Clinical Trial Patient Matching

Challenge – Inefficient Patient Recruitment
The biopharma company struggled with slow patient recruitment for oncology trials, facing 30% screen-failure rates and delayed study timelines across 10 global sites. Manual eligibility reviews of unstructured medical notes made matching inaccurate and time-consuming, delaying both trial launches and regulatory milestones.

Solution – AI-Driven Patient Matching System
Partnering with NucleusTeq, the organization built a data-driven recruitment platform powered by Maestro (NuoData). The system leveraged NLP and real-world data from EHRs and clinical registries to automatically extract eligibility attributes and match patients to suitable trials. The solution was designed for scalability, supporting diverse disease areas and compliance with HIPAA and FDA 21 CFR Part 11 standards.

Impact – From Manual Screening to Intelligent Matching
• 25% reduction in time-to-enrollment
• 20% decrease in screen-failure rates
• 2-month acceleration in trial timelines

The platform enabled faster patient identification, reduced manual workload for coordinators, and improved collaboration between research teams — driving higher trial success rates and faster access to life-saving therapies.