Data Integrity: The Science, The Regulations, The Use
Throughout history, humans have recognized the importance of collecting reliable data. The Quality Assurance field is no exception, as promoting regulated life science that supports human, veterinary, and environmental health remains at the epicenter of our work.
But what defines data integrity, how does it differ from data quality, and how does it vary between regulations? What are the data integrity requirements specific to Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), Good Pharmacovigilance Practice (GVP), and other areas in regulated life science? What are specific, practical approaches to assessing data integrity?
After deep discussion surrounding these questions, leaders from the Society of Quality Assurance (SQA) saw the need to examine data quality and data integrity within the specific context of the QA profession. They collected their findings, takeaways from many discussions, and months of research to create a practical handbook tailored for the QA discipline – a book written by Quality Assurance professionals, for Quality Assurance professionals.
A key factor within Quality Assurance is that there are distinct differences in company data integrity policies and training, in what defines data quality and data integrity, organizational unit responsibilities, data integrity challenges and information needs, and in the use of electronic systems vs. paper-based systems to collect scientific data.
Regardless of whether your system is electronic, paper-based, or hybrid, and regardless of the specific regulatory mandates of your area, this book will be your go-to reference on data integrity principles and regulations, data governance, specific auditing tips, and much more that you can apply not only within your organization, but also throughout your Quality Assurance career.
Table of Contents
Chapter 1. What Is Data Integrity and Data Quality?
Chapter 2: Where Is It Written?
Chapter 3. Data Integrity Principles
Chapter 4. Roles, Responsibilities, and Stakeholders
Chapter 5. Data Governance, Classification, and Risk
Chapter 6. Data Collection, Metadata, and Audit Trails
Chapter 7. Data Integrity Challenges – Questions to Consider
Chapter 8. What Does Data Integrity Look Like?
Chapter 9. Training for Data Integrity Awareness
Chapter 10. Audit Strategies for Assessing Data Integrity
Chapter 11. The Future of Data Integrity
Appendix A. Regulations and Guidelines
Glossary
List of Figures and Tables
Index
About SQA
SQA is an association of over 2,500 professionals who are dedicated to implementing Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), and Good Pharmacovigilance Practice (GVP) across industry, government, academia, and consulting. Learn more at SQA.org.
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But what defines data integrity, how does it differ from data quality, and how does it vary between regulations? What are the data integrity requirements specific to Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), Good Pharmacovigilance Practice (GVP), and other areas in regulated life science? What are specific, practical approaches to assessing data integrity?
After deep discussion surrounding these questions, leaders from the Society of Quality Assurance (SQA) saw the need to examine data quality and data integrity within the specific context of the QA profession. They collected their findings, takeaways from many discussions, and months of research to create a practical handbook tailored for the QA discipline – a book written by Quality Assurance professionals, for Quality Assurance professionals.
A key factor within Quality Assurance is that there are distinct differences in company data integrity policies and training, in what defines data quality and data integrity, organizational unit responsibilities, data integrity challenges and information needs, and in the use of electronic systems vs. paper-based systems to collect scientific data.
Regardless of whether your system is electronic, paper-based, or hybrid, and regardless of the specific regulatory mandates of your area, this book will be your go-to reference on data integrity principles and regulations, data governance, specific auditing tips, and much more that you can apply not only within your organization, but also throughout your Quality Assurance career.
Table of Contents
Chapter 1. What Is Data Integrity and Data Quality?
Chapter 2: Where Is It Written?
Chapter 3. Data Integrity Principles
Chapter 4. Roles, Responsibilities, and Stakeholders
Chapter 5. Data Governance, Classification, and Risk
Chapter 6. Data Collection, Metadata, and Audit Trails
Chapter 7. Data Integrity Challenges – Questions to Consider
Chapter 8. What Does Data Integrity Look Like?
Chapter 9. Training for Data Integrity Awareness
Chapter 10. Audit Strategies for Assessing Data Integrity
Chapter 11. The Future of Data Integrity
Appendix A. Regulations and Guidelines
Glossary
List of Figures and Tables
Index
About SQA
SQA is an association of over 2,500 professionals who are dedicated to implementing Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), and Good Pharmacovigilance Practice (GVP) across industry, government, academia, and consulting. Learn more at SQA.org.
Data Integrity: The Science, The Regulations, The Use
Throughout history, humans have recognized the importance of collecting reliable data. The Quality Assurance field is no exception, as promoting regulated life science that supports human, veterinary, and environmental health remains at the epicenter of our work.
But what defines data integrity, how does it differ from data quality, and how does it vary between regulations? What are the data integrity requirements specific to Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), Good Pharmacovigilance Practice (GVP), and other areas in regulated life science? What are specific, practical approaches to assessing data integrity?
After deep discussion surrounding these questions, leaders from the Society of Quality Assurance (SQA) saw the need to examine data quality and data integrity within the specific context of the QA profession. They collected their findings, takeaways from many discussions, and months of research to create a practical handbook tailored for the QA discipline – a book written by Quality Assurance professionals, for Quality Assurance professionals.
A key factor within Quality Assurance is that there are distinct differences in company data integrity policies and training, in what defines data quality and data integrity, organizational unit responsibilities, data integrity challenges and information needs, and in the use of electronic systems vs. paper-based systems to collect scientific data.
Regardless of whether your system is electronic, paper-based, or hybrid, and regardless of the specific regulatory mandates of your area, this book will be your go-to reference on data integrity principles and regulations, data governance, specific auditing tips, and much more that you can apply not only within your organization, but also throughout your Quality Assurance career.
Table of Contents
Chapter 1. What Is Data Integrity and Data Quality?
Chapter 2: Where Is It Written?
Chapter 3. Data Integrity Principles
Chapter 4. Roles, Responsibilities, and Stakeholders
Chapter 5. Data Governance, Classification, and Risk
Chapter 6. Data Collection, Metadata, and Audit Trails
Chapter 7. Data Integrity Challenges – Questions to Consider
Chapter 8. What Does Data Integrity Look Like?
Chapter 9. Training for Data Integrity Awareness
Chapter 10. Audit Strategies for Assessing Data Integrity
Chapter 11. The Future of Data Integrity
Appendix A. Regulations and Guidelines
Glossary
List of Figures and Tables
Index
About SQA
SQA is an association of over 2,500 professionals who are dedicated to implementing Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), and Good Pharmacovigilance Practice (GVP) across industry, government, academia, and consulting. Learn more at SQA.org.
But what defines data integrity, how does it differ from data quality, and how does it vary between regulations? What are the data integrity requirements specific to Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), Good Pharmacovigilance Practice (GVP), and other areas in regulated life science? What are specific, practical approaches to assessing data integrity?
After deep discussion surrounding these questions, leaders from the Society of Quality Assurance (SQA) saw the need to examine data quality and data integrity within the specific context of the QA profession. They collected their findings, takeaways from many discussions, and months of research to create a practical handbook tailored for the QA discipline – a book written by Quality Assurance professionals, for Quality Assurance professionals.
A key factor within Quality Assurance is that there are distinct differences in company data integrity policies and training, in what defines data quality and data integrity, organizational unit responsibilities, data integrity challenges and information needs, and in the use of electronic systems vs. paper-based systems to collect scientific data.
Regardless of whether your system is electronic, paper-based, or hybrid, and regardless of the specific regulatory mandates of your area, this book will be your go-to reference on data integrity principles and regulations, data governance, specific auditing tips, and much more that you can apply not only within your organization, but also throughout your Quality Assurance career.
Table of Contents
Chapter 1. What Is Data Integrity and Data Quality?
Chapter 2: Where Is It Written?
Chapter 3. Data Integrity Principles
Chapter 4. Roles, Responsibilities, and Stakeholders
Chapter 5. Data Governance, Classification, and Risk
Chapter 6. Data Collection, Metadata, and Audit Trails
Chapter 7. Data Integrity Challenges – Questions to Consider
Chapter 8. What Does Data Integrity Look Like?
Chapter 9. Training for Data Integrity Awareness
Chapter 10. Audit Strategies for Assessing Data Integrity
Chapter 11. The Future of Data Integrity
Appendix A. Regulations and Guidelines
Glossary
List of Figures and Tables
Index
About SQA
SQA is an association of over 2,500 professionals who are dedicated to implementing Good Clinical Practice (GCP), Good Laboratory Practice (GLP), Good Manufacturing Practices (GMP), and Good Pharmacovigilance Practice (GVP) across industry, government, academia, and consulting. Learn more at SQA.org.
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Data Integrity: The Science, The Regulations, The Use
Data Integrity: The Science, The Regulations, The Use
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$150.00
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Product Details
| BN ID: | 2940184366869 |
|---|---|
| Publisher: | Society of Quality Assurance Learning Foundation |
| Publication date: | 04/08/2025 |
| Series: | SQA Learning Foundation Educational Books , #1 |
| Sold by: | Barnes & Noble |
| Format: | eBook |
| File size: | 2 MB |
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