solving problems, combining research, ideation, prototyping, and testing to create user-centered solutions.
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01. Discover

We conducted deep market research across the Canadian and U.S. clinical trial sectors, interviewing physicians and CRO executives to map pain points in participant recruitment. Insights revealed a gap in intelligent, patient-centric digital tools — shaping our strategy for Horizon’s AI-powered, compliance-ready system.

02. Design

Our design philosophy emphasized clarity, trust, and accessibility. We created wireframes that mirrored the workflows of physicians and CROs, paired with a calm, healthcare-appropriate visual palette. Every element — from the onboarding flow to analytics dashboards — was designed for speed, simplicity, and trust.

03. Develop

The development stage integrated machine learning algorithms capable of scanning and ranking trials based on patient data, condition profiles, and trial success probabilities. Scalable cloud architecture and secure API layers ensured compliance with Canadian data protection laws (PIPEDA). Continuous testing refined matching accuracy and response time.

04. Deliver

The final MVP launched with early-stage CRO partners in Ontario. Horizon Trial now enables faster recruitment cycles, reduced trial costs, and improved access for patients seeking new treatments. The project set a new benchmark in AI-enabled healthcare innovation — bridging the distance between research and real-world impact.