In every clinical trial, sample data gets trapped in three separate silos:

• The Sponsor's Data Your EDC and CTMS systems capture protocol requirements, patient enrollment, and study milestones—but they don't know what's actually happening with samples in real time.
• The Lab's Data Your central lab maintains their LIMS with processing schedules, test results, and sample inventories—but they're working from outdated collection information and manual data transfers.
• The Sites' Data Your clinical sites track patient visits and sample collection in spreadsheets, paper logs, and separate systems—but this critical information rarely syncs with sponsor or lab systems in real time.

When these three data worlds don't align, your team spends weeks—sometimes months—reconciling discrepancies:

• Missing samples that were collected but never logged properly
• Timing conflicts between what the protocol requires and what actually happened
• Processing delays when labs receive samples with incomplete or conflicting information
• Quality issues discovered too late because no one had the complete picture
• Manual auditing to trace where the disconnect happened and who's responsible

These reconciliation efforts don't just waste time—they put your entire study timeline at risk.

Instead of three separate systems trying to communicate after the fact, OverSite creates a single, real-time view of sample collection and processing that everyone can trust:

• Sponsors see exactly what samples have been collected, when, and their current status—without waiting for site reports or lab updates
• Labs receive complete, accurate sample information the moment collection happens—eliminating guesswork and processing delays
• Sites follow digital protocols that automatically sync with sponsor requirements and lab specifications—no more manual data entry or protocol deviations

Because OverSite captures sample data at the point of collection and shares it instantly across all stakeholders, issues get caught and resolved before they become costly problems:

• Protocol deviations are flagged immediately, not discovered during data review
• Missing samples are identified within hours, not weeks
• Processing requirements are communicated clearly to labs before samples arrive
• Quality issues are documented and tracked in real time across all systems