Mislabelled vials or mishandled specimens in clinical trials can compromise data accuracy, potentially affecting patient safety and outcomes. With increasing study size and complexity across multiple locations and partners, accurate and consistent sample handling is crucial.

Effective sample management necessitates a structured system to track the diverse range of samples collected and analysed at each step in order to maintain data integrity and adhere to stringent regulatory and scientific requirements. Failures in sample management can result in delayed regulatory reviews, incorrect research findings, diminished data quality, and lost opportunities.

Consequently, clinical research teams are increasingly looking for technology that can standardise workflows, minimise errors, and enhance transparency throughout the entire sample lifecycle.

Common Challenges in the Sample Journey

Clinical trial sample management encompasses multiple complex stages from collection to analysis, each with unique operational and technical demands where even minor errors can significantly impact data reliability.