1st Edition

Six Sigma in the Pharmaceutical Industry Understanding, Reducing, and Controlling Variation in Pharmaceuticals and Biologics

    220 Pages 87 B/W Illustrations
    by CRC Press

    220 Pages
    by CRC Press

    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.

    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


    John S. McConnell, Brian K. Nunnally