Site Selection

Predict top-tier investigators for higher enrollment rates

In traditional trials, sites are identified largely using relationships and past experience – and nearly half of sites miss enrollment targets1. IQVIA has created a novel, more precise approach to predict the best-performing sites and investigators for your study.  

Using the power of the IQVIA™ CORE, we apply unmatched global real-world data, domain expertise, machine learning and predictive modeling to site identification. This allows us to bypass the low performers, and instead prioritize the top potential recruiters – speeding enrollment and your study completion. 

To validate this new insight-driven approach, we put it to the test against the universe of our >500 ongoing clinical studies.  See the impact based on actual enrollment rates below, and contact us to learn more.

 

1 Getz, K. Changing Drug Development Landscape and its Anticipated Impact on R&D Operations. http://csdd.tufts.edu/files/uploads/Outlook-2014.pdf .