Data Integrity in the pharmaceutical quality system / Data Governance
- Which PQS elements need to be added or updated?
- The Data Integrity Program
- Priorities (immediate/short/mid-term)
- Governance responsibilities
- Data governance vs. IT governance
- Elements of a data governance
- Embedding data governance into the PQS
Data flow analysis
- Objective and purpose
- Electronic data flow
- Complete data flow
- Identification of possible weaknesses
Workshop on Data Flow Analysis
- Identification of data flow weaknesses and non-compliances
Metrics for Data Integrity
- Metrics in the context of a corporate data integrity programme
- Suggested metrics in the assessment phase
- Suggested metrics in the operational phase
- Control of Master Templates and Blank Forms
- Why is control of master templates and blank forms important?
- Regulatory requirements from FDA, MHRA, WHO, EMA and PIC/S
- Devising and controlling the master template
- Operational use of the blank forms
- Do you really want to work this way?
- Basis for Inspections: “PIC/S Good Practices for Data Management and Integrity in regulated GMP/GDP Environments”
- Data Integrity Assessment during Inspection
- Quality Control
- Inspection Findings
Preparing your company for an Data Integrity inspection
- How to present the DI status and future approach?
- Gap analysis
- Training program coverage
- Experience from FDA inspections – Hot Buttons
Second Person Review
- Regulatory and guidance document requirements for the second person review
- Role of the second person review
- Scope of the second person review
- Documenting the review for paper, hybrid and electronic systems
- Facilitated discussion on Second Persons Review
Quality Culture for Data Integrity
- Regulatory expectations for a data integrity quality culture
- Role senior management in creating the culture
- Components of a quality culture
- Reinforcement of the culture
QA oversight for data integrity
- Data integrity training
- Enforce data flows
- Internal inspection
- Audit of external organisations
Workshop on QA Oversight for Data Integrity
- Identification of QA oversight weaknesses
Vulnerability of Records
- What is record vulnerability?
- Protection and security of electronic records requirements
- What can go wrong? Scope of misfortunes that can impact records
- Assessment of record vulnerability and implementation of control measures
Workshop on Vulnerability of Records
- Working in teams, the attendees will be presented with a scenario of a computerised system that generates electronic records. They will assess the record vulnerability and determine the controls to put in place to protect the records and ensure data integrity. Team outputs will be discussed with all participants.
Audit trail review
- Regulatory Overview
- Essential Audit Trails in QA/QC/Manufacturing. Risk-based approach.
- What about legacy systems w/o Audit Trail?
- Who shall review Audit Trails? Documentation
- What process and documentation is appropriate in case of deviations/discrepancies?
Options for Long Term Data Retention of Laboratory Data
- Proprietary v open standards for laboratory data
- Options for long term retention:
- Keep original system, Virtualisation, Data migration
Case study Data Migration
- Principles of data migration
- Design of the migration process
- Risk-based elaboration of the verification strategy – case study examples
Cybersecurity / Cloud Computing / Time synchronisation
- Cybersecurity securing data integrity
- Robust IT infrastructure
- Time synchronisation
- Qualification of time dissemination
Results of a Data integrity audit from a contract laboratory
- Audit context, Audit scope, Findings, Root causes
Data Integrity Investigations
- What are data integrity investigations?
- Human and technical triggers for DI investigations
- Who should investigate the problem?
- Process description and how to document a DI investigation
- Should we inform regulatory authorities?
Workshop on Data Integrity Investigations
Based on a case study, attendees will be presented with key facts and determine what an organisation should do to investigate a data integrity issue. At the end of the workshop, during the discussion of the team outputs there will be a comparison with the work performed in the case study.