Study Feasibility
With 43% of study sites failing to enroll a single patient, a more data-driven approach to study planning is needed.
Medidata Study Feasibility leverages the power of AI and real-time site- and country-level performance metrics to predict high-enrolling and non-enrolling sites, suggest the leanest viable study footprint, and forecast enrollment in a single unified platform.
Confidently Plan Better Trials with Predictive AI
You’re expected to deliver faster enrollment, more diverse representation, and predictable timelines—without increasing complexity or cost. But too often, feasibility decisions rely on incomplete data, manual iterations, and static forecasts.
Powered by the industry’s largest operational dataset, Medidata Study Feasibility gives you insights you can act on.
Leverage predictive AI to simulate your trial before it begins:
Optimize study footprint in minutes
Identify high-performing and non-enrolling sites
Discover previously unknown sites
Benchmark internal performance metrics against industry trends
Why Medidata Study Feasibility?
Site Strategy
Data-Driven Site Selection
Rather than relying on assumptions or historical participation alone, teams can make earlier, more informed decisions with Medidata’s real-time site- and country-level performance metrics.
Identify high-performing sites, understand competition for patients from nearby trials, optimize site and country mix, and simulate the most efficient path to enrollment.
Featured Resource
2026 State of AI in Clinical Trials Report
Over half of organizations are in active pilots or fully implementing AI for study feasibility and site selection.
Download now for adoption trends and more insights.
FAQ
How does Medidata Study Feasibility improve site selection accuracy?
The solution uses AI-powered forecasting derived from actual site-level enrollment and congestion data—not just surveys—to identify high-performing sites. It provides unmatched granularity on operational performance metrics, including enrollments, screen failures, and data quality, allowing you to select sites that are statistically more likely to meet your specific timeline goals.
What data foundation supports the feasibility insights?
Medidata leverages the industry’s largest proprietary dataset, comprising over 38,000 trials and 12 million patients across 140+ countries. Additionally, the data is refreshed weekly from over 8,000 active studies, ensuring that your feasibility assessments and benchmarks are based on relevant, real-time industry performance rather than outdated historical records.
Can the solution assist with meeting diversity enrollment targets?
Yes. The platform allows you to identify sites with a proven historical track record of recruiting diverse patient populations. By using indication-specific, cross-industry patient demographic data, you can prioritize sites that consistently meet diversity goals, helping you achieve inclusivity targets and comply with regulatory Diversity Action Plans.
How are scenarios simulated for enrollment contribution?
Scenarios are simulated using Medidata’s AI models, which are trained on real-time Rave EDC data and account for user-defined parameters—such as "must-have" or "must-not-have" regions, countries, and sites, as well as specific performance metrics. The platform generates optimized scenarios for single or multiple enrollment duration targets to solve for the leanest, most efficient study footprint.
Does Medidata offer training for its clients and partners?
Yes. Medidata offers a variety of training options for our clients and partners, including both self-paced and instructor-led courses. To learn more about available courses and to access our resources, please visit the Medidata Global Education and Training section.