Six Sigma in the Pharmaceutical Industry: Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics, 1st Edition (Paperback) book cover

Six Sigma in the Pharmaceutical Industry

Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics, 1st Edition

By Brian K. Nunnally, John S. McConnell

CRC Press

220 pages | 87 B/W Illus.

Purchasing Options:$ = USD
Paperback: 9781420054392
pub: 2007-06-13
SAVE ~$29.00
Hardback: 9781138445772
pub: 2017-07-27
SAVE ~$43.00
eBook (VitalSource) : 9780429146411
pub: 2007-06-13
from $72.50

FREE Standard Shipping!


The pharmaceutical industry is under increasing pressure to do more with less. Drug discovery, development, and clinical trial costs remain high and are subject to rampant inflation. Ever greater regulatory compliance forces manufacturing costs to rise despite social demands for more affordable health care. Traditional methodologies are failing and the industry needs to find new and innovative approaches for everything it does.

Six Sigma in the Pharmaceutical Industry: Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics is the first book to focus on the building blocks of understanding and reducing variation using the Six Sigma method as applied specifically to the pharmaceutical industry. It introduces the fundamentals of Six Sigma, examines control chart theory and practice, and explains the concept of variation management and reduction. Describing the approaches and techniques responsible for their own significant success, the authors provide more than just a set of tools, but the basis of a complete operating philosophy. Allowing other references to cover the structural elements of Six Sigma, this book focuses on core concepts and their implementation to improve the existing products and processes in the pharmaceutical industry. The first half of the book uses simple models and descriptions of practical experiments to lay out a conceptual framework for understanding variation, while the second half introduces control chart theory and practice. Using case studies and statistics, the book illustrates the concepts and explains their application to actual workplace improvements.

Designed primarily for the pharmaceutical industry, Six Sigma in the Pharmaceutical Industry: Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics provides the fundamentals of variation management and reduction in sufficient detail to assist in transforming established methodologies into new and efficient techniques.

Table of Contents

The Enormous Initial Mistake


The Ultimate Curse

A Metamorphosis is Possible

The Enormous Initial Mistake

The Origins of Six Sigma


Understanding and Reducing Variation

Understanding the Sigma Level

Gaining Greatest Leverage

Some Structural Elements of Six Sigma



In the Beginning…

The Advent of Mass Production

Illustrating Variation


Is This Understanding Important?

Stabilize First

…Then Improve the Process

The First Principle

Deming Polishes the Diamond

Deming’s First Opportunity

Deming’s Second Opportunity

The Deming Approach

Limits to Knowledge


How Do You Know?

Improving the Analysis

Detecting Instability Using Control Charts

Chemical Example from the Pharmaceutical Industry

Biological Example from the Pharmaceutical Industry

Compliance Example from the Pharmaceutical Industry

The Attributes or Binary Mindset

Action and Reaction

The Nelson Funnel (or Pen Dropping) Experiment

Results of the Exercise

Service Elements of the Pharmaceutical Industry

Close Enough; … Or On Target?

Make More…Faster!

The Dice Experiment

Little’s Law

Quality Control Considerations

Six Sigma and First Pass Yield

Pharmaceutical Case Study — Increasing Output

Case Studies

Biological Case Study — Fermentation

Parenterals Operation Case Study

Safety Case Study

Improved Control of Potency

Deviations in a Pharmaceutical Plant

The Camera Always Lies

In God We Trust…

How Exact is Exact?

Giving Data Meaning

Service Industries

Keeping It Simple

Time — The First Imperative

Pattern and Shape

The DTLF Approach

Why Use Control Charts?

Why Use Control Charts?

Types of Data

Control Charts Advantages

Developing Control Limits

Average and Range Control Charts

Constructing an Average and Range Control Chart

How the Formulae Work

Why the Chart Works

Sub-Group Integrity

Serial Sampling — Loss of Sub-Group Integrity and Over-Control

Origins and Theory

Developing Control Limits

Making the Control Chart

Control Limits Vary with Sub-Group Size

Specifications and Control Limits

Why Use Averages?

Interpreting the Charts

The Final Word

Appendix A Origins of the Formulae

Charts for Individuals

Constructing the Charts

Interpreting Individual Point and Moving Range Charts



Pattern and Shape


Practical Considerations

What Do the Statistics Mean?

Rational Sub-Groups

The Blessing of Chaos

Stabilizing a Process

Causal Relationships

Process Control

Eliminate Waste

What to Measure and Plot

Appendix A Example Operational Directive

Improving Laboratories

Production Lines are the Laboratory’s Customers

Types of Methods

Variability Estimates

Understanding Capability

Accuracy vs. Precision

Use of Validation Data to Determine Laboratory Precision

Reducing Variability — More Is Not Always Better

Appendix A Implementing a Laboratory Variability Reduction Project

Appendix B Implementing a Blind Control Study

Beyond Compliance

We Have Met the Enemy, and He is Us

Appendix 1

Factors for Estimating s from and s¯

Appendix 2

Factors for x¯ and R Control Charts

Appendix 3

Factors for x¯ and s Control Charts

Subject Categories

BISAC Subject Codes/Headings:
MATHEMATICS / Probability & Statistics / General
MEDICAL / Pharmacology
MEDICAL / Biostatistics
SCIENCE / Chemistry / General