Hidden Threats in Clinical Trials

• Paper forms & Excel
• Lost Samples
• Label Mismatches

Unfortunate Status Quo

Every clinical trial hinges on the quality and integrity of its data. But in far too many studies, that data is built on a shaky foundation: mismanaged, mislabeled, or missing biological samples. Despite all the digital tools used in clinical trials—EDCs, CTMSs, lab information systems—there’s a glaring blind spot in how samples are actually collected, handled, and tracked at the site level. Many sites still rely on paper requisitions, sticky notes, and verbal instructions. Samples go missing. Labels don’t match. Timepoints are off. And the result is a chaotic, time-consuming effort to reconcile it all months later—when it’s often too late.

Costly Affects

This isn’t a niche problem—it’s a systemic one. Sponsors report delays in 80% of U.S. studies, and mishandled samples are a major contributor. Every day of delay can cost tens of thousands in operational costs and millions in lost drug sales. Worse, it undermines the trust and contributions of the patients who participate in these trials, giving their time and biological material under the assumption that it will be used responsibly.

What the Industry Needs

We need better infrastructure. We need tools that start the chain of custody at the patient’s arm, not the central lab. We need real-time visibility, protocol enforcement, and interoperable systems that work with the messy, variable, real-world environments of clinical trial sites. There won’t be a one-size-fits-all solution—there shouldn’t be. What we need is more innovation in this space, more attention on the operational backbone of trials, and more collaboration between vendors, sites, sponsors, and labs. OverSite is one product working to close that gap, but we need a whole ecosystem of solutions to truly fix the problem.

Good news!

Change is happening. More people in the industry are recognizing the cracks in the system—and stepping up to fix them. With collaboration, shared standards, and smarter tools, we can build a future where sample quality is never the reason a trial fails, and where every patient contribution counts exactly as it should.