Increase speed to first patient in with data-driven analysis
Maximize your enrollment potential with a platform that combines subject matter expertise with machine learning to rapidly provide predictive insights for feasibility planning.
We are accelerating clinical trial timelines by bringing together our technical/machine learning capabilities with our expertly curated, best-in-class clinical data sets.
The core machine learning engine in Citeline Study Feasibility is based on gradient boosted decision trees that are trained on Informa’s data and proprietary engineered features.
In a single platform, feasibility scenarios can be instantly modeled, optimized, compared, and shared with explain-ability and transparency. Users can see what trial design elements are having a positive or negative impact on predictions and refine their plans accordingly.
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