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Index
Cover
Data Integrity and Data Governance: Practical Implementation in Regulated Laboratories
Preface
Acknowledgements
Glossary, Abbreviations and Data Integrity Terms
Contents
Chapter 1 - How to Use This Book and an Introduction to Data Integrity
1.1 Aims and Objectives
1.2 Structure of This Book
1.2.1 Chapter Structure
1.2.2 You Do Not Read the Regulations!
1.2.3 The Regulatory Environment
1.2.4 Data Governance
1.2.5 Data Integrity
1.2.6 Quality Oversight for Data Integrity
1.3 Mapping This Book to the Data Integrity Model
1.4 Pharmaceutical Quality System and Data Integrity
1.4.1 Integration Within the Pharmaceutical Quality System
1.4.2 No Chapter on Risk Management
1.4.3 Back to the Future 1: Understanding Current in cGMP
1.4.4 The European Equivalent of cGMP
1.5 What Is Data Integrity
1.5.1 How Many Definitions Would You Like
1.5.2 What Do These Definitions Mean
1.5.3 ALCOA+ Criteria for Integrity of Laboratory Data
1.6 Data Quality and Data Integrity
1.6.1 From Sample to Reportable Result
1.6.2 Contextual Metadata and a Reportable Result
1.6.3 Data Integrity – Can I Trust the Data
1.6.4 Data Quality – Can I Use the Data
1.6.5 The Proposed FDA GLP Quality System
1.6.6 Continual Versus Continuous Improvement
1.7 Static Versus Dynamic Data
1.8 Important Data Integrity Concepts
1.8.1 Data Integrity Is More than Just Numbers
1.8.2 Quality Does Not Own Quality Anymore
1.8.3 Data Integrity Is Not Just 21 CFR 11 or Annex 11 Compliance
1.8.4 Data Integrity Is an IT Problem
1.8.5 Data Integrity Is a Laboratory Problem
1.8.6 We Are Research – Data Integrity Does Not Impact Us
1.9 It’s Déjà vu all Over Again!
References
Chapter 2 - How Did We Get Here
2.1 Barr Laboratories 1993: You Cannot Test into Compliance
2.1.1 Background to the Court Case
2.1.2 Key Laboratory Findings from the Judgement
2.1.3 Regulatory Response
2.2 Able Laboratories 2005: You Cannot Falsify into Compliance
2.2.1 Background to the Inspection
2.2.2 483 Observations
2.2.3 Regulatory Response
2.3 Ranbaxy Warning Letters and Consent Decrees
2.3.1 Background to the Regulatory Action
2.3.2 Details of the 2012 Consent Decree
2.4 Court Case for GLP Data Falsification
2.5 Semler Research Data Falsification
2.6 The Cost of Data Integrity Non-compliance
2.6.1 Relative Costs of Compliance Versus Non-compliance
2.6.2 Is It Worth It
2.7 A Parcel of Rogues: FDA Laboratory Data Integrity Citations
2.7.1 Why Use Only FDA Warning Letters and 483 Observations
2.7.2 Quality Management System Failures
2.7.3 Instrument Citations
2.7.4 Citations for Lack of Laboratory Controls
2.7.5 Failure to Have Complete Laboratory Records
2.7.6 Too Much Data – Duplicate Record Sets
2.7.7 Industrial Scale Shredding and Discarding of GMP Documents
2.7.8 Responses by the Regulatory Authorities
References
Chapter 3 - The Regulators' Responses
3.1 What Do the Regulators Want
3.1.1 EU Good Manufacturing Practice Chapter 1
3.1.2 EU GMP Chapter 4 on Documentation
3.1.3 21 CFR 211 cGMP Regulations for Finished Pharmaceutical Goods
3.1.4 EU GMP Annex 11 on Computerised Systems
3.1.5 Regulatory Requirements Summary
3.2 The Proposed FDA GLP Quality System
3.2.1 Background to the Proposed Regulation
3.2.2 New Data Quality and Integrity Requirements
3.2.3 A New Data Integrity Role for the Study Director
3.2.4 The GLP Study Report
3.2.5 No Hiding Place for GLP Data Integrity Issues
3.3 Overview of Regulatory Guidance Documents for Data Integrity
3.4 Food and Drug Administration Guidance Documents
3.4.1 FDA Guide to Inspection of Pharmaceutical Quality Control Laboratories
3.4.2 FDA Compliance Program Guide 7346.832 on Pre Approval Inspections
3.4.3 FDA Level 2 Guidance
3.4.4 Delaying, Denying, Limiting or Refusing an FDA Inspection
3.4.5 FDA Guidance on Data Integrity and Compliance with cGMP
3.4.6 Key Points from the FDA Data Integrity Guidance
3.5 MHRA Data Integrity Guidance Documents
3.5.1 Initial Request to Industry December 2013
3.5.2 MHRA GMP Data Integrity Guidance for Industry
3.5.3 MHRA GXP Data Integrity Guidance for Industry
3.5.4 MHRA Definition of Raw Data
3.6 PIC/S Guidance Documents
3.6.1 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
3.7 WHO Guidance on Good Data and Records Management Practices
3.8 GAMP Guide for Records and Data Integrity
3.9 PDA Technical Report 80
3.9.1 Regulatory Trends for Data Integrity Issues
3.9.2 Data Integrity in Microbiology Laboratories
3.9.3 Data Integrity in Analytical QC Laboratories
3.9.4 How to Remediate Breaches in Data Integrity
3.10 Understanding the Meaning of Raw Data and Complete Data
3.10.1 Are Raw Data First-capture or Original Observations
3.10.2 In the Beginning …
3.10.3 Later, Much Later in Europe …
3.10.4 The GLP Quality System – The Proposed 21 CFR 58 Update
3.10.5 Extracting Principles for Laboratory GXP Raw Data
3.10.6 Visualising What Raw Data Mean
3.10.7 Summary: Raw Data Is the Same as Complete Data
3.11 Regulations and Data Integrity Guidance Summary
References
Chapter 4 - What Is Data Governance
4.1 What Do the Regulators Want
4.1.1 EU GMP Chapter 1 Pharmaceutical Quality System
4.1.2 FDA Proposed GLP Quality System Update
4.1.3 MHRA GXP Data Integrity Guidance
4.1.4 WHO Guidance on Good Records and Data Management Practices
4.1.5 PIC/S PI-041 – Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
4.1.6 EMA Questions and Answers on Good Manufacturing Practice – Data Integrity
4.1.7 Summary of Regulatory Guidance
4.2 The Rationale for Data Governance: Regulatory Boot or Business Imperative
4.3 Perspectives of Data Governance Outside the Pharmaceutical Industry
4.4 Key Data Governance Elements
4.4.1 Summary of Regulatory Guidance for Data Governance
4.4.2 Main Data Governance Areas
4.4.3 Further Data Governance Chapters in this Book
References
Chapter 5 - A Data Integrity Model
5.1 A Data Integrity Model
5.1.1 A Logical Organisation of Data Integrity Elements
5.1.2 Descriptions of the Four Levels in the Model
5.1.3 An Analogy of Building a House
5.1.4 Focus on the Laboratory Levels of the Data Integrity Model
5.2 Foundation Level: The Right Corporate Culture for Data Integrity
5.2.1 Role of Senior Management
5.2.2 Data Governance Functions in the Foundation Level
5.3 Level 1: The Right Analytical Instrument and Computer System for the Job
5.3.1 Analytical Instrument Qualification and Computerised System Validation (AIQ and CSV)
5.3.2 Data Governance Functions in Level 1
5.4 Level 2: The Right Analytical Procedure for the Job
5.4.1 Validation of Analytical Procedures
5.4.2 Verification of Pharmacopoeial Methods
5.4.3 Bioanalytical Method Validation Guidance
5.4.4 Manual Analytical Procedures Must Be Designed for Data Integrity
5.5 Level 3: Right Analysis for the Right Reportable Result
5.6 Quality Oversight for Data Integrity
5.6.1 Quality Oversight of Laboratory Procedures and Work
5.6.2 Data Integrity Audits
5.6.3 Data Integrity Investigations
5.7 Linking the Data Integrity Model to the Analytical Process
5.7.1 The Data Integrity Model in Practice
5.7.2 Quality Does Not Own Quality Anymore
5.8 Mapping the WHO Guidance to the Data Integrity Model
5.9 Assessment of Data Integrity Maturity
5.9.1 Data Management Maturity Model
5.9.2 Data Integrity Maturity Model
References
Chapter 6 - Roles and Responsibilities in a Data Governance Programme
6.1 What Do the Regulators Want
6.1.1 ICH Q10 Pharmaceutical Quality Systems
6.1.2 EU GMP Chapter 1
6.1.3 PIC/S-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
6.1.4 WHO Guidance on Good Data and Record Management Practices
6.1.5 Update of the US GLP Regulations
6.1.6 GAMP Guide Records and Data Integrity
6.1.7 A Summary of Regulatory and Industry Guidance Documents
6.2 Data Governance Roles and Responsibilities – Corporate Level
6.3 Data Integrity Policy
6.4 Management, Monitoring and Metrics
6.5 Data Integrity and Data Governance Roles and Responsibilities – Process and System Level
6.5.1 From Data Governance to Data Ownership
6.5.2 Process Owner and System Owner
6.5.3 Can a Process Owner Be a Data Owner
6.5.4 Other Data Governance Roles at the System Level
6.5.5 Data Owner
6.5.6 Data Steward
6.5.7 Is a Lab Administrator a Data Steward
6.5.8 Is a Technology Steward a System Owner
6.5.9 Segregation of Roles and Duties
6.6 The Short Straw ...…
6.6.1 Where Are We Now
6.6.2 The Hybrid System Nightmare
6.7 Cascade of Roles and Responsibilities: from Boardroom to Bench
References
Chapter 7 - Data Integrity Policies, Procedures and Training
7.1 What Do the Regulators Want
7.1.1 EU GMP Chapter 4 on Documentation
7.1.2 WHO Guidance on Good Data and Record Management Practices
7.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
7.1.4 Regulatory Requirements Summary
7.2 Environmental Analysis and an Approach to Data Integrity
7.2.1 Background to EPA and Data Integrity
7.2.2 NELAC and Laboratory Accreditation
7.2.3 NELAC Quality System
7.2.4 NELAC Data Integrity Training
7.3 Corporate Data Integrity Policy Coupled with Effective Training
7.3.1 Contents of a Corporate Data Integrity Policy
7.3.2 Training in the Data Integrity Policy
7.3.3 Agreeing to Comply with the Policy
7.4 Suggested Data Integrity Procedures
7.5 Principles of Good Documentation Practice
7.5.1 Say What You Do
7.5.2 Do What You Say
7.5.3 Document It
7.5.4 Automating Procedure Execution
7.6 Training to Collect and Manage Raw Data and Complete Data
7.6.1 Principles for GXP Laboratory Raw Data and Complete Data
7.6.2 Approach to Training for Complete and Raw Data in the Laboratory
7.6.3 Example 1 – Paper Records from a Manual Test
7.6.4 Example 2 – Spectroscopic Analysis Using a Hybrid System
7.6.5 Example 3 – Chromatographic Analysis with a CDS Interfaced with a LIMS
7.6.6 Additional Raw Data
7.7 Good Documentation Practice for Paper Records
7.7.1 Recording Observations and Results
7.7.2 Examples of Good and Poor Documentation Practice for Handwritten Records
7.7.3 Fat Finger, Falsification and Fraud – Take 1
7.7.4 Original Records and True Copies
7.8 Good Documentation Practice for Hybrid Records
7.8.1 Record Signature Linking for Hybrid Systems – Spreadsheet Example
7.9 Good Documentation Practice for Electronic Records
7.9.1 Good Documentation Practice for Electronic Records
7.10 Good Documentation Practice Training
7.11 Role of the Instrument Log Book
7.11.1 EU GMP Chapter 4 on Documentation
7.11.2 FDA Good Laboratory Practice 21 CFR 58
7.11.3 FDA 21 CFR 211 cGMP for Finished Pharmaceutical Products
7.11.4 FDA Inspection of Pharmaceutical QC Laboratories
7.11.5 Instrument Lag Books in Practice
7.12 Training for Generating, Interpreting and Reviewing Laboratory Data
7.12.1 Data Integrity Training for a Chromatography Data System: Operational SOPs
7.12.2 Training Is of Little Value without an Open Culture
References
Chapter 8 - Establishing and Maintaining an Open Culture for Data Integrity
8.1 What Do the Regulators Want
8.1.1 WHO Guidance on Good Data and Record Management Practices
8.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
8.1.3 MHRA “GXP” Data Integrity Guidance and Definitions
8.1.4 Regulatory Guidance Summary
8.2 Bad Culture: Cressey's Fraud Triangle and Organisational Pressure
8.2.1 Cressey's Fraud Triangle
8.2.2 Breaking the Fraud Triangle
8.2.3 Managerial and Peer Pressures Can Influence Analytical Results
8.3 ISPE Cultural Excellence Report
8.4 Management Leadership
8.4.1 Generate and Communicate the Data Integrity Vision
8.4.2 Talk the Talk and Walk the Walk
8.4.3 Reinforcing an Open Culture for Data Integrity
8.4.4 FDA Expectations for Analysts
8.5 Mind Set and Attitudes
8.5.1 Quality Does Not Own Quality Anymore
8.5.2 The Iceberg of Ignorance
8.5.3 How Do I Raise Problems to Management
8.6 Gemba Walks
8.6.1 Where Does a Gemba Walk Fit in a QMS
8.6.2 What Gemba Walks Are and Are Not
8.6.3 Why Bother with a Gemba Walk
8.6.4 Activation Energy for a Gemba Walk
8.6.5 Performing the Gemba Walk
8.6.6 Keep the Focus on the Process
8.6.7 Generic Questions for a Gemba Walk
8.6.8 Let Management See Analytical Instruments First Hand
8.7 Fat Finger, Falsification and Fraud – Take 2
8.7.1 To Err Is Human
8.7.2 Verification of Data Entry
8.7.3 What Is the Fat Finger Rate in a Laboratory
8.7.4 Learning from Health Service Studies
8.8 Maintaining the Open Culture
References
Chapter 9 - An Analytical Data Life Cycle
9.1 What Do the Regulators Want
9.1.1 MHRA GXP Data Integrity Guidance
9.1.2 WHO Guidance on Good Data and Record Management Practices
9.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
9.1.4 Regulatory Requirements Summary
9.2 Published Data Life Cycles
9.2.1 GAMP Guide on Records and Data Integrity
9.2.2 Validation of Chromatography Data Systems
9.2.3 Critique of the Two Life Cycle Models
9.3 An Analytical Data Life Cycle
9.3.1 Overview of an Analytical Data Life Cycle
9.3.2 Controlling the Analytical Data Life Cycle
9.3.3 Phases of the Analytical Data Life Cycle
9.3.4 Generic Data Life Cycles Do Not Work in the Laboratory
9.3.5 The Requirement for Flexibility to Adapt to Different Analytical Procedures
9.4 Establishing Data Criticality and Inherent Integrity Risk
9.4.1 Spectrum of Analytical Instruments and Laboratory Computerised Systems
9.5 Risks to Data Over the Data Life Cycle
9.5.1 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
9.5.2 Initial Assessment of Risk of the Analytical Data Life Cycle Phases
9.5.3 Phases of the Data Life Cycle are Equal but Some are More Equal than Others
9.5.4 Summary Risks in the Analytical Data Life Cycle
References
Chapter 10 - Assessment and Remediation of Laboratory Processes and Systems
10.1 What Do the Regulators Want
10.1.1 WHO Guidance on Good Data and Record Management Practices
10.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
10.1.3 MHRA GXP Data Integrity Guidance and Definitions
10.1.4 Regulatory Guidance Summary
10.2 Business Rationale for Assessment and Remediation
10.2.1 Improve Business Processes
10.2.2 Ensure Regulatory Compliance
10.2.3 Release Product Earlier
10.2.4 The Problem is Management
10.3 Current Approaches to System Assessment and Remediation
10.3.1 The Rationale for Current Approaches
10.3.2 Assessment of Validated Computerised Systems
10.4 Data Process Mapping
10.4.1 The Problem with Checklists
10.4.2 What is Data Process Mapping
10.4.3 Instrument Data System with Spreadsheet Calculations
10.4.4 Spreadsheets Used for GMP Calculations Are High Risk
10.4.5 Critical Activities in a Process
10.4.6 Fix and Forget versus Delivering Business Benefits
10.4.7 Short Term Remediation Leading to Long Term Solution
10.5 Data Integrity Issues with Analysis by Observation
10.5.1 Potential Problems with Analysis by Observation
10.5.2 A Risk Based Approach to Analysis by Observation
10.5.3 Melting Point Determination
10.6 Data Integrity Issues with Paper Records
10.6.1 Blank Forms Must be Controlled with Accountability
References
Chapter 11 - Data Integrity and Paper Records: Blank Forms and Instrument Log Books
11.1 What Do the Regulators Want – Blank Forms
11.1.1 Focus on the Key Data Integrity Issues with Paper Records
11.1.2 FDA Guide to Inspection of Quality Control Laboratories
11.1.3 MHRA GMP Data Integrity Guidance
11.1.4 MHRA Draft GXP Data Integrity Guidance
11.1.5 MHRA GXP Data Integrity Guidance and Definitions
11.1.6 WHO Guidance on Good Data and Record Management Practices
11.1.7 FDA Data Integrity and Compliance with cGMP
11.1.8 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
11.1.9 EMA GMP Questions and Answers on Data Integrity
11.1.10 Regulatory Guidance Summary
11.2 Control of Master Templates and Blank Forms
11.2.1 Understanding Master Templates and Blank Forms
11.2.2 Requirements for the Design, Approval and Storage of Master Templates
11.2.3 Process for Generation, Review and Approval of a Master Template
11.2.4 Requirements for the Issue and Reconciliation of Blank Forms
11.2.5 Process for Issue and Reconciliation of Blank Forms
11.2.6 Process for Issue and Reconciliation of Blank Forms
11.2.7 Completing Blank Forms and Creating GXP Records
11.3 What Do the Regulators Want – Instrument Log Books
11.3.1 EU GMP Chapter 4 on Documentation
11.3.2 FDA GMP 21 CFR 211
11.3.3 FDA Good Laboratory Practice 21 CFR 58
11.3.4 OECD GLP Regulations
11.3.5 Summary of Regulatory Requirements for an Instrument Log Book
11.4 The Role of an Instrument Log Book for Ensuring Data Integrity
11.4.1 Why is an Instrument Log Book Important
11.4.2 What Needs to be Entered in the Log Book
11.4.3 Inspectors Know the Importance of an Instrument Log
11.4.4 FDA Citations for Laboratory Log Books
11.4.5 Instrument Log Books in Practice
11.5 Role of the Instrument Log Book in the Second Person Review
11.5.1 Is an Instrument Performing OK
11.6 Automating Blank Forms and Instrument Log Books
11.6.1 Automating Master Templates and Blank Forms
11.6.2 Instrument Log Book
Acknowledgements
References
Chapter 12 - The Hybrid System Problem
12.1 What Do the Regulators Want
12.1.1 Electronic Records and Electronic Signatures Regulations (21 CFR 11)
12.1.2 WHO Guidance on Good Data and Record Management Practices
12.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
12.1.4 EU GMP Chapter 4 on Documentation
12.1.5 FDA Guidance for Industry Data Integrity and cGMP Compliance
12.1.6 FDA Level 2 Guidance for Records and Reports
12.1.7 Regulatory Summary
12.2 What Is a Hybrid System
12.2.1 WHO Definition of a Hybrid System
12.2.2 Key Features of a Hybrid System
12.3 The Core Problems of Hybrid Systems
12.3.1 A Typical Hybrid System Configuration
12.3.2 File Organisation and Printing Results
12.3.3 Synchronising Paper Printouts and Electronic Records
12.3.4 A Simple Way to Reduce Paper with Hybrid Systems
12.4 Eliminate Hybrid Systems
References
Chapter 13 - Get Rid of Paper: Why Electronic Processes are Better for Data Integrity
13.1 What Do the Regulators Want
13.1.1 WHO Guidance on Good Data and Record Management Practices
13.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
13.1.3 EU GMP Annex 11 Computerised Systems
13.1.4 Regulatory Summary
13.2 Why Bother with Paper
13.2.1 Tradition – Why Change Our Approach
13.2.2 Back to the Future 2: Understanding the Current in cGMP
13.2.3 The Pharmaceutical Industry is a Two Sigma Industry
13.2.4 Are the Regulations Part of the Data Integrity Problem
13.2.5 Is Paper a Realistic Record Medium Now
13.3 Design Principles for Electronic Working
13.4 Designing Data Workflows 1 – Analytical Balances
13.4.1 Weighing a Reference Standard or Sample
13.4.2 Recording a Weight by Observation
13.4.3 Recording Balance Weights with a Printer
13.4.4 Connecting the Balance to an Instrument Data System
13.5 Designing Data Workflows 2 – Chromatography Data Systems and LIMS
13.5.1 Options for Interfacing
13.5.2 Manual Data Transfer Between CDS and LIMS
13.5.3 Unidirectional Interfacing from CDS to LIMS
13.5.4 Bidirectional Interfacing Between CDS and LIMS
13.6 Impact on Data Integrity and Second Person Review
13.6.1 Ensuring Data Integrity with Electronic Working
13.6.2 Impact on Second Person Review
13.6.3 Summary of an Approach for Electronic Working that Ensures Data Integrity
References
Chapter 14 - Data Integrity Centric Analytical Instrument Qualification and Computerised System Validation
14.1 What the Regulators Want
14.1.1 21 CFR 211 Current GMP for Finished Pharmaceutical Products
14.1.2 21 CFR 58 GLP for Non-clinical Studies
14.1.3 United States Pharmacopoeia ၘ on Analytical Instrument Qualification
14.1.4 EU GMP Annex 11
14.1.5 ICH Q7 and EU GMP Part 2: Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients
14.1.6 WHO Guidance on Good Data and Record Management Practices
14.1.7 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
14.1.8 Regulatory Summary
14.2 GMP Regulations and the Pharmacopoeias
14.2.1 Relationship Between GMP and the Pharmacopoeias
14.2.2 Importance of USP ၘ
14.2.3 Use the USP ၘ Principles for GLP Instruments and Systems
14.3 Why Is Instrument Qualification Important
14.3.1 Data Quality Triangle
14.3.2 Data Integrity Model
14.4 Why a New Revision of USP ၘ
14.4.1 Problems with the 2008 Version
14.4.2 Revision Path of USP ၘ
14.5 What Has Changed with USP ၘ
14.5.1 Differences Between the Old and New Versions of USP ၘ
14.5.2 Omitted Sections in the New Version
14.5.3 Additions and Changes to USP ၘ
14.5.4 Roles and Responsibilities
14.5.5 An Updated 4Qs Model
14.5.6 Harmonisation of Qualification Approaches
14.6 Importance of the Laboratory URS for Analytical Instruments
14.6.1 Role of the URS
14.6.2 Understand Your Intended Use
14.6.3 A Role of the Supplier: Write Meaningful Specifications
14.6.4 How Minimal Is Minimal
14.6.5 Do Not Forget the Software!
14.6.6 Purchasing a Second Instrument
14.6.7 It's all About Investment Protection
14.7 Software Validation Changes to USP ၘ
14.7.1 Improving the Analytical Process
14.7.2 A Validated System with Vulnerable Records Means Data Integrity Problems
14.7.3 Change the Validation Approach to Ensure Data Integrity
14.7.4 Brave New CSV World
14.7.5 Turning Principles into Practice
14.7.6 Qualified, Validated and Released for Operational Use
14.8 Performance Qualification
14.8.1 Changes to USP ၘ and the Impact on Understanding of PQ
14.8.2 Linking the URS, OQ, and PQ
14.8.3 PQ for Group A Instruments
14.8.4 PQ for Group B Instruments
14.8.5 PQ for Group C Instruments
14.8.6 System Suitability Tests as Part of a PQ
14.8.7 Keep It as Simple as Possible – But No Simpler
14.8.8 Holistic HPLC PQ Test
Acknowledgement
References
Chapter 15 - Validating Analytical Procedures
15.1 What the Regulators Want
15.1.1 US GMP 21 CFR 211
15.1.2 EU GMP Chapter 6 on Quality Control
15.1.3 EU GMP Annex 15: Qualification and Validation
15.1.4 Bioanalytical Method Validation Guidances
15.1.5 Regulatory Requirements Summary
15.1.6 Outsource Analytical Work with Care
15.2 Current Method Validation Guidance
15.2.1 Terminology: Analytical Method or Analytical Procedure
15.2.2 Business Rationale for Procedure Validation/Verification
15.2.3 ICH Q2(R1) Validation of Analytical Procedures: Text and Methodology
15.2.4 FDA Guidance for Industry on Analytical Procedure Validation
15.2.5 Update of ICH Q2(R1) to a Life Cycle Approach
15.2.6 Pharmacopoeial Methods Do Not Work as Written
15.3 Role of Analytical Procedure Validation in Data Integrity
15.3.1 Method Validation in the Data Integrity Model
15.3.2 Equating the Data Integrity Model with the USP ၘ Data Quality Triangle
15.4 Current Approaches to Validation and Verification of Procedures
15.4.1 Good Manufacturing Practice
15.4.2 Bioanalytical Method Validation
15.4.3 Validation Documentation for Analytical Procedures
15.4.4 Validation Parameters
15.5 Overview of the Life Cycle of Analytical Procedures
15.5.1 USP ሠ and Stimuli to the Revision Process
15.5.2 Life Cycle of Analytical Procedures
15.6 Defining the Analytical Target Profile (ATP)
15.6.1 Specification for an Analytical Procedure
15.6.2 Advantages and Limitations of an Analytical Target Profile
15.7 Stage 1: Procedure Design and Development
15.7.1 Overview
15.7.2 Information Gathering and Initial Procedure Design
15.7.3 Iterative Method Development and Method Optimisation
15.7.4 Risk Assessment and Management
15.7.5 Analytical Control Strategy: Identifying and Controlling Risk Parameters
15.7.6 Procedure Development Report
15.8 Stage 2: Procedure Performance Qualification
15.8.1 Planning the Validation
15.8.2 Validation Report
15.8.3 Analytical Procedure Transfer
15.9 Stage 3: Procedure Performance Verification
15.9.1 Routine Monitoring of Analytical Performance
15.9.2 Changes to an Analytical Procedure
15.9.3 Validated Analytical Procedure
References
Chapter 16 - Performing an Analysis
16.1 What the Regulators Want
16.1.1 EU GMP Chapter 1 Pharmaceutical Quality System
16.1.2 US GMP 21 CFR 211 GMP for Finished Pharmaceutical Products
16.1.3 FDA Guide for Inspection of Pharmaceutical Quality Control Laboratories
16.2 The Analytical Process
16.2.1 Linking the Data Integrity Model to the Analytical Process
16.2.2 Process Overview
16.2.3 Analytical Instruments Are Qualified and/or Validated
16.2.4 System Suitability Tests and Point of Use Checks
16.3 The Scope of Analytical Procedures
16.4 Sampling and Sample Management
16.4.1 What the Regulators Want
16.4.2 Sampling Is Critical
16.4.3 GMP Sample Plan and Sampling
16.4.4 GLP Protocol and Sampling
16.4.5 Ensure Correct Sample Labelling
16.4.6 Transport to the Laboratory
16.4.7 Sample Receipt and Storage
16.4.8 Sample Collection Best Practice
16.5 Reference Standards and Reagents
16.5.1 What the Regulators Want
16.5.2 Preparation of Reference Standards and Solutions
16.5.3 Sweep Under the Carpet or Own Up to a Mistake
16.5.4 What Is the FDA's View of Analyst Mistakes
16.6 Sample Preparation
16.6.1 What the Regulators Want
16.6.2 Sample Preparation Current Practices
16.6.3 Automate Where Technically Feasible
16.7 Recording Data by Observation
16.7.1 Typical Tests Recording Results by Observation
16.7.2 Instruments with No Printer or Data Transfer Capability
16.7.3 Pharmacopoeial Indicator Tests
16.8 Sample Preparation Followed by Instrumental Analysis Methods
16.8.1 An Illustrative Analytical Procedure
16.8.2 Ensuring Data Integrity
16.8.3 Consider Alternate Analytical Approaches
16.9 Methods Involving Instrumental Analysis and Data Interpretation
16.9.1 What the Regulators Want
16.9.2 Near Infra-red (NIR) Identity Testing
16.9.3 Building a Spectral Library
16.9.4 Performing the Analysis
16.10 Chromatographic Analysis and CDS Data Interpretation
16.10.1 What the Regulators Want
16.10.2 Setting Up the Chromatograph and Acquiring Data
16.10.3 Entering Factors, Weights, and Other Assay Values into the Sequence File
16.10.4 An Alternate Approach to Weights and Factors
16.10.5 System Evaluation Injections
16.10.6 System Suitability Tests – What the Regulators Want
16.10.7 Integrating Chromatograms
16.10.8 General Principles for Ensuring Good Chromatographic Integration
16.10.9 SOP for Integration of Chromatograms
16.10.10 Bioanalytical Guidance for Integration of Chromatograms
16.10.11 Incomplete (Aborted) Runs
16.10.12 Other Unplanned Injections
16.10.13 Data Storage Locations
16.10.14 Chromatography Falsification Practices 1: Peak Shaving and Enhancing
16.10.15 Chromatography Falsification Practices 2: Inhibiting Integration
16.10.16 Chromatography Falsification Practices 3: Integrating Samples First
16.11 Calculation of Reportable Results
16.11.1 What the Regulators Want
16.11.2 General Considerations for Calculations
16.11.3 Avoid Using Spreadsheets for Analytical Calculations Whenever Possible
16.11.4 Calculation of Reportable Results and Out of Specification Results
16.11.5 Completion of Testing
Acknowledgement
References
Chapter 17 - Second Person Review
17.1 What Do the Regulators Want
17.1.1 cGMP for Finished Pharmaceutical Products (21 CFR 211)
17.1.2 EU GMP Chapter 6 Quality Control
17.1.3 EU GMP Annex 11
17.1.4 MHRA GXP Data Integrity Guidance and Definitions
17.1.5 FDA Guidance on Data Integrity and cGMP Compliance
17.1.6 WHO Guidance on Good Data and Record Management Practices
17.1.7 Regulatory Compliance Summary
17.2 What the Regulators Want: Out of Specification (OOS) Results
17.2.1 21 CFR 211
17.2.2 EU GMP Chapter 6 Quality Control
17.2.3 FDA Guidance for Industry on Investigating OOS Test Results
17.2.4 FDA Guidance on Quality Metrics
17.2.5 OOS Definitions
17.2.6 OOS Regulatory Summary
17.3 Procedures for the Second Person Review
17.3.1 Who Should Conduct a Second Person Review
17.3.2 The Scope of the Procedure
17.3.3 The Troika of Record Review
17.3.4 Timeliness of the Second Person Review
17.3.5 Documenting the Audit Trail Review
17.3.6 Training for Second Person Review
17.3.7 Out of Specification (OOS) Procedure
17.4 Second Person Review of Analytical Procedures Involving Observation
17.4.1 What Is an Analytical Procedure Involving Observation
17.4.2 Improving Manual Analytical Procedures
17.4.3 Witness Testing or Second Person Review
17.5 Sample Preparation and Instrumental Analysis
17.5.1 Loss on Drying Analysis
17.5.2 Review of the Second Person Review of the Analytical Records
17.6 Second Person Review of a Hybrid System Records
17.6.1 Increased Scope of Record and Data Review
17.6.2 Technical Versus Procedural Controls for Second Person Review
17.6.3 The Scope of an Analytical Procedure Involving a Hybrid System
17.6.4 Technical Controls to Aid a Second Person Review
17.6.5 Paper and Electronic Records to be Reviewed
17.6.6 Recording the Work Performed and the Review
17.6.7 Original Record or True Copy
17.6.8 Have Critical Data Been Entered into the Instrument Data System
17.6.9 Review of Electronic Records, Metadata and Audit Trail
17.6.10 Second Person Review to Ensure Data Have Not Been Falsified
17.6.11 Do You Really Want to Work This Way
17.7 Risk Based Audit Trail Review
17.7.1 MHRA GXP Data Integrity Guidance and Definitions
17.7.2 Which Audit Trail Should Be Reviewed
17.7.3 How Regular Is a Regular Review of Audit Trail Entries
17.8 Second Person Review of Electronic Systems and Data
17.8.1 LIMS Interfaced with a CDS
17.8.2 A Second Person Review Is Process Not System Centric
17.9 Recording and Investigating Out of Specification Results
17.9.1 Phase 1: Initial OOS Laboratory Investigation
17.9.2 Phase 2A Production
17.9.3 Phase 2B Additional Laboratory Testing
17.9.4 OOS Investigations: Prevention Is Better than the Cure
References
Chapter 18 - Record Retention
18.1 What Do the Regulators Want
18.1.1 WHO Guidance on Good Data and Record Management Practices
18.1.2 EU GMP Annex 11
18.1.3 GLP Regulations: 21 CFR 58
18.1.4 US GMP Regulations: 21 CFR 211
18.1.5 21 CFR 11 Requirements
18.1.6 MHRA GXP Data Integrity Guidance and Definitions
18.1.7 FDA Guidance on Data Integrity and cGMP Compliance
18.1.8 EU GMP Chapter 4 Documentation
18.1.9 FDA Guidance for Industry Part 11 – Scope and Application Guidance
18.1.10 FDA Inspection of Pharmaceutical Quality Control Laboratories
18.1.11 OECD GLP Regulations
18.1.12 OECD GLP Guidance on Application of GLP to Computerised Systems
18.1.13 Regulatory Requirements Summary
18.2 Laboratory Data File Formats and Standards
18.2.1 JCAMP-DX Data Format for Spectroscopy
18.2.2 Current CDS Data Standards
18.2.3 Progress Towards Universal Data File Formats
18.3 Options for Electronic Records Retention and Archive
18.3.1 Backup Is Not Archive (Unless You Are the FDA)
18.3.2 Organising Electronic Records to Retain
18.3.3 Options for Electronic Archive
18.3.4 Can I Read the Records
18.3.5 Impact of a Changed Data System File Format
18.3.6 Selection of Off-line Archive Media
18.3.7 Changing the Instrument Data System – What Are the Archive Options
18.3.8 Overview of Some Options
18.3.9 Assessment of Option Feasibility
18.4 OECD Guidance for Developing an Electronic Archive
18.4.1 Definitions
18.4.2 Roles and Responsibilities
18.4.3 Archive Facilities
18.4.4 Archiving Electronic Records
References
Chapter 19 - Quality Metrics for Data Integrity
19.1 What Do the Regulators Want
19.1.1 EU GMP Chapter 6 Quality Control
19.1.2 FDA Quality Metrics Guidance for Industry
19.1.3 WHO Guidance on Good Data and Record Management Practices
19.1.4 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
19.1.5 MHRA GXP Data Integrity Guidance and Definitions
19.1.6 Regulatory Guidance Summary
19.2 KPIs and Metrics for the Laboratory
19.2.1 Understanding Laboratory Metrics
19.2.2 Metrics Must Be Generated Automatically
19.2.3 Why Metrics for Data Integrity
19.2.4 Do Quality Metrics Lead Behaviour
19.2.5 Are Incidents Hidden Metrics
19.3 Data Integrity Metrics in an Organisation
19.3.1 Overview: Start Small and Expand
19.3.2 Scope of the Organisation
19.3.3 Some Suggested Data Integrity Metrics
19.4 DI Policies, Assessment and Remediation of Processes and Systems
19.4.1 Data Integrity Policy and Associated Procedures
19.4.2 Assessment of Processes and Systems
19.4.3 Executed Remediation Plans
19.5 Laboratory Data Integrity Metrics
19.5.1 Some Preliminary Considerations for Laboratory Data Integrity Metrics
19.5.2 Outsourced Laboratory Testing
19.6 Quality Assurance DI Metrics
19.7 Management Review of DI Metrics
19.7.1 Management Are Responsible for Data Integrity and the PQS
19.7.2 How Regular Is Regular Review
Acknowledgement
References
Chapter 20 - Raising Data Integrity Concerns
20.1 What Do the Regulators Want
20.1.1 WHO Guidance on Good Data and Record Management Practices
20.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
20.1.3 NELAC Quality Standard
20.1.4 Regulatory Guidance Summary
20.2 Data Integrity Problem or Concern
20.3 What Is Needed to Raise a Data Integrity Concern
20.3.1 A Section in the Corporate Data Integrity Policy
20.3.2 Communicate and Train How to Raise Data Integrity Concerns
20.3.3 Raising a Concern or Airing a Grievance
20.3.4 What Should Be Reported
20.3.5 Protecting the Whistleblower
20.3.6 Confidentiality
20.3.7 Raising Concerns Anonymously
20.4 Raising a Concern
20.4.1 Who Should You Raise Your Concern with
20.4.2 How to Raise a Concern
20.4.3 Raise an Issue via Management or Quality Assurance
20.4.4 What the Organisation Must Do
20.4.5 What If the Company Is the Problem
References
Chapter 21 - Quality Assurance Oversight for Data Integrity
21.1 What Do the Regulators Want
21.1.1 EU GMP Chapter 9 Self-inspections
21.1.2 US GMP 21 CFR 211 Current Good Manufacturing Practice for Finished Pharmaceutical Products
21.1.3 FDA Compliance Program Guide 7346.832 for Pre-approval Inspections
21.1.4 21 CFR 58 Good Laboratory Practice for Non-clinical Laboratory Studies
21.1.5 MHRA GXP Data Integrity Guidance and Definitions
21.1.6 WHO Guidance on Good Data and Record Management Practices
21.1.7 PIC/S-PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
21.1.8 Regulatory Compliance Summary
21.1.9 Role of the Laboratory in Ensuring Data Integrity
21.2 Data Integrity Audits: Planning and Execution
21.2.1 Rationale for Data Integrity Audits
21.2.2 What Are the Objectives of a Laboratory Data Integrity Audit
21.2.3 What Will We Audit The Data Integrity Inventory and Data Criticality
21.2.4 What Is the Order and Frequency of Audit
21.2.5 Who Will Conduct the Audit
21.2.6 Data Integrity Audits and Periodic Reviews of Computerised Systems
21.2.7 Procedure and Checklist for a Data Integrity Audit
21.3 Conducting a Laboratory Data Integrity Audit
21.3.1 Relationship Between the Data Integrity Model and a Data Integrity Audit
21.3.2 Overview of the Analytical Process for a Laboratory Data Integrity Audit
21.3.3 Expectations for Laboratory Records
21.3.4 Auditing Records and Data from Sampling to Report
21.3.5 Checking the Configuration Settings of Computerised Systems
21.3.6 Identification and Investigation of Laboratory Out of Specification Results
21.3.7 Photographs to Support Audit Observations and Findings
21.3.8 Reporting the Audit
21.4 What Is a Forensic Approach to Data Checking
21.4.1 Forensic Data Analysis
21.4.2 Recovery of Deleted Files
21.4.3 Forensic Data Analysis Techniques
21.5 Triggers for a Data Integrity Investigation
References
Chapter 22 - How to Conduct a Data Integrity Investigation
22.1 What the Regulators Require
22.1.1 WHO Guidance on Good Data and Record Management Practices
22.1.2 FDA Guidance on Data Integrity and Compliance with CGMP
22.1.3 FDA Application Integrity Policy
22.1.4 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
22.1.5 Summary of Data Investigation Regulations and Guidance
22.2 Case Study 1: Software Error Investigation
22.2.1 Case Study 1 Background
22.2.2 Sequester a Copy of the System and the Data
22.2.3 Temporary Resolution of the Problem
22.2.4 Systems Approach to the Issue
22.2.5 Time Frame of the Potential Data Integrity Vulnerability
22.2.6 Investigating the Impacted Database
22.2.7 Informing Regulatory Authorities
22.3 Case Study 2: Data Falsification Investigation
22.3.1 Case Study Background
22.3.2 Meeting the Intent of the Application Integrity Policy
22.3.3 Scope of the Data Integrity Investigation
22.3.4 Approaches to the Investigation of Laboratory Data Integrity Issues
22.3.5 Do Not Just Focus on Data Integrity Violations – Look Also for Poor Practices
22.3.6 Investigation of Tests Using Observation
22.3.7 Investigation of Simple Analytical Testing
22.3.8 Investigation of Analytical Testing by Chromatography
22.3.9 Staff Interviews
22.3.10 Findings and Their Classification
22.3.11 Root Cause of Data Integrity and Poor Data Management Practices
22.3.12 Assessment of Material Impact
22.3.13 CAPA Plans: Short-term Remediation and Long-term Solutions
22.4 Summary
References
Chapter 23 - Data Integrity and Outsourcing
23.1 What the Regulators Want
23.1.1 WHO Guidance on Good Data and Record Management Practices
23.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
23.1.3 Regulatory Guidance Summary
23.2 Cetero Research Laboratories Data Falsification Case
23.3 Include Data Integrity in Supplier Assessment/Audit
23.3.1 Current Approaches to Laboratory Audit
23.3.2 Extending Assessment to Include Data Integrity
23.4 Initial Data Integrity Assessment of a Facility
23.4.1 Initial Selection of the Contract Laboratory
23.4.2 Do Not Forget the Scientific and Technical Competence of the Supplier
23.4.3 Request for Pre-audit Information
23.4.4 Planning the Audit
23.4.5 Data Governance and Data Integrity in the Context of a PQS
23.4.6 Investigate Electronic Record Controls
23.4.7 Conclusion of the Audit
23.5 Agreements and Contracts for Data Integrity
23.5.1 Main Data Integrity Contractual Responsibilities
23.5.2 Using the Same Chromatography Data System
23.5.3 Storage of the Records Generated
23.6 On-going Monitoring of Work and Audits
23.6.1 Risk Based Approaches to Monitoring
23.6.2 Monitoring the Results
23.6.3 Remote Assessment of Work Packages
23.6.4 On-site Audits
23.6.5 Contract Analytical Work with Your Eyes Open
References
Chapter 24 - Data Integrity Audit Aide Memoire
24.1 What the Regulators Want
24.1.1 EU GMP Chapter 9 Self-inspections
24.1.2 Data Integrity Guidances for Audits
24.1.3 Regulatory Requirements Summary
24.2 Audit Aide Memoire for the Foundation Layer: Data Governance
24.2.1 Management Leadership for Data Integrity
24.2.2 Corporate Data Integrity and Ethics Policy
24.2.3 Data Integrity Training
24.2.4 Data Ownership for Computerised Systems
24.2.5 Data Ownership for Manual Processes
24.2.6 Establishment and Maintenance of an Open Culture
24.3 Audit Aide Memoire for Level 1: AIQ and CSV
24.3.1 Overview
24.3.2 Analytical Instrument Qualification
24.3.3 Computerised System Validation
24.3.4 Validating Interfaces Between Computerised Systems
24.4 Audit Aide Memoire for Level 2: Analytical Procedure Validation Life Cycle
24.4.1 Procedure Design (Method Development)
24.4.2 Analytical Procedure Performance Qualification (Method Validation)
24.4.3 Method Application: Control and Monitoring
24.5 Level 3: Study and Batch Analysis Data Integrity Aide Memoire
24.5.1 Routine Analysis Data Integrity Aide Memoire
24.5.2 Audit of Paper Analytical Records
24.5.3 Audit of Hybrid Laboratory Computerised Systems
24.5.4 Validation and Use of a Spreadsheet
24.5.5 Chromatography Data System Aide Memoire
24.6 Quality Assurance Oversight Aide Memoire
24.6.1 Routine Checks of Study or Batch Records
24.6.2 Data Integrity Audits
24.6.3 Data Integrity Investigations
Acknowledgements
References
Subject Index
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