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ECA - Data Integrity

Data Integrity (9/10 April 2019)

Objective

  • You will get a deeper understanding what European inspectors expects from pharmaceutical companies in regard to Data Integrity
  • You will learn how to prepare your company for an successful inspection in regard to Data Integrity
  • You will learn how to investigate Data Integrity issues in your Company especially in manufacturing and Engineering
  • You will discuss supplier’s responsibility in Data Integrity compliance

Background

Even Data Integrity is one of the basic GMP principles since years multiple Data Integrity citations were reported by FDA und European inspectors during the last 3 years. Many US Warning Letters and EU Non-Compliance Reports deal with serious Data Integrity violations. Data Integrity questions have been and will continue be the focus of many GMP inspections.

As a consequence international authorities – FDA, EMA, PIC/S, WHO, MHRA - published (draft) documents to describe the regulatory expectations of Data Integrity.

Although all guidelines are not intended to impose additional regulatory burden to the regulated companies, a lot of uncertainty predominates the pharmaceutical industry how to implement these requirements into the daily business and how to integrate supplier’s experience.

Moderator

Yves Samson, ECA IT Compliance Interest Group

Target Audience

  • Managers and staff from Manufacturing, QA and Engineering of pharmaceutical companies and suppliers
  • Auditors (internal and external) responsible for performing self-inspections or external audits and needing to understand and assess data integrity

Programme (9 April 2019)

CONGRESS KEYNOTE
Pharmaceutical industry in digital change

Thomas Reiner, CEO, Berndt+Partner

  • Changes in the value chains
  • Opportunities and risks for production processes
  • What can and will change for packaging?
  • Strategies to benefit from Change

 

Requirements for Operating Computerized Systems and Data Management
Dr. Philip Hörsch, Vetter Pharma-Fertigung

  • Data Integrity: Definitions and requirements for operating computerized Systems
  • Risk-based evaluation of data management (data input and Output during operation) and follow-up activities for application (e.g. data review)
  • Application of data management evaluation in case of new System acquisition and for assessment of existing Systems
  • Examples from quality control and manufacturing (aseptic, secondary packaging)

Requirements in Data Integrity
Dr. Gerald Kindermann, F. Hoffmann La-Roche

  • Data Integrity – Data species & ALCOA principles
  • Hot topic - Myths Critical factors for DI program
  • DI Problems
  • Case study DI in the manufacturing area System / data mgmt.
  • User set up

Data Integrity from a QP’s Perspective
Gabriela Schallmeiner, Austrian QP Association

  • The Regulatory Pillar
    • regulatory baseline on data integrity
    • regulatory Impact on the Qualified Person (QP)
  • The Qualified Person’s “Data” Challenge
    • Quality Management (QM) System Fundamentales
    • How GMP documents/data are related
  • Make Data Integrity Integral to a Qualified Person‘s Daily Work
    • Data Integrity Impact on the QP
    • What gives a QP the confidence to certify a Batch

Inspecting DI in Manufacturing – what does an inspector expect?
Dr. Arno Terhechte, Bezirksregierung Münster

  • Regulatory Update (Chapter 4, Annex 11, PIC/S Guidance Good Practices for Data Management and Integrity)
  • Definitions of Data, Raw Data, original data in Manufacturing
    • Aggregation of Data
    • Paper Records versus Continuous Monitoring / E-Records
  • Upgrade / Modernizing the QMS with regard to Data Integrity
  • Self Inspection, Assessment, Data Flow Analysis
  • Data Integrity with regard to Outsourced Activities
  • Data Integrity during Inspection / Inspection Findings

Data Integrity Assessment Manufacturing: Preparation, Conducting and Remediation Activities
Stefan Schöttle, Roche Diagnostics

  • Authorities Focus
  • Corporate Guidelines
  • Assessment Project
  • Best practises
  • Challenges

A Paperless Lab, a Good Idea for Data Integrity, Risk Minimization and Lean Management?
Dr. Thomas Meindl, Labor LS

  • Data integrity by avoidance of human errors by use of electronic data evaluation and documentation
  • Minimization of contamination risk due to contaminated paper.
  • Optimization and reduction of errors by implementation of electronic Workflows
  • Paper management: avoidance of excessive use of prints in order to save space in physical archives

 

Programme (10 April 2019)

CONGRESS KEYNOTE
EU GMP Inspection in Sterile/Aseptic Production
Klaus Eichmüller, Wolnzach, c/o Regional Council Darmstadt, GMP Inspectorate, Germany
Head of Inspectorate

  • Main focus areas of inspections
  • Frequently detected findings
  • Data Integrity issues – where are possible weak spots?
  • Possible new areas due to the revision of Annex 1 and further regulatory changes

 

How QA can check for data integrity in electronic Systems
Knud Ryhl, Novo Nordisk

  • A practical approach to data integrity
  • Examples of where to look for applied data integrity
  • How to approach data integrity when you have no clue of where to start
  • Computer systems are manageable

Data Integrity in manufacturing and engineering Environments - Another source of weaknesses or Compliance by Design?
Yves Samson, ECA IT Compliance Interest Group

  • Identifying applicable data integrity requirements
  • Design review: how to promote and to secure compliant design − Product, process, data, System
  • Securing data integrity during the engineering and commissioning activities
  • Necessity to rely on secure and robust IT infrastructure

Audit trail functionality and review – expectations from an inspector
Ib Alstrup, Danish Medicines Agency

  • Good documentation practice
  • Qualities of the audit trail functionality
  • Qualifi cation of the audit trail functionality
  • Audit trail Review

Expectations of an inspector on a training system with respect to data Management
Klaus Eichmüller, Wolnzach, c/o Regional Council Darmstadt

  • Introduction
  • Expectations on the System
  • Expectations not met - examples

Data Integrity requirements to technical suppliers – Expectations to equipment suppliers and Engineering service Providers
Yves Samson, ECA IT Compliance Interest Group

  • Regulatory management: knowing and understanding regulatory requirements
  • Configurability to support customer process requirements
  • System design expectations
  • Cybersecurity requirements and constraints for Equipment
  • Eff ective support of review activities

TBD
Miro Zdilar, Teva