Lynn Torbeck

TREND ANDOUT-OF-TRENDANALYSIS FOR

PHARMACEUTICALQUALITY AND

MANUFACTURINGUSING MINITAB

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Trend and Out-of-Trend

Analysis

For Pharmaceucial and Quality

Manufacturing Using Minitab

Lynn D.Torbeck

PDABethesda, MD, USA

DHI Publishing, LLCRiver Grove, IL, USA

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ISBN: 1-933722-90-8Copyright 2015 Lynn TorbeckAll rights reserved.

All rights reserved. This book is protected by copyright. No part of it maybe reproduced, stored in a retrieval system or transmitted in any means,electronic, mechanical, photocopying, recording, or otherwise, withoutwritten permission from the publisher. Printed in the United States ofAmerica.

Where a product trademark, registration mark, or other protectedmark is made in the text, ownership of the mark remains with the lawfulowner of the mark. No claim, intentional or otherwise, is made byreference to any such marks in the book. Websites cited are current at thetime of publication. The author has made every effort to provide accuratecitations. If there are any omissions, please contact the publisher.

While every effort has been made by the publisher and the authors toensure the accuracy of the information expressed in this book, theorganization accepts no responsibility for errors or omissions. The viewsexpressed in this book are those of the editors and authors and may notrepresent those of either Davis Healthcare International or the PDA, itsofficers, or directors.

This book is printed on sustainable resource paper approved by the Forest StewardshipCouncil. The printer, Gasch Printing, is a member of the Green Press Initiative and all paperused is from SFI (Sustainable Forest Initiative) certified mills.

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CONTENTS

Preface vii

Introduction ix

1 DATA COLLECTION 1The Data Collection Process 2Operational Definitions 3Training 3Protocols 3Reportable Values 4Good Data Collection 4Negligence and Fraud 5Testing into Compliance 8Data Auditing by Quality Control 10Data Inspection 11Designing Data Collection Forms 11Data Symmetry 13Data Bases 13Example 15

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2 DATA CONCEPTS 17Measurement Scales 18Levels of Results and Data 20Collecting Data so Statisticians can use them Later 24Significant Digits and Rounding 24

3 DATA VARIABILITY 27Nature of Variability 28Classic Bead Box 29Sampling 33Sample Size 37Sampling Plans 39Sources of Variability 40Categories of Sources of Variability 42Techniques for Reducing Variation 43

4 DATA SUMMARIES 47Summaries vs. Individuals 48Jotting Down Summaries 48Ranking the Data 50Finding Summary Numbers 51Measure of Center 52Percents and Percentiles 53Measures of Variability 54Quartiles 55Reporting Summary Numbers 56Relationship to Measurement Scales 57

5 DATA PRESENTATION 59Four Presentations 61Text 61Lists and Tables 62Data Lists 63Data Tables 64TwoWay Tables 64Tables for Analysis 66Graphs 70Good Graphics Design 71Suggestions for Constructing Graphs 71Suggestions for Hand-drawn Graphs 73

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OneVariable Graphs 73Bar Charts 73Histograms 74Shape of the Data 77Pareto Plots 79Defect Location Plots 80Outliers and Outlier Management 81

6 DISTRIBUTION ANALYSES 91Frequency Distributions 92Normal Distribution 92Standard Normal 95Probability Plots 97Adding Normals 99Subtracting Normals 100Weight to Run Fallacy 101Truncated Normals 102Log Normal Distribution 104Exponential Distribution 106Box-Cox Transformation 108Johnson Transformation 113Individual Distribution Identification 114

7 DATA TRENDING 117Background 119Scope of the Topic 119Philosophical Basis for Trending 122Changes that can Occur in a Data Series 123Engineering Control 126Statistical Control 126Trends 126Neutral Trends 127Beneficial Trends 127Adverse Trends 128OOT 129Neutral OOT 129Beneficial OOT 129Adverse OOT 129Types of Adverse OOT 130Trend Analysis 134Trend Fitting 134

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Trend Limits 135Summary 135Conclusion 143

8 OOS, OOT,OOC,AND OOSC 145

9 FDAWARNING LETTERS 151

10 REFERENCES 157

Appendix A Control Charts 163

Appendix B Tolerance Intervals Parametric 169

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PREFACE

This book is for pharmaceutical professionals working in productdiscovery, development, manufacturing, quality assurance andquality control.

The need for a trend analysis book is justified by the continuedinterest in presentations and discussions both public and private.Philosophies and definitions have been proposed and presented,but there is not yet a widely accepted clearly defined approach bythe industry that lends itself to consistent interpretation anduniform application.

Like other topics, (i.e., assay and process validation), trendanalysis is good business and good science.

Trend analysis should not be done only to meet a minimumregulatory expectation but to establish base line reference trends forkey processes, products and business variables. These referencetrends are then used to identify out-of-out trend data and eventsand initiate root cause investigations.

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That the FDA is concerned about current and future industrypractice for trending is obvious and can be measured by the volumeof investigators observations. See Chapter 9.

It is hoped that this book will contribute to an industry/regulatory dialog and consensus that will serve and benefit allstakeholders, especially the group for whom we serve, the patients.

LDT April 30, 2015

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INTRODUCTION

The essential message of this book can be illustrated with aneveryday example. My wife Joyce and I have lived in a condo forthe last 15 years or so. It has an assigned parking space. Love it inthe winter time. Next to our space is a neighbors space. For as longas I can remember, he has always parked straight in and parallel tothe painted strips. Unlike me, where every attempt is a unique heartpounding event.

He had never varied, was always perfectly parallel, until oneday he wasnt. I was startled to say the least. This had neverhappened before. Now of course, this is not a big deal in the grandscheme of life, but it did raise questions in my mind. Was he ill andsomeone else parked the car? Was he in a big hurry because of anemergency and he didnt take the usual time to straighten out?

Why was I surprised? Because it was a change from his typicalexpected and established pattern. He departed from his historicalbaseline. Something changed for that parking event and mycuriosity was raised. What changed to be out of the expected andestablished norm? I didnt ask, but wanted to.

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Another classic is the mother with eyes in the back of her headso to speak. She knows her house and her children so well that thesmallest noise or object out of place sets off alarm bells in her head.Something is atypical or out-of-typical (OOT), from the expectednorm. Get out of the candy jar.

Lets now define an established expected pattern of data orevents as the trend. Then my neighbors established trend that Iexpect to see was that he was always perfectly parallel to the strips.His one nonparallel event was out of my expectation of hisestablished trend.

Thus in this book, a trend is a series of events or data collected,generally over time, that has an established and expected patternthat repeats. It is the typical pattern or baseline. The trend can beobserved, historical, or it can be based on theoretical models. Anydeparture from the trend is then an unexpected OOT event. It isatypical and begs for investigation.

Analysis can be as simple as a line plot over time to identify thetrend, or as complicated as necessary to gain understanding. If atrend cant be established then an out-of-trend event or data doesntexist either. To summarize:

Trend is the data or events we expect to see.

Out-of-Trend is the events or data we did not expect to see.

Chapter 7 presents trend and OOT definitions with discussionsand example graphics. Readers with some statistical backgroundcan proceed to that chapter.

Chapters 16 present a basic introduction to data and simple gra-phical analysis for those new to the topic or who wish a brief review.

Chapter 8 proposes terminology to clarify the use of the wordcontrol in the context of OOT, out-of-specification (OOS), andout-of-statistical control (OOSC).

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Chapter 9 reproduces outtakes from Food and DrugAdministration (FDA) warning letters, plant