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.

Contenu
Preface; Glossary, Abbreviations and Data Integrity Terms;How to Use This Book and an Introduction to Data Integrity; How Did We Get Here?; The Regulators' Responses; What Is Data Governance?; A Data Integrity Model; Roles and Responsibilities in a Data Governance Programme; Data Integrity Policies, Procedures and Training; Establishing and Maintaining an Open Culture for Data Integrity; An Analytical Data Life Cycle; Assessment and Remediation of Laboratory Processes and Systems; Data Integrity and Paper Records; Blank Forms and Instrument Log Books; The Hybrid System Problem; Get Rid of Paper: Why Electronic Processes are Better for Data Integrity; Data Integrity Centric Analytical Instrument Qualification and Computerised System Validation; Validating Analytical Procedures; Performing an Analysis; Second Person Review; Record Retention; Quality Metrics for Data Integrity; Raising Data Integrity Concerns; Quality Assurance Oversight for Data Integrity; How to Conduct a Data Integrity Investigation; Data Integrity and Outsourcing; Data Integrity Audit Aide Memoire; Subject Index