Case Study

How To Double High-Performing Site Count In A Priority Indication

Source: Medidata AI
GettyImages-1297414842-lab-computer

Challenge

A top 10 biopharmaceutical company was looking to gain agility and confidence in their trial planning, site selection, and
enrollment decisions in a priority indication. Typically, the sponsor used a proprietary methodology based on internal data
as well as a prominent data-sharing initiative to categorize and prioritize Tier 1 sites for site selection. As they embarked on upcoming clinical trials, the sponsor wanted to expand their site list and gain a deeper understanding of how existing sites in their database performed.

As the clinical trial landscape grows more complex, running successful clinical trials becomes more and more difficult.
Currently, 80% of trials do not enroll within target enrollment timeframes and 55% of terminated trials cite low patient accrual as the main reason.1, 2 These enrollment issues are impacted by many factors, including site selection, industry competition, increasingly targeted patient populations for precision medicine treatments, and changing trial conditions. In such a cut- throat environment, it was critical for this top sponsor to choose high-performing sites based on reliable data to set their trials up for success.

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