Regulatory Science Symposium: Monitoring and Auditing Session 3: Auditing GCP Systems for Data Integrity (2016)

1. Data Integrity concepts
   • ALCOA + CCEA
   • Paper replaced with electronic files
   • GMP inspections have revealed data integrity problems all over the world
2. GCP systems
   • EDC-Electronic Data Capture
   • IWRS-Interactive Web Response
   • Instrument Systems
   • LIMS-Laboratory Information Management
   • PIMS- Patient Information Management
   • PV- Pharmacovigilance
   • ECG reading systems
   • Radiological image reading systems
   • Programs to analyze and report subject data
   • LMS-Learning Management
   • EDMS- Electronic Document Management
   • ETMF- Electronic Trial Master File
   • CTMS- Clinical Trial Management
3. Regulatory framework for enforcement
   • Investigator, Sponsor and CRO are 3 responsible entities in a clinical trial
   • Intended Recordkeeping ICH E-6: Investigators are responsible for all data in CRFs. Any discrepancies are the responsibility of the investigators.
   • IVRS Provider, EDC Provider, ePRO Provider, CRO, Central Lab are all selected by the Sponsor. Sponsor delegates all the responsibilities.
   • Investigator prepares case histories and sends data to the contractors/sponsors.
4. Auditing for data integrity
   • Quality Management System (QMS) auditing helps us verify that a provider has processes, procedures, equipment, facilities, supporting documentation and qualified personnel to provide high quality services.
   • Data integrity audits show how a sponsor is preventing and detecting data integrity problems and risks.
   • Preparing for a data integrity audit
     • Review:
       • Protocol
       • Quality agreement
       • Documented requirements
       • Instructions provided and data transfer specifications
     • Ask clinical team about problems they experienced
       • Study manager
       • Data manager
       • Statistician
       • Programmer
       • Technical monitors
     • Identify parameters that have a serious impact on subject safety:
       • Exclusionary parameters
       • Change in parameters
       • Efficacy parameters
     • Identify equipment used to create those parameters
     • Research the equipment
     • Draft a data flow diagram
   • Conducting a data integrity audit
     • Don’ts:
       • Read all QMS documents
       • Focus only on computer system validation
       • Review descriptions
       • Read all disaster recovery plans
     • Do’s:
       • Work to develop high quality data
       • Focus on implementation parameters
       • Look at audit trails
       • Pay careful attention to how flat files are managed
       • Concentrate on QMS documents that support your work

Accompanying text created by Amelia Spinrad | Regulatory Knowledge Support Specialist | spinrad@usc.edu