Data Integrity Master Class with full-day pre-course session Raw Data including 8 Interactive Workshops

Data Integrity Master Class with full-day pre-course session Raw Data

Heidelberg, Germany

Seminar Nr. 18797

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

 

Unser Seminarservice

Kosten

ECA-Member*: EUR 2690,--
Non ECA Member*: EUR 2890,--
EU/GMP Inspectorates*: EUR 1445,--
APIC Member Discount*: EUR 2790,--

Alle Preise zzgl. MwSt. Wichtige Hinweise zur Umsatzsteuer.

Zur Anmeldung
* auch unkompliziert per Kreditkarte bezahlbar American Express Visa Mastercard

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

Sprecher

Bob McDowall, R.D.McDowall, UK
Yves Samson, Kereon, Switzerland
Dr Franz Schönfeld, GMP Inspector, Germany
Dr Wolfgang Schumacher, formerly F. Hoffmann-La Roche, Switzerland

Zielsetzung

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 expect 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

Hintergrund

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.

Zielgruppe

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".

Programm

Pre-course session "Raw Data - Understanding, Defining and Managing"
 
Tuesday, 29 August 2023
 
Data, Information and Knowledge
An overview presentation covering for production, laboratories and QA. Link to regulations e.g,
  • 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
  • ƒEU GMP Chapter 4 regulations – raw data principles outlined from a GMP perspective
Understanding GMP Definitions and Regulations for Raw Data
Currently there are many terms used in GMP regulations and data integrity guidance documents. What do they mean? How are they relevant to debate?  Definition and interpretation of
  • 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
Using a manufacturing process that is automated by standalone PLCs, PLCs linked to a SCADA system and an automated Manufacturing Execution System, what constitutes raw data will be outlined.
  • 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?
This brief presentation will start from the definitions of raw data and true copy and explore if and how a true copy can be considered raw data.
 
Workshop : What are Raw Data for Quality Decisions
 
 
Data Integrity Master Class
 
Wednesday, 30 August 2023
 
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
 
Thursday, 1 September 2023
 
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
 
Friday, 2 September 2023
 
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

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