ASSURING DATA INTEGRITY LIFE SCIENCES FOR. Edited by Siegfried Schmitt.
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1 ASSURING DATA INTEGRITY FOR LIFE SCIENCES Edited by
2 CONTENTS THE DATA INTEGRITY ISSUE SECTION 1 INTRODUCTION 3 2 HISTORY OF DATA INTEGRITY IN THE LIFE SCIENCES James P. Stumpff Analytical Data Manufacturing Data Clinical Data Post Marketing Surveillance Data 3 DATA INTEGRITY REGULATORY ENFORCEMENT iii
3 iv Assuring Data Integrity for Life Sciences 4 CLINICAL TRIAL DATA INTEGRITY ASSESSMENTS Yingying Liu and s THE PREVENTING DATA INTEGRITY PROBLEMS SECTION 5 MANAGEMENT STRATEGIES FOR DATA INTEGRITY Ronald F. Tetzlaff Perspectives on Data Integrity Regulatory Priorities have Refocused on Data Integrity Key Data Integrity Concepts (A Few Management Reminders) Five Strategies for Preventing Data Integrity Lapses Five Strategies for Detecting Data Integrity Lapses Summary and Conclusion Appendix: Internet Sources of Information on Data Integrity 6 DATA INTEGRITY CONSIDERATIONS IN AUTOMATED SYSTEMS Joseph Liscouski What is Laboratory Automation? Why is Automation Important in Laboratory Work? It is All About the Process Types of Laboratory Automation Implementations Roles and Responsibilities in Method Conversion Summary 7 CONTROLS TO ENSURE LABORATORY DATA INTEGRITY R.D. McDowall Data Integrity Concerns in GXP Regulated Laboratories
4 Contents v Laboratory Data Versus Production Information Scope of Laboratory Instruments and Systems Data Integrity Issues with a Networked Chromatography Data System Improving Laboratory Data System Design Summary 8 DATA INTEGRITY IN THE LABORATORY Jeanne Moldenhauer What are Data? Requirements for Data Integrity Data Pedigree Regulatory Expectations for Data Integrity Difficulties in Having Complete Data Evaluating Data Integrity in the Laboratory Triggers for Checking Data Integrity in the Laboratory The Effect of Personnel Behavior on Data Integrity Conclusion 9 DATA INTEGRITY PRACTICAL ASPECTS FROM AN INSTRUMENT SUPPLIER S PERSPECTIVE Christoph Jansen The Dream The Reality Strategies for a Simplified Data Integrity Process Paper vs. Paperless Laboratory Data Flow Approve Results in the Electronic Data Flow Active Directory Drop-at-Cursor -Transfer Who pays for this? ROI Considerations, Payback Time Customer Feedback Conclusion
5 vi Assuring Data Integrity for Life Sciences 10 DATA LIFE CYCLE CONSIDERATIONS FOR DATA INTEGRITY IN AUTOMATED SYSTEMS Joseph Liscouski Product Retirement and Replacement The Potential Impact of Data Interchange Standards on Data Life Cycles and Integrity 11 THE DATA INTEGRITY LIFE CYCLE RISKS AND MITIGATION David Stokes A Data Life Cycle Approach Data Life Cycle Complexity Regulated Companies Data Life Cycle Responsibilities Data and Records The Data Life Cycle Data Acquisition Data Entry Data Storage Data Editing Data Processing Data Copying Data Delete Data Move System Level Data Life Cycle Processes Data Archiving Data (System) Backup Data (System) Restore Data Migration Example of Data Life Cycle Modelling Overview Batch Processing Time Mid-point ph Particle Size Distribution PLC/SCADA System LIMS ERP System Is it Worth It?
6 Contents vii 12 INCORPORATING DATA INTEGRITY INTO THE QUALITY SYSTEM Roles and Responsibilities The Data Life Cycle Ownership The Data Life Cycle A Risk Based Approach Data Governance Preventing Data Integrity Problems Strategies to Ensure Data Integrity Preventing Data Integrity Problems The Role of Management Culture in Assuring Data Integrity Preventing Data Integrity Problems Controls to Ensure Data Integrity Covering Manual Observations, Hybrid and Electronic Systems Preventing Data Integrity Problems The Cloud Preventing Data Integrity Problems Data Integrity Audits Preventing Data Integrity Problems Documentation and Archive Reference 13 BIG DATA Magdalena Kurpierz Overview Over the Advantages of Big Data for the Life Science Industry Big Data Computerized System Requirements for the Regulated Life Science Industry Big Data Challenges in the Regulated Life Science Industry Big Data and Data Integrity Principles Conclusion 14 DATA REPRODUCIBILITY AND DATA QUALITY Joseph Liscouski The Cost of Bad Data Primary Causes for Irreproducible Experiments Recommendations for Improving Laboratory Work
7 viii Assuring Data Integrity for Life Sciences Electronic Record Keeping Approaches to Resolving both Reproducibility and Data Quality Issues 15 A BURDEN WORTH BEARING Alicia Pruett APPENDIX DATA LIFE AUDIT AIDE MEMOIRE Training to Assure Personnel are Aware of the Correct Practice Data Integrity Governance System Data Integrity Controls Verification of Data Integrity Glossary Index
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