Data Integrity Quality Oversight in the QC Laboratory - Live Online Training

Data Integrity Quality Oversight in the QC Laboratory - Live Online Training

Course No 20683

This course is part of the GMP Certification Programme "ECA Certified Data Integrity Manager". Learn more.

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Dr Christopher Burgess, Chairman of the ECA Analytical Quality Control Group
Dr Markus Dathe, F. Hoffmann-La Roche AG, Switzerland
Dr Bob McDowall, Member of the ECA IT Compliance Interest Group


The involvement of Quality Assurance in ensuring data integrity in GMP regulated laboratories is discussed in both the PIC/S and WHO guidance documents.  However, turning guidance document recommendations into practice can be difficult, especially if members of QA are not familiar with the topics covered in these guides. This two-day, interactive workshop-based course is intended to fill this gap in the training spectrum.  After an introduction covering the scope and regulatory requirements of quality oversight for GMP regulated laboratories there are presentations, Q&A sessions and case studies on the main topics of the course:
  • Understanding process and record risk by using data process mapping
  • Controlling master templates and blank forms
  • Raising and handling data integrity concerns
  • Data integrity Audits
  • Data integrity investigations
The case studies material is based on real world examples, so that the attendees can gain experience that they can take back to their own organisations.


Data integrity is a major topic in the pharmaceutical industry and organisations supporting it such as contrast research and manufacturing organisations.  The regulatory focus has been in Quality Control and Analytical Development laboratories working to GMP especially since 2012 with the updated FDA Compliance Programme Guide 7346.832 for Pre-Approval Inspections.  This guide has as objective 3 the data integrity audit.  Therefore, it is important that Quality Assurance be aware of the FDA approach as well as ensuring that laboratory activities are under control, compliant and ensure data integrity.

Target Group

  •  Managers and staff from Quality Control and Analytical Development Laboratories of pharmaceutical companies
  •  Contract Research Organisation and Contract Manufacturing Organisation laboratory personnel
  •  Quality Assurance staff involved in reviewing laboratory data or performing data integrity audits
  •  Auditors (internal and external) responsible for performing self-inspections or external audits and needing to understand and assess data integrity

Technical Requirements

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Introduction to the Course
  • What will be covered in the Course
  • Introduction to the teaching Team
  • Roles of Quality Assurance and Quality Control defined and discussed
Regulatory Guidance for Data Integrity Quality Oversight
  • Review of data integrity guidances: PIC/S, WHO, EMA, MHRA, GAMP Guide for quality assurance role in data integrity and data governance
  • Building a framework for quality oversight for Data Integrity (DI) in a GMP analytical laboratory within the QMS
  • How culture can impact data Integrity
  • Identifying key QA roles in the Data Integrity programme
Knowing and Managing Data Integrity Risk
  • Data Process Mapping for Paper and Computerised Processes in the laboratory
  • Identifying risk to records and mitigating them
Case Study 1: Data Process Mapping
  • Review of data process maps for paper and hybrid process
  • Identification of record and data integrity risks
  • Proposals for risk Mitigation
  • Course feedback and discussion
Role of Quality Assurance in Control of Master Templates and Blank Forms
  •  Overview of regulatory guidance for blank forms – 1993 to date
  •  Process flows for master templates and blank form use
  •  Identifying the QA role in the process
  •  Look at alternative options from paper
Raising Data Integrity Concerns
  •  Process for handling concerns outlined
  •  Confidentiality of the people and process
  •  How to handle whistle blowers
Recap of Day 1 and Introduction to Day 2
Case Study 2: Handling Data Integrity Concerns
  •  How should a concern be raised and to whom?
  •  How will the matter be kept confidential?
  •  Generating a high-level scope and action plan
Overview of Data Integrity Audits and Investigations
  •  Regulatory guidance
  •  Approaches for DI audits – computer system inventories, paper processes and critical data identified
  •  Preventing overlap with computer system periodic Reviews
  •  Dealing with data integrity violations: the DI Investigation
Case Study 3: Identifying Data Integrity Audit Priority and Frequency
  •  From a list of processes and systems attendees will identify the priority order of processes and systems to be audited
  •  From the priority, the audit schedule will be developed
  •  Frequency of DI audit of critical systems and paper processes
Case Study 4: Developing the Data
  • Integrity Audit Coverage
  • Scope of the data integrity Audit
  • What will you audit?
  • How will you audit a computerised system vs. a paper process?
Case Study 5: Data Integrity
  • Investigation – Determining the Scope
  • A data integrity violation has been found during a data integrity audit and an investigation is to be launched
  • In a facilitated discussion, the course will define the scope and boundaries of the Investigation
Case Study 6: Data Integrity
  • Investigation – Findings, Root Cause and CAPAs
  • A list of findings from the investigation will be given and attendees must determine if they are poor data management errors or falsification
  • Identification of the root cause
  • What are the CAPAs: immediate fixes and long-term remediation Actions?
Key Learning Points

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