Data Integrity Master Class with full-day pre-course session Raw Data
27-30 August 2024, Copenhagen, Denmark
Course No. 21473
Speakers
Dr. Bob McDowall
R.D. McDowall Ltd.
Yves Samson
Kereon
Dr. Wolfgang Schumacher
formerly F. Hoffmann-La Roche
Dr. Franz Schönfeld
Regierung von Oberfranken
Note: All times mentioned are CEST.
Objectives
Pre-course session "Raw Data - Understanding, Defining and Managing"
The aim of this one day course is to understand what can be defined as raw data and to explore the meaning of the term for manufacturing, laboratory and quality records. Is there harmonisation of US and EU GMP regulations? For example:
What is a “quality decision” and what is the impact of having to define raw data for the process or system?
Can raw data be equivalent to complete information and complete data?
Should we treat manufacturing “information” and laboratory “data” as the same?
Data Integrity Master Class
Your will get familiar with the current regulatory requirements on data integrity and how regulators refine these requirements
You will get a deeper understanding what FDA and European inspectors expects from pharmaceutical companies in regard to Data Integrity
You will learn how to implement the (new) regulatory requirements on Data Integrity into your Pharmaceutical Quality System
You will learn how to prepare your company for a successful inspection in regard to Data Integrity
You will understand how to establish an effective Data Governance System
You will learn how to investigate Data Integrity issues in your company
Background
Pre-course session "Raw Data - Understanding, Defining and Managing"
FDA GMP in 21 CFR 211 requires “complete information” for manufacturing records and “complete data” for laboratory records. In contrast, Chapter 4 of EU GMP on documentation contains in the Principle three sentences that are in apparent contradiction to the United States regulations:
Records include the raw data which is used to generate other records
For electronic records regulated users should define which data are to be used as raw data
At least, all data on which quality decisions are based should be defined as raw data
In the days of harmonisation of regulations how can we reconcile these differences? This situation is compounded by the failure of EU GMP to define the term “raw data” in the regulations to help industry plan their approach to meeting these regulatory requirements.
Data Integrity Master Class
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.
Target Group
The courses are directed at
Managers and staff from Manufacturing, QC/QA and Analytical Development Laboratories of pharmaceutical companies
Contract Research Organisation and Contract Manufacturing Organisation manufacturing, laboratory and QA personnel
Auditors (internal and external) responsible for performing self-inspections or external audits and needing to understand and assess data integrity
Especially the Data Integrity Master Class course is directed to participants who have first experiences in Data Integrity, e.g. the ECA course “Data Integrity – Requirements for a GMP compliant Data Life Cycle".
For Attendees Only
Attendees will get a free electronic copy of ECA “GMP Data Governance and Data Integrity Guide” - Version 3
Pre-course session "Raw Data - Understanding, Defining and Managing"
Data, Information and Knowledge
Data vs information vs knowledge
From knowledge to insight
DIKI model
Product, Prcocess, Data
Regulations
US GMP regulations: 211.68(b), 211.180(d), 211.188 and 211.194(a-e): complete data and complete information
EU GMP Chapter 4 regulations – raw data principles outlined from a GMP perspective
Understanding GMP Definitions and Regulations for Raw Data
Original record / record
Raw data – MHRA GMP and US GLP definitions
Data and metadata
True copy
Complete data
Initial data
Translating raw data for a GMP environment: should we treat manufacturing and laboratory the same when it comes to raw data?
Interpretation of Raw Data for Production Systems
Raw Data for PLCs
PLCs linked to a SCADA system
SCADA linked to a Manufacturing Execution System
Interpretation of Raw Data for Laboratory Systems Using a process involving a chromatography data system and a LIMS, what constitutes raw data will be outlined in two scenarios
Hybrid CDS and manual input to the LIMS
Electronic CDS with automatic transfer to the LIMS
Managing sample management and preparation records
Workshop: Defining Raw Data for Production, QA and Laboratory Systems
Can a True Copy be Raw Data?
Workshop : What are Raw Data for Quality Decisions
Data Integrity Master Class
Regulatory Update
EU GMP Requirements
Chapter 4, Annex 11
Guidance Documents Overview (state of the art)
“These Guides are not intended to impose additional regulatory burden upon regulated entities”. Is this correct?
Data Governance, Dynamic Data
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
Data Flow Analysis
Objective and purpose
Electronic data flow
Complete data flow
Identification of possible weaknesses
Workshop on Data Flow Analysis
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
QA Oversight for Data Integrity
Data integrity training
Enforce data flows
Reviews
Internal inspection
Audit of external organisations
Workshop on QA Oversight for Data Integrity
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?
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)
Capacity, Timing
Governance responsibilities
Data governance vs. IT governance
Elements of a data governance
Embedding data governance into the PQS
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?
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 Person review
Facilitated Discussion on Second Person Review
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
DI Inspections
Basis for Inspections: “PIC/S Good Practices for Data Management and Integrity in regulated GMP/GDP Environments”
Data Integrity Assessment during Inspection
Quality Control, Manufacturing
Inspection Findings
Workshop: Data Inspection Findings
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
Case Study Data Migration: Preserving Content and Meaning
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
Options for Long Term Data Retention
Proprietary v open standards for laboratory data
Options for long term retention:
Keep original system, Virtualisation, Data migration
Workshop: Justifying Long Term Solutions
Key Learning Points and Final Discussion
This course is part of the GMP Certification Programme "ECA Certified Data Integrity Manager" Learn more
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