Data integrity – along with human research subject protection – have long been primary quality objectives of clinical research. With the advancement of technology and science in human research, regulatory agency’s focus on data integrity has intensified. GCP enforcements, such as 483's, Warning Letters, Notices of Concern, and EU inspections continue to escalate and describing the impact of non compliance and risk to data integrity. With multiple regulatory and industry guidances, organizations responsible for clinical research are enhancing data integrity infrastructures to comply with these quality requirements and address challenges ranging from access management to internet and database hackers.
This course will provide the regulatory background of data integrity and hands on experiences with the design, development, execution and monitoring of critical data and systems using a hypothetical case-study (raw data, records, data flow diagram, RACI, and other materials). In small groups, you will use a plan do check act framework to evaluate this hypothetical case study. Goals include identification and prioritization of risks to data integrity from data entry or acquisition through evaluation, reporting, archiving, and retrieval.
Templates will be used to develop inspection ready documentation.
Who should attend?
At the conclusion of this course, participants should be able to:
- Discuss the importance of data integrity
- Interpret the FDA/EU/PICS/MHRA/WHO data integrity requirements
- Distinguish the different types of data integrity issues
- Develop and execute plans to achieve data integrity expectations throughout the lifecycle of data
- Apply risk-management principles to prevent breaches to data integrity