Statistical Design and Analysis of Stability Studies

Statistical Design and Analysis of Stability Studies

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The US Food and Drug Administration's Report to the Nation in 2004 and 2005 indicated that one of the top reasons for drug recall was that stability data did not support existing expiration dates. Pharmaceutical companies conduct stability studies to characterize the degradation of drug products and to estimate drug shelf life. Illustrating how stability studies play an important role in drug safety and quality assurance, Statistical Design and Analysis of Stability Studies presents the principles and methodologies in the design and analysis of stability studies. After introducing the basic concepts of stability testing, the book focuses on short-term stability studies and reviews several methods for estimating drug expiration dating periods. It then compares some commonly employed study designs and discusses both fixed and random batch statistical analyses. Following a chapter on the statistical methods for stability analysis under a linear mixed effects model, the book examines stability analyses with discrete responses, multiple components, and frozen drug products. In addition, the author provides statistical methods for dissolution testing and explores current issues and recent developments in stability studies. To ensure the safety of consumers, professionals in the field must carry out stability studies to determine the reliability of drug products during their expiration period. This book provides the material necessary for you to perform stability designs and analyses in pharmaceutical research and more

Product details

  • Hardback | 352 pages
  • 152.4 x 236.2 x 25.4mm | 589.67g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 11 black & white illustrations
  • 1584889055
  • 9781584889052
  • 1,864,184

Table of contents

INTRODUCTION Background Regulatory Requirements Stability Testing Practical Issues Aim and Scope of the Book ACCELERATED TESTING Chemical Kinetic Reaction Statistical Analysis and Prediction Examinations of Model Assumptions An Example Discussion EXPIRATION DATING PERIOD Basic Concepts Shelf-Life Estimation Other Methods Concluding Remarks STABILITY DESIGNS Basic Design Considerations Long-Term Stability Designs Design Selection Discussion STABILITY ANALYSIS WITH FIXED BATCHES Preliminary Test for Batch Similarity Minimum Approach for Multiple Batches Multiple Comparison Procedure for Pooling Batches Example Discussion STABILITY ANALYSIS WITH RANDOM BATCHES Linear Regression with Random Coefficients Random Batch Effect and Other Fixed Effects Shelf-Life Estimation with Random Batches Comparison of Methods for Multiple Batches Determining Shelf Life Based on the Lower Prediction Bound Concluding Remarks STABILITY ANALYSIS WITH A MIXED EFFECTS MODEL Linear Mixed Effects Model Restricted Maximum Likelihood Estimation Restricted Maximum Likelihood Estimation The EM Algorithm Procedure Example Discussion STABILITY ANALYSIS WITH DISCRETE RESPONSES Binary Data without Batch-To-Batch Variation The Case of Random Batches Testing for Batch-To-Batch Variation Example Ordinal Responses Concluding Remarks STABILITY ANALYSIS WITH MULTIPLE COMPONENTS Basic Idea Models and Assumptions Shelf-Life Determination Example Discussion STABILITY ANALYSIS WITH FROZEN DRUG PRODUCTS Two-Phase Stability Study Stability Data and Model An Example Discussion STABILITY TESTING FOR DISSOLUTION USP/NF Dissolution Testing Dissolution Profile Testing Statistical Methods for Assessing Similarity Numerical Examples Concluding Remarks CURRENT ISSUES AND RECENT DEVELOPMENTS Scale-Up and Postapproval Changes Storage Conditions in Different Climatic Zones Optimal Designs in Stability Studies Current Issues in Stability Analysis SAS Programs for Stability Analysis APPENDIX A: Guidance for Industry APPENDIX B: SAS Macro Files for STAB System for Stability Analysis REFERENCES INDEXshow more

About Shein-Chung Chow

Duke University School of Medicine, Durham, North Carolina,show more