Karneyium | AI Clinical Trial Site Selection SaaS

Problem

Choosing where to run a clinical trial is a slow, manual process that can add months and millions of dollars to a drug's path to market. Research teams struggle to make data-driven decisions about optimal trial locations without unified access to patient demographics, healthcare infrastructure, and historical recruitment data.

🛑 The Business Challenge

Selecting a clinical trial site involves balancing patient demographics, proximity to medical facilities, and historical recruitment success. Traditionally, this is a manual and fragmented process prone to high costs and significant delays. The goal was to build a unified cloud based ecosystem capable of processing massive datasets and visualizing them on an interactive map for better decision making.

Solution: Intelligent Mapping & AI Analysis

We developed a multi-tenant SaaS architecture that integrates real-world health data with advanced AI to automate site feasibility studies.

• Geospatial Intelligence: Using ArcGIS Integration, we implemented precise mapping layers that allow researchers to visualize patient density and healthcare infrastructure geographically.
• Generative AI Insights: OpenAI API integration enables natural language querying of clinical data, allowing users to ask complex questions like, "Where are the optimal hubs for Stage 2 oncology trials in the Midwest?"
• Data Analytics Visualization: Integrated Chart.js to provide real-time analytics dashboards tracking recruitment metrics and site performance.