SOCAR’s data management systems – SOCDAT™ for research studies using paper CRFs or
e-SOCDAT™ for studies using electronic CRFs – combine clinical data and operational information within the same system. The implementation of SOCAR’s data management procedures and processes allow a true multidisciplinary approach thus allowing delivery of complete and accurate data in the most time efficient manner while maintaining the highest data quality.

Our experienced clinical and non-clinical data management teams work together on an ongoing basis to execute complete data management activities. This approach enables simultaneous medical and non-medical data checking which increases productivity and accelerates the timetable to declare data clean. During the data management process, (e-)DCFs are created as required, with automatic notifications sent to site personnel for (e-)DCFs requiring urgent resolution. The data management workflow is data driven and streamlined using detailed task lists. Scheduled visits and multiple data records (e.g. concomitant treatments, adverse events, and unscheduled visits) declared clean following the data cleaning process are locked on an ongoing basis.

This approach to data management ensures the availability of accurate and complete data for interim analyses and/or status reports which may be required during the conduct of a research project in addition to reducing the time to final database lock after the last patient visit.

SOCAR’s data management services include:

• Design, development and implementation of the research study database (paper based or electronic data capture) according to clients specifications and industry standards (e.g. CDISC, ODM)
• Testing and validation of each research project database according to well-documented procedures, ICH GCP predicate rule requirements, laws, and regulations for clinical trial conduct, computerised systems validation and FDA 21 CFR 11 for electronic record and signature use
• First and second data entry (for paper-based clinical studies)
• Data query management
• Data tracking
• Data quality assurance and quality control until final database lock
• Coding of medical conditions, (serious) adverse events and concomitant treatments and indication for use
• Planning and organisation of Blinded Data Review meetings in preparation of database lock