Blog

When Verified Clinical Trials (VCT) first launched, the idea was simple: What if sponsors and sites could share a single, privacy-protective way to see when a research participant was already in another study? At the time, preventing duplicate subjects in clinical trials, catching professional patients, and using a shared research subject database / clinical trial

Verified Clinical Trials: The global research subject database Most discussions about clinical trial economics start with big, visible levers: Those all matter. But there’s another lever that’s usually underplayed in financial models—precisely because it’s quiet and hard to see: The quality of who you actually randomize. Not just how many participants you enroll, but how

In the hottest therapeutic areas today, it can feel like everyone is looking at the same recruitment map. GLP-1 and obesity. CNS and psychiatry. Dermatology. Vaccines. Rare diseases in concentrated geographies. Sponsors design different protocols, contract with different CROs, choose different sites—and yet, in practice, they’re often competing for the same limited patient pools at

Clinical trials have never been better measured — and never more vulnerable to the risks that metrics don’t capture. Sponsors are excellent at tracking what happened: enrollment velocity, screen-failure rates, protocol deviations, data queries, adverse events, and time to database lock. These are essential operational and quality signals. But as therapeutic areas become more competitive

In today’s clinical research landscape, data integrity and subject safety are paramount — yet both remain at risk from a persistent and often invisible problem: duplicate and professional research participants. Across thousands of studies and millions of verifications, Verified Clinical Trials (VCT) has amassed the largest global dataset on subject duplication and protocol violations in

The Aha Moment We See Again and Again It usually starts the same way. A sponsor or site team is confident that duplicate subjects or professional pateints are not an issue in their clinical trial. After all, it seems rare—an unlikely problem compared to recruitment challenges, protocol deviations, or data entry errors. Then comes the