• Learning Track

    Pharmaceuticals

    This 4-day track provides participants with the foundation for effectively using statistical methods to validate a pharmaceutical process.

    It is appropriate for process engineers, R&D team members, and other quality professionals who need to understand how to use statistical tools for pharmaceutical processes.

    Explore the data analysis techniques necessary to understand product variation and defects, determine shelf life, assess if a process is capable of meeting specifications, and monitor the stability of a validated process.

    Statistical principles will be presented through examples and exercises ― all supported by Minitab Statistical Software.

    Schedule On-Site Training   Find Public Sessions
  • Days 1-4
  • Statistical Tools for Pharmaceuticals

    Manufacturing

    Learn to apply Minitab tools commonly used in the pharmaceutical industry. Develop sound statistical approaches to data analysis by understanding how to select the right tool for a given scenario and to correctly interpret the results of the analysis. Learn how to easily import data and export output.

    Learn the foundation for important statistical concepts for determining if a process mean is off target, whether two means are significantly different, and for demonstrating if a process change does not significantly affect a critical response. Develop the necessary skills to successfully evaluate and certify measurement systems. Understand how to utilize important capability analysis tools to evaluate your processes relative to internal and customer specifications. Learn how to evaluate a random sample of product from a lot to determine whether to accept or reject the entire lot.

    Understand how to apply DOE for process improvement. Learn how to use stability analysis for determining the shelf life of a product. All applications place emphasis on making good business decisions based upon the practical application of statistical techniques commonly used in the pharmaceutical industry.

    Topics include:

    • Importing and Formatting Data
    • Bar Charts
    • Histograms
    • Boxplots
    • Scatterplots
    • Power and Sample Size Determination
    • t-Tests
    • Equivalence Tests
    • Proportion Tests
    • Tolerance Intervals
    • Variables and Attribute Control Charts
    • Regression
    • One-Way ANOVA
    • Multi-Variable ANOVA
    • DOE
    • Attribute Agreement Analysis
    • Gage R&R
    • Attribute Acceptance Sampling
    • Capability Analysis for Normal and Nonnormal Data

    Prerequisite:

    None. This course can be used as a pre-requisite to Response Surface Designs and DOE in Practice.

By using this site you agree to the use of cookies for analytics and personalized content in accordance with our Policy.

OK