Data Integrity : FDA/EU Requirements and Implementation

Day 1 : 08h30 AM - 04h30 PM

• 08.30 AM - 09.00 AM: Registration
• 09.00 AM: Session Start
• Day 1 – Lectures and Workshop Exercises
• Module 1: 
  Definitions, requirements and approaches for data integrity
  • Definition of data integrity: ALCOA+
  • The importance of data integrity for public health
  • Regulations and guidelines related to data integrity
  • Main reasons for non-compliance
  • Warning letter statistics by subject and countries
  • FDA’s inspection and enforcement strategy of Part 11
  • Lessons from recent FDA Warning Letters and how to avoid them
• Module 2: 
  Introduction to FDA 21 CFR Part 11 and EU/PICS Annex 11 
  • Objective, scope, current situation and future of Part11 
  • Requirements for electronic records 
  • Requirements for electronic and digital signatures 
  • Additional requirements from the PICS/EU Annex 11, 
  • Developing a gap analysis 
  • Upgrading existing or purchasing new systems: 
  • Six steps for implementation of Part11/Annex 11 
  • Examples on how to implement Annex11 and Part11 
• Module 3: 
  Cost effective Validation of software and computer systems
  • Selecting the right validation lifecycle model 
  • Going through examples of a complete computer system validation from planning to reporting
  • Examples for risk based DQ, IQ, OQ and PQ 
  • Vendor assessment and supplier agreements
  • Validation of existing systems
  • Maintaining the validated state: Revalidation vs. periodic review
  • Recommendation for network qualification and cloud Computing
• Module 4: 
  Aligning data integrity with the company’s quality system and Code of Conduct
  • Contributions to poor quality
  • Consequences of poor quality systems
  • Recommendations from the FDA 
  • ICH Q10 – The quality system for pharma industry
  • Aligning key requirements with data integrity: e.g., CAPA system, training, internal, audits, risk management and ongoing improvements
  • How a Code of Conduct helps to ensure data integrity
  • Definition and contents of a related Code of Conduct

Day 2 : 08h30 AM - 04h30 PM

• Day 2 - Lectures and Workshop Exercises
• Module 5: 
  Definition and Handling of Raw Data
  • Definition of Raw Data
  • Examples of raw data 
  • Raw data for paper based and electronic systems
  • Criteria for electronic raw data with paper print-outs
  • Raw data management along the data lifecycle
  • Changing of raw data
  • Archiving of raw data from electronic and hybrid systems
  • Going through examples 
• Module 6: 
  Good documentation practices to ensure data integrity
  • Requirements for documentation ( ALCOA+)
  • Documents that must be readily available
  • Examples for good and bad documentation
  • Good practices for paper and electronic data
  • How to avoid common documentation mistakes
  • The importance of global documentation
  • Improving effectiveness through standardization
• Module 7: 
  Strategies to detect and avoid integrity issues
  • Recruit, train and retain employees who will be responsible for ensuring data integrity
  • Possible causes for data integrity breaches
  • Show consequences of data integrity violations
  • Understand system vulnerabilities, motivation and likelihood operators might compromise data
  • Understand high risks in the data lifecycle
  • Formally investigate internal hints about data falsification
  • Learning from internal audits and FDA inspections
• Module 8: 
  Data Integrity Auditing: Internal audits and FDA inspections
  • Going through a typical FDA inspection as a model for internal audit
  • FDA’s new approaches to data integrity inspections
  • Typical audit questions
  • Identifying systems that must be audited based on risk
  • Typical audit findings
  • The importance of the exit meeting
  • Writing a corrective and preventive action plan to fix data integrity audit findings
  • Follow-up on CAPA through verifying effectivess​