Computerised System Validation Master Class
Book together with the course "Computerised System Validation - Leveraging Suppliers" and save up to € 590,-

Computerised System Validation Master Class

Berlin, Germany

Seminar Nr. 20457

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

 

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Rückfragen unter:
Tel.: 06221 / 84 44 0 E-Mail: info@concept-heidelberg.de

Sprecher

Frank Behnisch, CSL Behring, Germany
Stefan Münch, Körber Pharma Consulting, Germany
Yves Samson, Kereon, Switzerland
Dr Robert Stephenson, Rob Stephenson Consultancy, UK

Zielsetzung

As a specialist for the validation of computerised systems, the event will provide you with
  • Suggestions on how current regulatory guidance on computerised systems relating to data integrity, critical thinking and CSA (Computer Software Assurance) can be put into practice
  • Real-life examples of how validation effort can be scaled according to risk-based approaches
  • Answers to specific questions, e.g. on source code review or on creating specification documents
  • The opportunity to bring questions from your own practice up for discussion

Hintergrund

The V-model has become a standard worldwide methodology for the validation of computerised systems. Regulatory requirements, as well as industry guidelines, like GAMP®5, are orientated towards this model. In practice, you as a validation specialist will want to know how to apply this model to current and increasingly complex validation projects.

Zielgruppe

The Master Class is directed at employees from
  • IT
  • Production
  • Engineering
  • Quality Assurance
  • Quality Control
Participants should already have gained experience in the validation of computerised systems, and preferably will have also attended a basic CSV Course.

Programm

Introduction – Gain Understanding of Delegate Experience and Background

Workshop 1: What the Delegates expect
  • Capturing delegates expectations
  • Sharing and reducing to key points in groups
  • Sharing with all delegates and tutors
Current Challenges and Evolution for CSV Activities
  • What does compliance really mean?
  • Data Integrity
  • Securing operation: cybersecurity
  • Project agility
  • Cost efficiency vs effective risk management
  • Applying critical thinking
Roles, Responsibilities and Governance
  • PQS – Pharmaceutical Quality System according to ICH Q10
  • Responsibilities
    • Operational ownerships
    • Supporting roles
  • QA oversight
Workshop 2: Governance Benchmark
  • Polling Exercise plus facilitated discussion
  • IT and System Governance
  • CSV Roles and Responsibilities
  • Role of Quality Unit
Practical Use of Scalability
  • What do we mean by Scalability?
  • How does it work in practice?
  • How can we combine documents successfully?
  • How much is enough?
Workshop 3: Scaleability of Validation Activities
  • LIMS – Laboratory Information Management System
  • Laboratory computerised equipment
  • Process control system: PLC – Programmable Logic Controller
Writing Requirements Documents
  • Requirements gathering
  • Writing good requirements
  • Use of templates / boilerplates
  • Requirement Quality
Requirements: The Good, the Bad and the Ugly
  • Good, bad, and could-be-better requirements
  • Testability
  • Use of templates / boilerplates
  • What you should never write
Ideal Content of a CSV SOP
  • Embedding the CSV SOP into the PQS
  • Topics to address
Data Integrity and Record Management: A Necessary Long-Term Approach
  • Regulatory context
  • Document life cycle
  • Retention requirements and constraints
  • Supporting processes
  • Areas of concern
System Classification – A Record-based Approach
  • Needs for record-based system classification
  • Classification criteria
  • Class A, B, C, D
Workshop 4: System Classification
 
Design Review – How to Apply Critical Thinking?
  • CSA – Computer Software Assurance
  • Scaleable Risk Management
  • Document Review
Workshop 5: Design Review Scaleability
  • Combining Risk Management & Design Review
Bringing Legacy Systems into Compliance
  • How to approach legacy system remediation
  • Examples
    • Learning management system
    • Laboratory Instruments
Interactive Session: Good Validation Practices
Open session in which delegates score their CSV approach against 12 good validation practices
  • Each good practice introduced
  • Delegates score themselves
  • Results consolidated and fed back
  • Allows delegates to compare their CSV system against best practice and other practitioners
Alternative & Agile Approaches
  • Alternative software development models
    • Unified Process, Scrum
  • Agility objectives
    • Need for flexible engineering methodologies
  • What Agile engineering is not
    • What Agile engineering needs
  • Practical approaches and recommendation
    • Conditions for success
Validating Spreadsheets
  • Why are spreadsheets high risks?
  • Design considerations
  • What is important (risk again)!
  • How to document spreadsheet validation
Code Review
  • Principles of code review
  • Regulatory expectations
  • Performing code reviews
  • How to document code reviews
Elaboration of a Data Integrity Programme
  • Data Integrity Programme: What to do?
    • Topics to address
    • Action planning
  • Embedding the Data Integrity Programme into the PQS
  • Progress Reporting
Case Studies: Complex Projects
  • Global projects
    • Roles & Responsibilities
    • Data-related requirements
  • Large systems
    • Phase-based implementation and deployment
  • Interface projects
    • Roles & Responsibilities
    • Testing
Today / Future IT Compliance Challenges
  • Open Source Software validation
  • Challenge demands Infrastructure platforms for applications
  • Global systems validation vs local defence
  • Paperless recipes based production – ISA 95 / S 88
  • Cloud Computing – Data Integrity
  • Validating Artificial Intelligence (AI)
  • Challenges for data integrity on Lab-Systems
Real Life Qualification / Validation Projects
  • Real Life Qualification / Validation Projects
  • Requirements
  • Constraints
  • Issues identified
  • Lessons learned

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