Data Certification Standards/Data Certified Units
The ECRIN Data Centre Certification Standards is ISO 9001:2015 certified and provides a structured quality framework for clinical trials units that manage data for multinational, non‑commercial clinical research. They set expectations for governance, staffing, information technology infrastructure and day‑to‑day data management operations so that clinical data are handled securely, reliably and in line with good clinical practice and data protection requirements. Units meeting these standards can be recognised as “ECRIN Certified Data Centres”, giving investigator‑sponsors greater confidence when selecting a data management partner for complex, investigator‑initiated trials.
On the ECRIN website, data certification information is organised into short sections on the programme, the certification process and the standards, with links to downloadable documents, e.g., Requirements for Certification of ECRIN Data Centres with Explanation and Elaboration Standards Version 5.0, May 2023. The 126 requirements, or standards, included in the current version are divided into 19 separate lists, focused on IT, data management, the more generic aspects of trial management, and – new in this version – statistical programming. Each standard has a code, a title, and a single statement summarising the requirement.. Each requirement is presented in a structured format, making it suitable both for formal audit and for internal self‑assessment by units establishing or improving their data management function.
Certification is granted following an application and on‑site audit, with decisions taken by an independent board, and is time‑limited. ECRIN maintains a public list of currently certified units.
The ECRIN Data Centre Certification Programme provides investigators with access to independently assessed, high-quality clinical data management services. By partnering with a certified data centre, academic sponsors can strengthen data quality, regulatory compliance, data integrity, and operational efficiency while reducing the risks associated with managing complex clinical trial data. This is particularly valuable for investigator-initiated and multinational studies, where robust data management infrastructure is essential but may not be available within a single institution.