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.
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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.
Chapter 1 How to Use This Book and an Introduction to Data Integrity,
Chapter 2 How Did We Get Here?,
Chapter 3 The Regulators' Responses,
Chapter 4 What Is Data Governance?,
Chapter 5 A Data Integrity Model,
Chapter 6 Roles and Responsibilities in a Data Governance Programme,
Chapter 7 Data Integrity Policies, Procedures and Training,
Chapter 8 Establishing and Maintaining an Open Culture for Data Integrity,
Chapter 9 An Analytical Data Life Cycle,
Chapter 10 Assessment and Remediation of Laboratory Processes and Systems,
Chapter 11 Data Integrity and Paper Records: Blank Forms and Instrument Log Books,
Chapter 12 The Hybrid System Problem,
Chapter 13 Get Rid of Paper: Why Electronic Processes are Better for Data Integrity,
Chapter 14 Data Integrity Centric Analytical Instrument Qualification and Computerised System Validation,
Chapter 15 Validating Analytical Procedures,
Chapter 16 Performing an Analysis,
Chapter 17 Second Person Review,
Chapter 18 Record Retention,
Chapter 19 Quality Metrics for Data Integrity,
Chapter 20 Raising Data Integrity Concerns,
Chapter 21 Quality Assurance Oversight for Data Integrity,
Chapter 22 How to Conduct a Data Integrity Investigation,
Chapter 23 Data Integrity and Outsourcing,
Chapter 24 Data Integrity Audit Aide Memoire,
Subject Index,
How to Use This Book and an Introduction to Data Integrity
Data Integrity is the hottest topic in the pharmaceutical industry now and will continue to be in the future. Regulatory authorities around the world have issued a number of guidance documents on the data integrity and data governance since the start of 2015 as well as two industry guidance documents. However, all documents are vague and most do not contain detailed examples or advice to help regulated laboratories to implement policies, procedures and processes to ensure integrity: they outline what needs to be done but there is often insufficient detail for effective implementation. From an analytical perspective there has not been a detailed focus on data integrity in a regulated analytical laboratory. Hence, the rationale for writing this book.
1.1 Aims and Objectives
The aim of this book is to provide practical and detailed advice on how to implement data integrity and data governance for regulated analytical laboratories working in the pharmaceutical and allied industries. Although the main thrust of the book is for chemical laboratories some microbiological analysis will also be discussed.
This book is written for analytical scientists, laboratory managers and supervisors and quality assurance personnel working in regulated laboratories in and for the pharmaceutical industry and who are involved with data integrity and data governance programmes. Where networked systems are discussed IT professionals may also find useful information here.
1.2 Structure of This Book
This book is comprised of 24 chapters that are divided into five sections of this book, as follows:
1. How to Use this Book is covered in this chapter.
2. The Regulatory Environment is discussed in Chapters 2 and 3.
3. Data Governance is presented and explained in Chapters 4 to 10 as well as Chapter 19.
4. Data Integrity is covered in Chapters 11 to 18.
5. Quality Assurance Oversight and Outsourcing are discussed in Chapters 20–24.
The detailed structure of the book and the constituent chapters are shown in Figure 1.1 and discussed in more detail in the following sections of this chapter. It is important to understand that data integrity and data governance is a complex subject that is not just focused on the accuracy, completeness and correctness of numbers generated in a regulated laboratory.
1.2.1 Chapter Structure
The majority of chapters in this book are structured and written in the same way:
• A chapter starts with a brief overview why the chapter is important within the overall context of data integrity and data governance.
• This is followed by a section on regulatory requirements or regulatory guidance that are relevant to the chapter; thereby positioning the regulatory rationale for the topic of the chapter.
• Where appropriate, there is also the business rationale for the tasks contained in the chapter.
• Then there is a discussion of how to achieve the objective of each chapter. For example, if you are assessing a process or a computerised system the chapter discusses how this can be achieved and how to avoid some of the common pitfalls.
• Each chapter finishes with a list of the references used.
1.2.2 You Do Not Read the Regulations!
As many people working in the pharmaceutical industry do not read the applicable regulations or applicable guidance documents, the intention of this approach is to put the regulatory and business rationale for performing a task at the reader's fingertips. It also allows an individual chapter to stand alone if a quick reference to a specific data integrity or data governance topic is all that is required. Overall, the aim is to give any reader the practical basis and confidence to implement or perform any of the topics covered by this book.
1.2.3 The Regulatory Environment
This topic is covered in two introductory chapters.
• Chapter 2, entitled How Did We Get Here?, provides the background to data integrity in regulated laboratories of the pharmaceutical industry over the past quarter of a century. The story starts with the Barr Laboratories court case and ruling in 1993 and then moves on to the Able Laboratories fraud case in 2005. The latter case triggered regulatory authorities to change their inspection focus from paper to electronic records and consequently they discovered many more cases of data falsification and poor data management practices in companies throughout the world. The key compliance issues, derived mainly from FDA warning letters for paper records and computerised systems, are used to highlight areas of regulatory concern for laboratory operations.
• Chapter 3 is The Regulators' Responses and outlines the response to the increased occurrence of data falsification and poor data integrity practices by the various regulatory agencies by issuing guidance documents and where necessary updating regulations. This chapter looks at the various guidance documents issued. The first was the FDA's Inspection of Pharmaceutical Quality Control Laboratories issued in 1993 following the Barr Laboratories case. Since 2015 there have been a many data integrity guidance documents issued from regulatory agencies and industry bodies.
1.2.4 Data Governance
Data governance is a relatively new concept to the pharmaceutical industry and the term comprises several interlinked topics that are discussed over the course of eight chapters.
• Chapter 4, entitled What is Data Governance?, sets out the strands of data governance that are discussed in more detail in the rest of the book. Data governance is not new and has been used outside the pharmaceutical industry for at least 15 years. We will compare and contrast DG...
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