Protocol Optimization
Protocol complexity and limited visibility into real-world performance make it hard to design trials that are both scientifically rigorous and operationally feasible.
Medidata Protocol Optimization uses AI trained on proprietary, cross-industry data to evaluate planned protocols against how similar studies have performed—helping you find inefficiencies early and refine trial design before start-up.
Identify Risk Early. Improve Feasibility.
Activity-level Metrics
Standardized, Cross-industry Trial Data
AI-powered Predictive Modeling
Scenario
Planning
Turn Smarter Study Design into Success
Design with Confidence
Balance Scientific Rigor and Operational Execution
Protocol decisions shape trial performance long before the first patient enrolls.
Use cross-industry benchmarks and predictive modeling to evaluate design choices early.
Simulate changes to understand their impact on enrollment, retention, cost, and site and patient burden—so you can balance scientific rigor with operational feasibility from the start.
FAQ
How does Protocol Optimization help reduce the number of protocol amendments?
The solution allows you to confidently assess the operational feasibility of your protocol before it’s finalized. By leveraging standardized, cross-sponsor data to identify risk factors early, teams can evaluate the operational impact of design changes up front, significantly reducing the need for costly amendments later in the study lifecycle.
Can Protocol Optimization predict the impact of design changes on enrollment and retention?
Yes. Protocol Optimization uses AI-powered predictive modeling to run simulations that forecast how specific design elements (such as procedures and visit frequency) will affect key outcomes. This allows you to see the predicted impact on enrollment rates, dropout rates, and timelines, helping you identify and mitigate risks proactively.
Does the platform allow us to assess site and patient burden?
Yes. You can benchmark your protocols against real trial data to accurately quantify patient and site burden at the activity and visit level. This capability enables you to identify likely cost drivers and present leaner, less burdensome trials to sites, which directly improves recruitment and retention outcomes.
What data informs the predictive modeling in Protocol Optimization?
The solution generates insights from one of the industry’s largest datasets, comprising cross-industry global clinical trial data from over 38,000 trials and 12 million patients. This broad data foundation allows the AI to transform site, patient, and indication-level data into clear, actionable scenarios for your specific study.
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.