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Data Integrity and Data Governance: Practical Implementation in Regulated Laboratories [Kõva köide]

(Director, R.D.McDowall Ltd)
  • Formaat: Hardback, 672 pages, kõrgus x laius: 234x156 mm, kaal: 1122 g, No
  • Ilmumisaeg: 09-Nov-2018
  • Kirjastus: Royal Society of Chemistry
  • ISBN-10: 178801281X
  • ISBN-13: 9781788012812
Teised raamatud teemal:
Data Integrity and Data Governance: Practical Implementation in Regulated LaboratoriesSuurem pilt
  • Formaat: Hardback, 672 pages, kõrgus x laius: 234x156 mm, kaal: 1122 g, No
  • Ilmumisaeg: 09-Nov-2018
  • Kirjastus: Royal Society of Chemistry
  • ISBN-10: 178801281X
  • ISBN-13: 9781788012812
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781788012812.html
Märksõnad:
Data integrity is the hottest topic in the pharmaceutical industry. Global regulatory agencies have issued guidance, after guidance after guidance in the past few years, most of which does not offer practical advice on how to implement policies, procedures and processes to ensure integrity. These guidances state what but not how. Additionally, key stages of analysis that impact data integrity are omitted entirely. The aim of this book is to provide practical and detailed help on how to implement data integrity and data governance for regulated analytical laboratories working in or for the pharmaceutical industry. It provides clarification of the regulatory issues and trends, and gives practical methods for meeting regulatory requirements and guidance. Using a data integrity model as a basis, the principles of data integrity and data governance are expanded into practical steps for regulated laboratories to implement. The author uses case study examples to illustrate his points and provides instructions for applying the principles of data integrity and data governance to individual laboratory needs. This book is a useful reference for analytical chemists and scientists, management and senior management working in regulated laboratories requiring either an understanding about data integrity or help in implementing practical solutions. Consultants will also benefit from the practical guidance provided.

Arvustused

The management of regulated industry needs to read all 600 pages in the book in order to set the standard for how every single person in their organization needs to work, themselves included. The book explains in detail all the aspects of the topics of data integrity, starting each chapter with the regulatory basis for each of them. McDowall has made it a lot easier for everyone by publishing this book. The amount of investigations that he has done in order to make system in the overwhelming craziness of the regulatory documents, is astonishing.

Chapter 1 How to Use This Book and an Introduction to Data Integrity
1(27)
1.1 Aims and Objectives
1(1)
1.2 Structure of This Book
2(7)
1.2.1
Chapter Structure
2(1)
1.2.2 You Do Not Read the Regulations!
2(2)
1.2.3 The Regulatory Environment
4(1)
1.2.4 Data Governance
4(2)
1.2.5 Data Integrity
6(2)
1.2.6 Quality Oversight for Data Integrity
8(1)
1.3 Mapping This Book to the Data Integrity Model
9(1)
1.4 Pharmaceutical Quality System and Data Integrity
9(3)
1.4.1 Integration Within the Pharmaceutical Quality System
9(2)
1.4.2 No
Chapter on Risk Management
11(1)
1.4.3 Back to the Future 1: Understanding Current in cGMP
11(1)
1.4.4 The European Equivalent of cGMP
11(1)
1.5 What Is Data Integrity?
12(3)
1.5.1 How Many Definitions Would You Like?
12(1)
1.5.2 What Do These Definitions Mean?
12(1)
1.5.3 ALCOA+ Criteria for Integrity of Laboratory Data
13(2)
1.6 Data Quality and Data Integrity
15(6)
1.6.1 From Sample to Reportable Result
15(1)
1.6.2 Contextual Metadata and a Reportable Result
16(2)
1.6.3 Data Integrity -- Can I Trust the Data?
18(2)
1.6.4 Data Quality -- Can I Use the Data?
20(1)
1.6.5 The Proposed FDA GLP Quality System
20(1)
1.6.6 Continual Versus Continuous Improvement
21(1)
1.7 Static Versus Dynamic Data
21(1)
1.8 Important Data Integrity Concepts
22(2)
1.8.1 Data Integrity Is More than Just Numbers
22(1)
1.8.2 Quality Does Not Own Quality Anymore
23(1)
1.8.3 Data Integrity Is Not Just 21 CFR 11 or Annex 11 Compliance
23(1)
1.8.4 Data Integrity Is an IT Problem
24(1)
1.8.5 Data Integrity Is a Laboratory Problem
24(1)
1.8.6 We Are Research - Data Integrity Does Not Impact Us
24(1)
1.9 It's Deja vu all Over Again!
24(1)
References
25(3)
Chapter 2 How Did We Get Here?
28(19)
2.1 Barr Laboratories 1993: You Cannot Test into Compliance
28(2)
2.1.1 Background to the Court Case
29(1)
2.1.2 Key Laboratory Findings from the Judgement
29(1)
2.1.3 Regulatory Response
30(1)
2.2 Able Laboratories 2005: You Cannot Falsify into Compliance
30(2)
2.2.1 Background to the Inspection
30(1)
2.2.2 Observations
30(1)
2.2.3 Regulatory Response
31(1)
2.3 Ranbaxy Warning Letters and Consent Decrees
32(1)
2.3.1 Background to the Regulatory Action
32(1)
2.3.2 Details of the 2012 Consent Decree
32(1)
2.4 Court Case for GLP Data Falsification
33(1)
2.5 Semler Research Data Falsification
34(1)
2.6 The Cost of Data Integrity Non-compliance
34(2)
2.6.1 Relative Costs of Compliance Versus Non-compliance
35(1)
2.6.2 Is It Worth It?
36(1)
2.7 A Parcel of Rogues: FDA Laboratory Data Integrity Citations
36(8)
2.7.1 Why Use Only FDA Warning Letters and 483 Observations?
36(1)
2.7.2 Quality Management System Failures
37(2)
2.7.3 Instrument Citations
39(2)
2.7.4 Citations for Lack of Laboratory Controls
41(1)
2.7.5 Failure to Have Complete Laboratory Records
41(2)
2.7.6 Too Much Data - Duplicate Record Sets
43(1)
2.7.7 Industrial Scale Shredding and Discarding of GMP Documents
43(1)
2.7.8 Responses by the Regulatory Authorities
44(1)
References
44(3)
Chapter 3 The Regulators' Responses
47(35)
3.1 What Do the Regulators Want?
47(3)
3.1.1 EU Good Manufacturing Practice
Chapter 1
47(1)
3.1.2 EU GMP
Chapter 4 on Documentation
48(1)
3.1.3 CFR 211 cGMP Regulations for Finished Pharmaceutical Goods
48(2)
3.1.4 EU GMP Annex 11 on Computerised Systems
50(1)
3.1.5 Regulatory Requirements Summary
50(1)
3.2 The Proposed FDA GLP Quality System
50(3)
3.2.1 Background to the Proposed Regulation
50(1)
3.2.2 New Data Quality and Integrity Requirements
51(1)
3.2.3 A New Data Integrity Role for the Study Director
52(1)
3.2.4 The GLP Study Report
52(1)
3.2.5 No Hiding Place for GLP Data Integrity Issues
52(1)
3.3 Overview of Regulatory Guidance Documents for Data Integrity
53(2)
3.4 Food and Drug Administration Guidance Documents
55(5)
3.4.1 FDA Guide to Inspection of Pharmaceutical Quality Control Laboratories
55(1)
3.4.2 FDA Compliance Program Guide 7346.832 on Pre Approval Inspections
56(1)
3.4.3 FDA Level 2 Guidance
57(1)
3.4.4 Delaying, Denying, Limiting or Refusing an FDA Inspection
58(1)
3.4.5 FDA Guidance on Data Integrity and Compliance with cGMP
58(2)
3.4.6 Key Points from the FDA Data Integrity Guidance
60(1)
3.5 MHRA Data Integrity Guidance Documents
60(3)
3.5.1 Initial Request to Industry December 2013
60(1)
3.5.2 MHRA GMP Data Integrity Guidance for Industry
61(1)
3.5.3 MHRA GXP Data Integrity Guidance for Industry
61(1)
3.5.4 MHRA Definition of Raw Data
62(1)
3.6 PIC/S Guidance Documents
63(1)
3.6.1 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
64(1)
3.7 WHO Guidance on Good Data and Records Management Practices
64(1)
3.8 GAMP Guide for Records and Data Integrity
65(3)
3.9 PDA Technical Report 80
68(4)
3.9.1 Regulatory Trends for Data Integrity Issues
70(1)
3.9.2 Data Integrity in Microbiology Laboratories
70(1)
3.9.3 Data Integrity in Analytical QC Laboratories
71(1)
3.9.4 How to Remediate Breaches in Data Integrity
72(1)
3.10 Understanding the Meaning of Raw Data and Complete Data
72(6)
3.10.1 Are Raw Data First-capture or Original Observations?
72(1)
3.10.2 In the Beginning
72(2)
3.10.3 Later, Much Later in Europe
74(1)
3.10.4 The GLP Quality System - The Proposed 21 CFR 58 Update
74(1)
3.10.5 Extracting Principles for Laboratory GXP Raw Data
75(1)
3.10.6 Visualising What Raw Data Mean
76(2)
3.10.7 Summary: Raw Data Is the Same as Complete Data
78(1)
3.11 Regulations and Data Integrity Guidance Summary
78(1)
References
79(3)
Chapter 4 What Is Data Governance?
82(14)
4.1 What Do the Regulators Want?
82(6)
4.1.1 EU GMP
Chapter 1 Pharmaceutical Quality System
82(1)
4.1.2 FDA Proposed GLP Quality System Update
83(1)
4.1.3 MHRA GXP Data Integrity Guidance
84(1)
4.1.4 WHO Guidance on Good Records and Data Management Practices
85(2)
4.1.5 PIC/S PI-041 - Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
87(1)
4.1.6 EMA Questions and Answers on Good Manufacturing Practice - Data Integrity
88(1)
4.1.7 Summary of Regulatory Guidance
88(1)
4.2 The Rationale for Data Governance: Regulatory Boot or Business Imperative?
88(1)
4.3 Perspectives of Data Governance Outside the Pharmaceutical Industry
89(1)
4.4 Key Data Governance Elements
90(4)
4.4.1 Summary of Regulatory Guidance for Data Governance
90(2)
4.4.2 Main Data Governance Areas
92(1)
4.4.3 Further Data Governance
Chapters in this Book
93(1)
References
94(2)
Chapter 5 A Data Integrity Model
96(23)
5.1 A Data Integrity Model
96(5)
5.1.1 A Logical Organisation of Data Integrity Elements
97(1)
5.1.2 Descriptions of the Four Levels in the Model
97(2)
5.1.3 An Analogy of Building a House
99(1)
5.1.4 Focus on the Laboratory Levels of the Data Integrity Model
100(1)
5.2 Foundation Level: The Right Corporate Culture for Data Integrity
101(3)
5.2.1 Role of Senior Management
101(1)
5.2.2 Data Governance Functions in the Foundation Level
101(3)
5.3 Level 1: The Right Analytical Instrument and Computer System for the Job
104(1)
5.3.1 Analytical Instrument Qualification and Computerised System Validation (AIQ and CSV)
104(1)
5.3.2 Data Governance Functions in the Level 1
105(1)
5.4 Level 2: The Right Analytical Procedure for the Job
105(2)
5.4.1 Validation of Analytical Procedures
105(1)
5.4.2 Verification of Pharmacopoeial Methods
106(1)
5.4.3 Bioanalytical Method Validation Guidance
106(1)
5.4.4 Manual Analytical Procedures Must Be Designed for Data Integrity
106(1)
5.5 Level 3: Right Analysis for the Right Reportable Result
107(1)
5.6 Quality Oversight for Data Integrity
107(1)
5.6.1 Quality Oversight of Laboratory Procedures and Work
107(1)
5.6.2 Data Integrity Audits
108(1)
5.6.3 Data Integrity Investigations
108(1)
5.7 Linking the Data Integrity Model to the Analytical Process
108(2)
5.7.1 The Data Integrity Model in Practice
108(2)
5.7.2 Quality Does Not Own Quality Anymore
110(1)
5.8 Mapping the WHO Guidance to the Data Integrity Model
110(2)
5.9 Assessment of Data Integrity Maturity
112(5)
5.9.1 Data Management Maturity Model
112(3)
5.9.2 Data Integrity Maturity Model
115(2)
References
117(2)
Chapter 6 Roles and Responsibilities in a Data Governance Programme
119(23)
6.1 What Do the Regulators Want?
119(6)
6.1.1 ICH Q10 Pharmaceutical Quality Systems
119(1)
6.1.2 EU GMP
Chapter 1
120(1)
6.1.3 PIC/S-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
121(1)
6.1.4 WHO Guidance on Good Data and Record Management Practices
122(1)
6.1.5 Update of the US GLP Regulations
123(1)
6.1.6 GAMP Guide Records and Data Integrity
124(1)
6.1.7 A Summary of Regulatory and Industry Guidance Documents
124(1)
6.2 Data Governance Roles and Responsibilities - Corporate Level
125(4)
6.3 Data Integrity Policy
129(1)
6.4 Management, Monitoring and Metrics
129(2)
6.5 Data Integrity and Data Governance Roles and Responsibilities - Process and System Level
131(6)
6.5.1 From Data Governance to Data Ownership
131(1)
6.5.2 Process Owner and System Owner
132(1)
6.5.3 Can a Process Owner Be a Data Owner?
132(1)
6.5.4 Other Data Governance Roles at the System Level
133(2)
6.5.5 Data Owner
135(1)
6.5.6 Data Steward
136(1)
6.5.7 Is a Lab Administrator a Data Steward?
136(1)
6.5.8 Is a Technology Steward a System Owner?
137(1)
6.5.9 Segregation of Roles and Duties
137(1)
6.6 The Short Straw
137(3)
6.6.1 Where Are We Now?
137(1)
6.6.2 The Hybrid System Nightmare
138(2)
6.7 Cascade of Roles and Responsibilities: from Boardroom to Bench
140(1)
References
140(2)
Chapter 7 Data Integrity Policies, Procedures and Training
142(39)
7.1 What Do the Regulators Want?
142(3)
7.1.1 EU GMP
Chapter 4 on Documentation
142(1)
7.1.2 WHO Guidance on Good Data and Record Management Practices
143(1)
7.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
144(1)
7.1.4 Regulatory Requirements Summary
144(1)
7.2 Environmental Analysis and an Approach to Data Integrity
145(4)
7.2.1 Background to EPA and Data Integrity
145(1)
7.2.2 NELAC and Laboratory Accreditation
146(1)
7.2.3 NELAC Quality System
146(1)
7.2.4 NELAC Data Integrity Training
147(2)
7.3 Corporate Data Integrity Policy Coupled with Effective Training
149(6)
7.3.1 Contents of a Corporate Data Integrity Policy
151(1)
7.3.2 Training in the Data Integrity Policy
152(3)
7.3.3 Agreeing to Comply with the Policy
155(1)
7.4 Suggested Data Integrity Procedures
155(1)
7.5 Principles of Good Documentation Practice
155(3)
7.5.1 Say What You Do
156(1)
7.5.2 Do What You Say
157(1)
7.5.3 Document It
157(1)
7.5.4 Automating Procedure Execution
157(1)
7.6 Training to Collect and Manage Raw Data and Complete Data
158(7)
7.6.1 Principles for GXP Laboratory Raw Data and Complete Data
158(1)
7.6.2 Approach to Training for Complete and Raw Data in the Laboratory
159(1)
7.6.3 Example 1 -- Paper Records from a Manual Test
159(2)
7.6.4 Example 2 -- Spectroscopic Analysis Using a Hybrid System
161(2)
7.6.5 Example 3 -- Chromatographic Analysis with a CDS Interfaced with a LIMS
163(2)
7.6.6 Additional Raw Data?
165(1)
7.7 Good Documentation Practice for Paper Records
165(4)
7.7.1 Recording Observations and Results
166(1)
7.7.2 Examples of Good and Poor Documentation Practice for Handwritten Records
167(1)
7.7.3 Fat Finger, Falsification and Fraud-Take 1
168(1)
7.7.4 Original Records and True Copies
169(1)
7.8 Good Documentation Practice for Hybrid Records
169(3)
7.8.1 Record Signature Linking for Hybrid Systems -- Spreadsheet Example
171(1)
7.9 Good Documentation Practice for Electronic Records
172(1)
7.9.1 Good Documentation Practice for Electronic Records
173(1)
7.10 Good Documentation Practice Training
173(1)
7.11 Role of the Instrument Log Book
173(5)
7.11.1 EU GMP
Chapter 4 on Documentation
175(2)
7.11.2 FDA Good Laboratory Practice 21 CFR58
177(1)
7.11.3 FDA 21 CFR 211 cGMP for Finished Pharmaceutical Products
177(1)
7.11.4 FDA Inspection of Pharmaceutical QC Laboratories
177(1)
7.11.5 Instrument Lag Books in Practice
178(1)
7.12 Training for Generating, Interpreting and Reviewing Laboratory Data
178(1)
7.12.1 Data Integrity Training for a Chromatography Data System: Operational SOPs
178(1)
7.12.2 Training Is of Little Value without an Open Culture
179(1)
References
179(2)
Chapter 8 Establishing and Maintaining an Open Culture for Data Integrity
181(21)
8.1 What Do the Regulators Want?
181(3)
8.1.1 WHO Guidance on Good Data and Record Management Practices
181(1)
8.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
182(1)
8.1.3 MHRA "GXP" Data Integrity Guidance and Definitions
183(1)
8.1.4 Regulatory Guidance Summary
183(1)
8.2 Bad Culture: Cressey's Fraud Triangle and Organisational Pressure
184(3)
8.2.1 Cressey's Fraud Triangle
184(1)
8.2.2 Breaking the Fraud Triangle
185(1)
8.2.3 Managerial and Peer Pressures Can Influence Analytical Results
186(1)
8.3 ISPE Cultural Excellence Report
187(1)
8.4 Management Leadership
188(1)
8.4.1 Generate and Communicate the Data Integrity Vision
188(1)
8.4.2 Talk the Talk and Walk the Walk
188(1)
8.4.3 Reinforcing an Open Culture for Data Integrity
189(1)
8.4.4 FDA Expectations for Analysts
189(1)
8.5 Mind Set and Attitudes
189(3)
8.5.1 Quality Does Not Own Quality Anymore
190(1)
8.5.2 The Iceberg of Ignorance
190(1)
8.5.3 How Do I Raise Problems to Management?
190(2)
8.6 Gemba Walks
192(5)
8.6.1 Where Does a Gemba Walk Fit in a QMS?
192(1)
8.6.2 What Gemba Walks Are and Are Not
193(1)
8.6.3 Why Bother with a Gemba Walk?
194(1)
8.6.4 Activation Energy for a Gemba Walk
194(1)
8.6.5 Performing the Gemba Walk
195(1)
8.6.6 Keep the Focus on the Process
196(1)
8.6.7 Generic Questions for a Gemba Walk
196(1)
8.6.8 Let Management See Analytical Instruments First Hand
197(1)
8.7 Fat Finger, Falsification and Fraud - Take 2
197(3)
8.7.1 To Err Is Human
197(1)
8.7.2 Verification of Data Entry
198(1)
8.7.3 What Is the Fat Finger Rate in a Laboratory?
198(1)
8.7.4 Learning from Health Service Studies
199(1)
8.8 Maintaining the Open Culture
200(1)
References
200(2)
Chapter 9 An Analytical Data Life Cycle
202(21)
9.1 What Do the Regulators Want?
202(3)
9.1.1 MHRA GXP Data Integrity Guidance
202(1)
9.1.2 WHO Guidance on Good Data and Record Management Practices
203(1)
9.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
203(1)
9.1.4 Regulatory Requirements Summary
204(1)
9.2 Published Data Life Cycles
205(3)
9.2.1 GAMP Guide on Records and Data Integrity
205(1)
9.2.2 Validation of Chromatography Data Systems
206(1)
9.2.3 Critique of the Two Life Cycle Models
207(1)
9.3 An Analytical Data Life Cycle
208(7)
9.3.1 Overview of an Analytical Data Life Cycle
208(1)
9.3.2 Controlling the Analytical Data Life Cycle
209(1)
9.3.3 Phases of the Analytical Data Life Cycle
210(2)
9.3.4 Generic Data Life Cycles Do Not Work in the Laboratory
212(1)
9.3.5 The Requirement for Flexibility to Adapt to Different Analytical Procedures
212(3)
9.4 Establishing Data Criticality and Inherent Integrity Risk
215(3)
9.4.1 Spectrum of Analytical Instruments and Laboratory Computerised Systems
215(3)
9.5 Risks to Data Over the Data Life Cycle
218(3)
9.5.1 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
218(1)
9.5.2 Initial Assessment of Risk of the Analytical Data Life Cycle Phases
219(1)
9.5.3 Phases of the Data Life Cycle are Equal but Some are More Equal than Others
220(1)
9.5.4 Summary Risks in the Analytical Data Life Cycle
221(1)
References
221(2)
Chapter 10 Assessment and Remediation of Laboratory Processes and Systems
223(19)
10.1 What Do the Regulators Want?
224(1)
10.1.1 WHO Guidance on Good Data and Record Management Practices
224(1)
10.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
224(1)
10.1.3 MHRA GXP Data Integrity Guidance and Definitions
224(1)
10.1.4 Regulatory Guidance Summary
225(1)
10.2 Business Rationale for Assessment and Remediation
225(1)
10.2.1 Improve Business Processes
225(1)
10.2.2 Ensure Regulatory Compliance
225(1)
10.2.3 Release Product Earlier
226(1)
10.2.4 The Problem is Management
226(1)
10.3 Current Approaches to System Assessment and Remediation
226(3)
10.3.1 The Rationale for Current Approaches?
226(1)
10.3.2 Assessment of Validated Computerised Systems
227(2)
10.4 Data Process Mapping
229(9)
10.4.1 The Problem with Checklists
229(1)
10.4.2 What is Data Process Mapping?
229(3)
10.4.3 Instrument Data System with Spreadsheet Calculations
232(1)
10.4.4 Spreadsheets Used for GMP Calculations Are High Risk
233(1)
10.4.5 Critical Activities in a Process
234(1)
10.4.6 Fix and Forget versus Delivering Business Benefits?
235(1)
10.4.7 Short Term Remediation Leading to Long Term Solution
236(2)
10.5 Data Integrity Issues with Analysis by Observation
238(1)
10.5.1 Potential Problems with Analysis by Observation
238(1)
10.5.2 A Risk Based Approach to Analysis by Observation
238(1)
10.5.3 Melting Point Determination
239(1)
10.6 Data Integrity Issues with Paper Records
239(2)
10.6.1 Blank Forms Must be Controlled with Accountability
240(1)
References
241(1)
Chapter 11 Data Integrity and Paper Records: Blank Forms and Instrument Log Books
242(25)
11.1 What Do the Regulators Want? - Blank Forms
242(5)
11.1.1 Focus on the Key Data Integrity Issues with Paper Records
242(1)
11.1.2 FDA Guide to Inspection of Quality Control Laboratories
243(1)
11.1.3 MHRA GMP Data Integrity Guidance
243(1)
11.1.4 MHRA Draft GXP Data Integrity Guidance
243(1)
11.1.5 MHRA GXP Data Integrity Guidance and Definitions
244(1)
11.1.6 WHO Guidance on Good Data and Record Management Practices
244(1)
11.1.7 FDA Data Integrity and Compliance with cGMP
244(1)
11.1.8 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
245(1)
11.1.9 EMA GMP Questions and Answers on Data Integrity
246(1)
11.1.10 Regulatory Guidance Summary
246(1)
11.2 Control of Master Templates and Blank Forms
247(8)
11.2.1 Understanding Master Templates and Blank Forms
247(1)
11.2.2 Requirements for the Design, Approval and Storage of Master Templates
248(1)
11.2.3 Process for Generation, Review and Approval of a Master Template
248(3)
11.2.4 Requirements for the Issue and Reconciliation of Blank Forms
251(2)
11.2.5 Process for Issue and Reconciliation of Blank Forms
253(1)
11.2.6 Process for Issue and Reconciliation of Blank Forms
254(1)
11.2.7 Completing Blank Forms and Creating GXP Records
255(1)
11.3 What Do the Regulators Want? - Instrument Log Books
255(3)
11.3.1 EU GMP
Chapter 4 on Documentation
255(1)
11.3.2 FDA GMP 21 CFR 211
255(2)
11.3.3 FDA Good Laboratory Practice 21 CFR 58
257(1)
11.3.4 OECD GLP Regulations
257(1)
11.3.5 Summary of Regulatory Requirements for an Instrument Log Book
257(1)
11.4 The Role of an Instrument Log Book for Ensuring Data Integrity
258(4)
11.4.1 Why is an Instrument Log Book Important?
258(1)
11.4.2 What Needs to be Entered in the Log Book?
259(1)
11.4.3 Inspectors Know the Importance of an Instrument Log
260(1)
11.4.4 FDA Citations for Laboratory Log Books
261(1)
11.4.5 Instrument Log Books in Practice
261(1)
11.5 Role of the Instrument Log Book in the Second Person Review
262(1)
11.5.1 Is an Instrument Performing OK?
262(1)
11.6 Automating Blank Forms and Instrument Log Books
263(2)
11.6.1 Automating Master Templates and Blank Forms
263(1)
11.6.2 Instrument Log Book
264(1)
Acknowledgements
265(1)
References
265(2)
Chapter 12 The Hybrid System Problem
267(14)
12.1 What Do the Regulators Want?
267(5)
12.1.1 Electronic Records and Electronic Signatures Regulations (21 CFR 11)
267(1)
12.1.2 WHO Guidance on Good Data and Record Management Practices
268(1)
12.1.3 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
269(1)
12.1.4 EU GMP
Chapter 4 on Documentation
269(1)
12.1.5 FDA Guidance for Industry Data Integrity and cGMP Compliance
269(2)
12.1.6 FDA Level 2 Guidance for Records and Reports
271(1)
12.1.7 Regulatory Summary
272(1)
12.2 What Is a Hybrid System?
272(1)
12.2.1 WHO Definition of a Hybrid System
272(1)
12.2.2 Key Features of a Hybrid System
273(1)
12.3 The Core Problems of Hybrid Systems
273(5)
12.3.1 A Typical Hybrid System Configuration
273(2)
12.3.2 File Organisation and Printing Results
275(1)
12.3.3 Synchronising Paper Printouts and Electronic Records
276(2)
12.3.4 A Simple Way to Reduce Paper with Hybrid Systems
278(1)
12.4 Eliminate Hybrid Systems
278(2)
References
280(1)
Chapter 13 Get Rid of Paper: Why Electronic Processes are Better for Data Integrity
281(24)
13.1 What Do the Regulators Want?
281(3)
13.1.1 WHO Guidance on Good Data and Record Management Practices
281(1)
13.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
282(1)
13.1.3 EU GMP Annex 11 Computerised Systems
283(1)
13.1.4 Regulatory Summary
283(1)
13.2 Why Bother with Paper?
284(3)
13.2.1 Tradition -- Why Change Our Approach?
284(1)
13.2.2 Back to the Future 2: Understanding the Current in cGMP
284(1)
13.2.3 The Pharmaceutical Industry is a Two Sigma Industry
285(1)
13.2.4 Are the Regulations Part of the Data Integrity Problem?
286(1)
13.2.5 Is Paper a Realistic Record Medium Now?
287(1)
13.3 Design Principles for Electronic Working
287(2)
13.4 Designing Data Workflows 1 -- Analytical Balances
289(6)
13.4.1 Weighing a Reference Standard or Sample
290(1)
13.4.2 Recording a Weight by Observation
290(1)
13.4.3 Recording Balance Weights with a Printer
291(1)
13.4.4 Connecting the Balance to an Instrument Data System
292(3)
13.5 Designing Data Workflows 2 - Chromatography Data Systems and LIMS
295(6)
13.5.1 Options for Interfacing
295(2)
13.5.2 Manual Data Transfer Between CDS and LIMS
297(1)
13.5.3 Unidirectional Interfacing from CDS to LIMS
297(2)
13.5.4 Bidirectional Interfacing Between CDS and LIMS
299(2)
13.6 Impact on Data Integrity and Second Person Review
301(1)
13.6.1 Ensuring Data Integrity with Electronic Working
301(1)
13.6.2 Impact on Second Person Review
302(1)
13.6.3 Summary of an Approach for Electronic Working that Ensures Data Integrity
302(1)
References
302(3)
Chapter 14 Data Integrity Centric Analytical Instrument Qualification and Computerised System Validation
305(37)
14.1 What the Regulators Want
306(3)
14.1.1 CFR 211 Current GMP for Finished Pharmaceutical Products
306(1)
14.1.2 CFR 58 GLP for Non-clinical Studies
306(1)
14.1.3 United States Pharmacopoeia <1058> on Analytical Instrument Qualification
306(1)
14.1.4 EU GMP Annex 11
307(1)
14.1.5 ICH Q7 and EU GMP Part 2: Good Manufacturing Practice Guide for Active Pharmaceutical Ingredients
307(1)
14.1.6 WHO Guidance on Good Data and Record Management Practices
307(1)
14.1.7 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
308(1)
14.1.8 Regulatory Summary
308(1)
14.2 GMP Regulations and the Pharmacopoeias
309(2)
14.2.1 Relationship Between GMP and the Pharmacopoeias
309(1)
14.2.2 Importance of USP <1058>
310(1)
14.2.3 Use the USP <1058> Principles for GLP Instruments and Systems
311(1)
14.3 Why Is Instrument Qualification Important?
311(1)
14.3.1 Data Quality Triangle
311(1)
14.3.2 Data Integrity Model
312(1)
14.4 Why a New Revision of USP <1058>?
312(2)
14.4.1 Problems with the 2008 Version
312(1)
14.4.2 Revision Path of USP<1058>
313(1)
14.5 What Has Changed with USP <1058>?
314(6)
14.5.1 Differences Between the Old and New Versions of USP <1058>
314(1)
14.5.2 Omitted Sections in the New Version
314(1)
14.5.3 Additions and Changes to USP <1058>
315(1)
14.5.4 Roles and Responsibilities
315(1)
14.5.5 An Updated 4Qs Model
315(4)
14.5.6 Harmonisation of Qualification Approaches
319(1)
14.6 Importance of the Laboratory URS for Analytical Instruments
320(4)
14.6.1 Role of the URS
320(1)
14.6.2 Understand Your Intended Use
321(1)
14.6.3 A Role of the Supplier: Write Meaningful Specifications
321(1)
14.6.4 How Minimal Is Minimal?
322(1)
14.6.5 Do Not Forget the Software!
323(1)
14.6.6 Purchasing a Second Instrument
323(1)
14.6.7 It's all About Investment Protection
323(1)
14.7 Software Validation Changes to USP <1058>
324(7)
14.7.1 Improving the Analytical Process
325(1)
14.7.2 A Validated System with Vulnerable Records Means Data Integrity Problems
326(2)
14.7.3 Change the Validation Approach to Ensure Data Integrity
328(1)
14.7.4 Brave New CSV World?
328(1)
14.7.5 Turning Principles into Practice
329(2)
14.7.6 Qualified, Validated and Released for Operational Use
331(1)
14.8 Performance Qualification
331(8)
14.8.1 Changes to USP <1058> and the Impact on Understanding of PQ
332(1)
14.8.2 Linking the URS, OQ, and PQ
333(1)
14.8.3 PQ for Group A Instruments
334(1)
14.8.4 PQ for Group B Instruments
334(1)
14.8.5 PQ for Group C Instruments
335(2)
14.8.6 System Suitability Tests as Part of a PQ
337(1)
14.8.7 Keep It as Simple as Possible -- But No Simpler
338(1)
14.8.8 Holistic HPLC PQ Test
338(1)
Acknowledgement
339(1)
References
339(3)
Chapter 1 Validating Analytical Procedures
342(25)
15.1 What the Regulators Want
343(3)
15.1.1 US GMP 21 CFR 211
343(1)
15.1.2 EU GMP
Chapter 6 on Quality Control
343(1)
15.1.3 EU GMP Annex 15: Qualification and Validation
343(1)
15.1.4 Bioanalytical Method Validation Guidances
343(2)
15.1.5 Regulatory Requirements Summary
345(1)
15.1.6 Outsource Analytical Work with Care
345(1)
15.2 Current Method Validation Guidance
346(4)
15.2.1 Terminology: Analytical Method or Analytical Procedure?
346(1)
15.2.2 Business Rationale for Procedure Validation/Verification
346(2)
15.2.3 ICH Q2(R1) Validation of Analytical Procedures: Text and Methodology
348(1)
15.2.4 FDA Guidance for Industry on Analytical Procedure Validation
348(1)
15.2.5 Update of ICH Q2(R1) to a Life Cycle Approach
348(1)
15.2.6 Pharmacopoeial Methods Do Not Work as Written
349(1)
15.3 Role of Analytical Procedure Validation in Data Integrity
350(1)
15.3.1 Method Validation in the Data Integrity Model
350(1)
15.3.2 Equating the Data Integrity Model with the USP <1058> Data Quality Triangle
351(1)
15.4 Current Approaches to Validation and Verification of Procedures
351(3)
15.4.1 Good Manufacturing Practice
351(1)
15.4.2 Bioanalytical Method Validation
351(2)
15.4.3 Validation Documentation for Analytical Procedures
353(1)
15.4.4 Validation Parameters
354(1)
15.5 Overview of the Life Cycle of Analytical Procedures
354(2)
15.5.1 USP <1220> and Stimuli to the Revision Process
354(1)
15.5.2 Life Cycle of Analytical Procedures
355(1)
15.6 Defining the Analytical Target Profile (ATP)
356(1)
15.6.1 Specification for an Analytical Procedure
356(1)
15.6.2 Advantages and Limitations of an Analytical Target Profile
356(1)
15.7 Stage 1: Procedure Design and Development
357(4)
15.7.1 Overview
357(1)
15.7.2 Information Gathering and Initial Procedure Design
357(1)
15.7.3 Iterative Method Development and Method Optimisation
358(2)
15.7.4 Risk Assessment and Management
360(1)
15.7.5 Analytical Control Strategy: Identifying and Controlling Risk Parameters
361(1)
15.7.6 Procedure Development Report
361(1)
15.8 Stage 2: Procedure Performance Qualification
361(3)
15.8.1 Planning the Validation
361(1)
15.8.2 Validation Report
362(1)
15.8.3 Analytical Procedure Transfer
363(1)
15.9 Stage 3: Procedure Performance Verification
364(1)
15.9.1 Routine Monitoring of Analytical Performance
364(1)
15.9.2 Changes to an Analytical Procedure
364(1)
15.9.3 Validated Analytical Procedure
364(1)
References
365(2)
Chapter 16 Performing an Analysis
367(48)
16.1 What the Regulators Want
368(2)
16.1.1 EU GMP
Chapter 1 Pharmaceutical Quality System
368(1)
16.1.2 US GMP 21 CFR 211 GMP for Finished Pharmaceutical Products
368(1)
16.1.3 FDA Guide for Inspection of Pharmaceutical Quality Control Laboratories
369(1)
16.2 The Analytical Process
370(4)
16.2.1 Linking the Data Integrity Model to the Analytical Process
370(2)
16.2.2 Process Overview
372(1)
16.2.3 Analytical Instruments Are Qualified and/or Validated
372(1)
16.2.4 System Suitability Tests and Point of Use Checks
372(2)
16.3 The Scope of Analytical Procedures
374(1)
16.4 Sampling and Sample Management
375(7)
16.4.1 What the Regulators Want
375(1)
16.4.2 Sampling Is Critical
376(1)
16.4.3 GMP Sample Plan and Sampling
377(1)
16.4.4 GLP Protocol and Sampling
377(1)
16.4.5 Ensure Correct Sample Labelling
378(1)
16.4.6 Transport to the Laboratory
379(1)
16.4.7 Sample Receipt and Storage
380(1)
16.4.8 Sample Collection Best Practice
381(1)
16.5 Reference Standards and Reagents
382(4)
16.5.1 What the Regulators Want
382(1)
16.5.2 Preparation of Reference Standards and Solutions
383(1)
16.5.3 Sweep Under the Carpet or Own Up to a Mistake?
384(1)
16.5.4 What Is the FDA's View of Analyst Mistakes?
385(1)
16.6 Sample Preparation
386(2)
16.6.1 What the Regulators Want
386(1)
16.6.2 Sample Preparation Current Practices
386(1)
16.6.3 Automate Where Technically Feasible
387(1)
16.7 Recording Data by Observation
388(1)
16.7.1 Typical Tests Recording Results by Observation
388(1)
16.7.2 Instruments with No Printer or Data Transfer Capability
388(1)
16.7.3 Pharmacopoeial Indicator Tests
389(1)
16.8 Sample Preparation Followed by Instrumental Analysis Methods
389(2)
16.8.1 An Illustrative Analytical Procedure
389(1)
16.8.2 Ensuring Data Integrity
390(1)
16.8.3 Consider Alternate Analytical Approaches
390(1)
16.9 Methods Involving Instrumental Analysis and Data Interpretation
391(2)
16.9.1 What the Regulators Want
391(1)
16.9.2 Near Infra-red (NIR) Identity Testing
392(1)
16.9.3 Building a Spectral Library
392(1)
16.9.4 Performing the Analysis
393(1)
16.10 Chromatographic Analysis and CDS Data Interpretation
393(15)
16.10.1 What the Regulators Want
394(1)
16.10.2 Setting Up the Chromatograph and Acquiring Data
394(1)
16.10.3 Entering Factors, Weights, and Other Assay Values into the Sequence File
394(2)
16.10.4 An Alternate Approach to Weights and Factors
396(1)
16.10.5 System Evaluation Injections
397(1)
16.10.6 System Suitability Tests - What the Regulators Want
398(1)
16.10.7 Integrating Chromatograms
399(1)
16.10.8 General Principles for Ensuring Good Chromatographic Integration
400(1)
16.10.9 SOP for Integration of Chromatograms
401(3)
16.10.10 Bioanalytical Guidance for Integration of Chromatograms
404(1)
16.10.11 Incomplete (Aborted) Runs
405(1)
16.10.12 Other Unplanned Injections
406(1)
16.10.13 Datastorage Locations
406(1)
16.10.14 Chromatography Falsification Practices 1: Peak Shaving and Enhancing
406(1)
16.10.15 Chromatography Falsification Practices 2: Inhibiting Integration
407(1)
16.10.16 Chromatography Falsification Practices 3: Integrating Samples First
408(1)
16.11 Calculation of Reportable Results
408(4)
16.11.1 What the Regulators Want
409(1)
16.11.2 General Considerations for Calculations
410(1)
16.11.3 Avoid Using Spreadsheets for Analytical Calculations Whenever Possible
411(1)
16.11.4 Calculation of Reportable Results and Out of Specification Results
411(1)
16.11.5 Completion of Testing
412(1)
Acknowledgement
412(1)
References
412(3)
Chapter 17 Second Person Review
415(38)
17.1 What Do the Regulators Want?
416(4)
17.1.1 cGMP for Finished Pharmaceutical Products (21 CFR 211)
416(1)
17.1.2 EU GMP
Chapter 6 Quality Control
416(1)
17.1.3 EU GMP Annex 11
416(1)
17.1.4 MHRA GXP Data Integrity Guidance and Definitions
417(1)
17.1.5 FDA Guidance on Data Integrity and cGMP Compliance
417(2)
17.1.6 WHO Guidance on Good Data and Record Management Practices
419(1)
17.1.7 Regulatory Compliance Summary
420(1)
17.2 What the Regulators Want: Out of Specification (OOS) Results
420(3)
17.2.1 CFR 211
420(1)
17.2.2 EU GMP
Chapter 6 Quality Control
421(1)
17.2.3 FDA Guidance for Industry on Investigating OOS Test Results
421(1)
17.2.4 FDA Guidance on Quality Metrics
422(1)
17.2.5 OOS Definitions
422(1)
17.2.6 OOS Regulatory Summary
422(1)
17.3 Procedures for the Second Person Review
423(3)
17.3.1 Who Should Conduct a Second Person Review?
423(1)
17.3.2 The Scope of the Procedure
423(1)
17.3.3 The Troika of Record Review
424(1)
17.3.4 Timeliness of the Second Person Review
425(1)
17.3.5 Documenting the Audit Trail Review
425(1)
17.3.6 Training for Second Person Review
425(1)
17.3.7 Out of Specification (OOS) Procedure
426(1)
17.4 Second Person Review of Analytical Procedures Involving Observation
426(2)
17.4.1 What Is an Analytical Procedure Involving Observation?
426(1)
17.4.2 Improving Manual Analytical Procedures
426(1)
17.4.3 Witness Testing or Second Person Review?
427(1)
17.5 Sample Preparation and Instrumental Analysis
428(3)
17.5.1 Loss on Drying Analysis
428(1)
17.5.2 Review of the Second Person Review of the Analytical Records
429(2)
17.6 Second Person Review of a Hybrid System Records
431(7)
17.6.1 Increased Scope of Record and Data Review
431(1)
17.6.2 Technical Versus Procedural Controls for Second Person Review
431(1)
17.6.3 The Scope of an Analytical Procedure Involving a Hybrid System
432(1)
17.6.4 Technical Controls to Aid a Second Person Review
433(1)
17.6.5 Paper and Electronic Records to be Reviewed
434(1)
17.6.6 Recording the Work Performed and the Review
434(1)
17.6.7 Original Record or True Copy?
435(1)
17.6.8 Have Critical Data Been Entered into the Instrument Data System?
436(1)
17.6.9 Review of Electronic Records, Metadata and Audit Trail
436(1)
17.6.10 Second Person Review to Ensure Data Have Not Been Falsified
437(1)
17.6.11 Do You Really Want to Work This Way?
437(1)
17.7 Risk Based Audit Trail Review
438(4)
17.7.1 MHRA GXP Data Integrity Guidance and Definitions
438(1)
17.7.2 Which Audit Trail Should Be Reviewed?
439(1)
17.7.3 How Regular Is a Regular Review of Audit Trail Entries?
439(3)
17.8 Second Person Review of Electronic Systems and Data
442(5)
17.8.1 LIMS Interfaced with a CDS
442(2)
17.8.2 A Second Person Review Is Process Not System Centric
444(3)
17.9 Recording and Investigating Out of Specification Results
447(4)
17.9.1 Phase 1: Initial OOS Laboratory Investigation
448(2)
17.9.2 Phase 2A Production
450(1)
17.9.3 Phase 2B Additional Laboratory Testing
450(1)
17.9.4 OOS Investigations: Prevention Is Better than the Cure
451(1)
References
451(2)
Chapter 18 Record Retention
453(21)
18.1 What Do the Regulators Want?
453(7)
18.1.1 WHO Guidance on Good Data and Record Management Practices
453(1)
18.1.2 EU GMP Annex 11
454(1)
18.1.3 GLP Regulations: 21 CFR 58
454(1)
18.1.4 US GMP Regulations: 21 CFR 211
455(1)
18.1.5 CFR 11 Requirements
455(1)
18.1.6 MHRA GXP Data Integrity Guidance and Definitions
456(1)
18.1.7 FDA Guidance on Data Integrity and cGMP Compliance
456(1)
18.1.8 EU GMP
Chapter 4 Documentation
457(1)
18.1.9 FDA Guidance for Industry Part 11 -- Scope and Application Guidance
457(1)
18.1.10 FDA Inspection of Pharmaceutical Quality Control Laboratories
458(1)
18.1.11 OECD GLP Regulations
458(1)
18.1.12 OECD GLP Guidance on Application of GLP to Computerised Systems
459(1)
18.1.13 Regulatory Requirements Summary
459(1)
18.2 Laboratory Data File Formats and Standards
460(2)
18.2.1 JCAMP-DX Data Format for Spectroscopy
460(1)
18.2.2 Current CDS Data Standards
461(1)
18.2.3 Progress Towards Universal Data File Formats
461(1)
18.3 Options for Electronic Records Retention and Archive
462(6)
18.3.1 Backup Is Not Archive (Unless You Are the FDA)
462(1)
18.3.2 Organising Electronic Records to Retain
463(1)
18.3.3 Options for Electronic Archive
464(1)
18.3.4 Can I Read the Records?
465(1)
18.3.5 Impact of a Changed Data System File Format
466(1)
18.3.6 Selection of Off-line Archive Media
466(1)
18.3.7 Changing the Instrument Data System - What Are the Archive Options?
467(1)
18.3.8 Overview of Some Options
467(1)
18.3.9 Assessment of Option Feasibility
467(1)
18.4 OECD Guidance for Developing an Electronic Archive
468(4)
18.4.1 Definitions
468(1)
18.4.2 Roles and Responsibilities
469(1)
18.4.3 Archive Facilities
469(1)
18.4.4 Archiving Electronic Records
470(2)
References
472(2)
Chapter 19 Quality Metrics for Data Integrity
474(17)
19.1 What Do the Regulators Want?
474(3)
19.1.1 EU GMP
Chapter 6 Quality Control
474(1)
19.1.2 FDA Quality Metrics Guidance for Industry
475(1)
19.1.3 WHO Guidance on Good Data and Record Management Practices
475(1)
19.1.4 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
476(1)
19.1.5 MHRA GXP Data Integrity Guidance and Definitions
477(1)
19.1.6 Regulatory Guidance Summary
477(1)
19.2 KPIs and Metrics for the Laboratory
477(4)
19.2.1 Understanding Laboratory Metrics
478(1)
19.2.2 Metrics Must Be Generated Automatically
478(1)
19.2.3 Why Metrics for Data Integrity?
479(1)
19.2.4 Do Quality Metrics Lead Behaviour?
479(2)
19.2.5 Are Incidents Hidden Metrics?
481(1)
19.3 Data Integrity Metrics in an Organisation
481(1)
19.3.1 Overview: Start Small and Expand
481(1)
19.3.2 Scope of the Organisation
482(1)
19.3.3 Some Suggested Data Integrity Metrics
482(1)
19.4 DI Policies, Assessment and Remediation of Processes and Systems
482(4)
19.4.1 Data Integrity Policy and Associated Procedures
482(1)
19.4.2 Assessment of Processes and Systems
483(1)
19.4.3 Executed Remediation Plans
484(2)
19.5 Laboratory Data Integrity Metrics
486(1)
19.5.1 Some Preliminary Considerations for Laboratory Data Integrity Metrics
486(1)
19.5.2 Outsourced Laboratory Testing
487(1)
19.6 Quality Assurance DI Metrics
487(1)
19.7 Management Review of DI Metrics
488(1)
19.7.1 Management Are Responsible for Data Integrity and the PQS
488(1)
19.7.2 How Regular Is Regular Review?
489(1)
Acknowledgement
489(1)
References
489(2)
Chapter 20 Raising Data Integrity Concerns
491(8)
20.1 What Do the Regulators Want?
491(2)
20.1.1 WHO Guidance on Good Data and Record Management Practices
491(1)
20.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
492(1)
20.1.3 NELAC Quality Standard
493(1)
20.1.4 Regulatory Guidance Summary
493(1)
20.2 Data Integrity Problem or Concern?
493(1)
20.3 What Is Needed to Raise a Data Integrity Concern?
494(2)
20.3.1 A Section in the Corporate Data Integrity Policy
494(1)
20.3.2 Communicate and Train How to Raise Data Integrity Concerns
494(1)
20.3.3 Raising a Concern or Airing a Grievance?
495(1)
20.3.4 What Should Be Reported?
495(1)
20.3.5 Protecting the Whistleblower
495(1)
20.3.6 Confidentiality
495(1)
20.3.7 Raising Concerns Anonymously
496(1)
20.4 Raising a Concern
496(2)
20.4.1 Who Should You Raise Your Concern with?
496(1)
20.4.2 How to Raise a Concern
496(1)
20.4.3 Raise an Issue via Management or Quality Assurance?
497(1)
20.4.4 What the Organisation Must Do
497(1)
20.4.5 What If the Company Is the Problem?
498(1)
References
498(1)
Chapter 21 Quality Assurance Oversight for Data Integrity
499(22)
21.1 What Do the Regulators Want?
499(6)
21.1.1 EU GMP
Chapter 9 Self-inspections
499(1)
21.1.2 US GMP 21 CFR 211 Current Good Manufacturing Practice for Finished Pharmaceutical Products
500(1)
21.1.3 FDA Compliance Program Guide 7346.832 for Pre-approval Inspections
500(1)
21.1.4 CFR 58 Good Laboratory Practice for Non-clinical Laboratory Studies
501(1)
21.1.5 MHRA GXP Data Integrity Guidance and Definitions
501(1)
21.1.6 WHO Guidance on Good Data and Record Management Practices
502(1)
21.1.7 PIC/S-PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
503(1)
21.1.8 Regulatory Compliance Summary
504(1)
21.1.9 Role of the Laboratory in Ensuring Data Integrity
505(1)
21.2 Data Integrity Audits: Planning and Execution
505(5)
21.2.1 Rationale for Data Integrity Audits
505(1)
21.2.2 What Are the Objectives of a Laboratory Data Integrity Audit?
505(1)
21.2.3 What Will We Audit? The Data Integrity Inventory and Data Criticality
506(1)
21.2.4 What Is the Order and Frequency of Audit?
506(2)
21.2.5 Who Will Conduct the Audit?
508(1)
21.2.6 Data Integrity Audits and Periodic Reviews of Computerised Systems
508(1)
21.2.7 Procedure and Checklist for a Data Integrity Audit
509(1)
21.3 Conducting a Laboratory Data Integrity Audit
510(7)
21.3.1 Relationship Between the Data Integrity Model and a Data Integrity Audit
510(1)
21.3.2 Overview of the Analytical Process for a Laboratory Data Integrity Audit
511(2)
21.3.3 Expectations for Laboratory Records
513(1)
21.3.4 Auditing Records and Data from Sampling to Report
513(2)
21.3.5 Checking the Configuration Settings of Computerised Systems
515(1)
21.3.6 Identification and Investigation of Laboratory Out of Specification Results
516(1)
21.3.7 Photographs to Support Audit Observations and Findings
516(1)
21.3.8 Reporting the Audit
517(1)
21.4 What Is a Forensic Approach to Data Checking?
517(2)
21.4.1 Forensic Data Analysis
517(1)
21.4.2 Recovery of Deleted Files
518(1)
21.4.3 Forensic Data Analysis Techniques
519(1)
21.5 Triggers for a Data Integrity Investigation
519(1)
References
520(1)
Chapter 22 How to Conduct a Data Integrity Investigation
521(26)
22.1 What the Regulators Require
521(6)
22.1.1 WHO Guidance on Good Data and Record Management Practices
522(1)
22.1.2 FDA Guidance on Data Integrity and Compliance with CGMP
523(1)
22.1.3 FDA Application Integrity Policy
523(1)
22.1.4 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
524(1)
22.1.5 Summary of Data Investigation Regulations and Guidance
525(2)
22.2 Case Study 1: Software Error Investigation
527(3)
22.2.1 Case Study 1 Background
527(1)
22.2.2 Sequester a Copy of the System and the Data
527(1)
22.2.3 Temporary Resolution of the Problem
528(1)
22.2.4 Systems Approach to the Issue
528(1)
22.2.5 Time Frame of the Potential Data Integrity Vulnerability
528(1)
22.2.6 Investigating the Impacted Database
529(1)
22.2.7 Informing Regulatory Authorities
529(1)
22.3 Case Study 2: Data Falsification Investigation
530(15)
22.3.1 Case Study Background
530(1)
22.3.2 Meeting the Intent of the Application Integrity Policy
531(2)
22.3.3 Scope of the Data Integrity Investigation
533(1)
22.3.4 Approaches to the Investigation of Laboratory Data Integrity Issues
533(1)
22.3.5 Do Not Just Focus on Data Integrity Violations - Look Also for Poor Practices
534(1)
22.3.6 Investigation of Tests Using Observation
534(1)
22.3.7 Investigation of Simple Analytical Testing
535(1)
22.3.8 Investigation of Analytical Testing by Chromatography
535(1)
22.3.9 Staff Interviews
536(1)
22.3.10 Findings and Their Classification
537(3)
22.3.11 Root Cause of Data Integrity and Poor Data Management Practices
540(3)
22.3.12 Assessment of Material Impact
543(1)
22.3.13 CAPA Plans: Short-term Remediation and Long-term Solutions
544(1)
22.4 Summary
545(1)
References
545(2)
Chapter 23 Data Integrity and Outsourcing
547(18)
23.1 What the Regulators Want
547(5)
23.1.1 WHO Guidance on Good Data and Record Management Practices
547(2)
23.1.2 PIC/S PI-041 Good Practices for Data Management and Integrity in Regulated GMP/GDP Environments
549(2)
23.1.3 Regulatory Guidance Summary
551(1)
23.2 Cetero Research Laboratories Data Falsification Case
552(1)
23.3 Include Data Integrity in Supplier Assessment/Audit
553(1)
23.3.1 Current Approaches to Laboratory Audit
553(1)
23.3.2 Extending Assessment to Include Data Integrity
554(1)
23.4 Initial Data Integrity Assessment of a Facility
554(6)
23.4.1 Initial Selection of the Contract Laboratory
555(1)
23.4.2 Do Not Forget the Scientific and Technical Competence of the Supplier
556(1)
23.4.3 Request for Pre-audit Information
556(1)
23.4.4 Planning the Audit
557(1)
23.4.5 Data Governance and Data Integrity in the Context of a PQS
557(1)
23.4.6 Investigate Electronic Record Controls
558(1)
23.4.7 Conclusion of the Audit
559(1)
23.5 Agreements and Contracts for Data Integrity
560(1)
23.5.1 Main Data Integrity Contractual Responsibilities
560(1)
23.5.2 Using the Same Chromatography Data System
561(1)
23.5.3 Storage of the Records Generated
561(1)
23.6 On-going Monitoring of Work and Audits
561(3)
23.6.1 Risk Based Approaches to Monitoring
562(1)
23.6.2 Monitoring the Results
562(1)
23.6.3 Remote Assessment of Work Packages
563(1)
23.6.4 On-site Audits
563(1)
23.6.5 Contract Analytical Work with Your Eyes Open
564(1)
References
564(1)
Chapter 24 Data Integrity Audit Aide Memoire
565(21)
24.1 What the Regulators Want
565(1)
24.1.1 EU GMP
Chapter 9 Self-inspections
565(1)
24.1.2 Data Integrity Guidances for Audits
566(1)
24.1.3 Regulatory Requirements Summary
566(1)
24.2 Audit Aide Memoire for the Foundation Layer: Data Governance
566(5)
24.2.1 Management Leadership for Data Integrity
567(1)
24.2.2 Corporate Data Integrity and Ethics Policy
568(1)
24.2.3 Data Integrity Training
568(2)
24.2.4 Data Ownership for Computerised Systems
570(1)
24.2.5 Data Ownership for Manual Processes
570(1)
24.2.6 Establishment and Maintenance of an Open Culture
570(1)
24.3 Audit Aide Memoire for Level 1: AIQ and CSV
571(1)
24.3.1 Overview
571(1)
24.3.2 Analytical Instrument Qualification
571(1)
24.3.3 Computerised System Validation
571(1)
24.3.4 Validating Interfaces Between Computerised Systems
571(1)
24.4 Audit Aide Memoire for Level 2: Analytical Procedure Validation Life Cycle
571(5)
24.4.1 Procedure Design (Method Development)
574(2)
24.4.2 Analytical Procedure Performance Qualification (Method Validation)
576(1)
24.4.3 Method Application: Control and Monitoring
576(1)
24.5 Level 3: Study and Batch Analysis Data Integrity Aide Memoire
576(3)
24.5.1 Routine Analysis Data Integrity Aide Memoire
577(2)
24.5.2 Audit of Paper Analytical Records
579(1)
24.5.3 Audit of Hybrid Laboratory Computerised Systems
579(1)
24.5.4 Validation and Use of a Spreadsheet
579(1)
24.5.5 Chromatography Data System Aide Memoire
579(1)
24.6 Quality Assurance Oversight Aide Memoire
579(5)
24.6.1 Routine Checks of Study or Batch Records
582(1)
24.6.2 Data Integrity Audits
582(2)
24.6.3 Data Integrity Investigations
584(1)
Acknowledgements
584(1)
References
584(2)
Subject Index 586