Statistics for Non-Statisticians Seminar

Presented by Global Compliance Panel

This seminar will be highly interactive and participative. Participants apply their learning of statistics to real-world example data sets. The program begins by providing a basic overview of the most common statistical tools and terms.

Course Description

Statistical tools and techniques are very commonly used to help measure and improve the quality of a firm's process and product. If statistical analysis is not properly performed and/or understood, a firm can run the risk of distributing the kind of product to the market that ultimately fails, resulting in lost time and money. And of course, with statistics, practice makes perfect. During this two-day HIGHLY interactive training program, participants will be given the opportunity to apply statistics learned to real-world example data sets! The program begins by providing a basic overview of the most common statistical tools and terms. The course covers the use of statistical software packages and the role of software in statistical analysis and statistical process control. Areas addressed include how to use statistics to properly trend data, support the annual product review, justify process changes and set product specifications. By the end of day two, course participants will have acquired the skills necessary to design a statistically sound sampling plan that helps them comply with FDA APR requirements. Throughout the duration of this intimate, hands-on course, participants will be able to interact with both an expert instructor and their peers.

Why should you attend:

This course will help you to use statistics correctly and minimize compliance risk.

Who will benefit:

Day 1 Schedule:

Lecture 1:

Introduction and Basic Overview of Common Statistical Tools

Exercise: Identify Participants' Statistical Experience and Course Goals

• Types of Data
  • Continuous versus discrete
  • Descriptive versus inferential
• Data Presentation and Graphics
• Normal Distribution
• Introduction to Hypothesis Testing
  • P-value
  • z-test
  • t-test
  • Chi-square
  • F-test
• Discuss applicable software packages for use:
  • Microsoft Excel - SAS
  • Mini-tab - JMP

Apply Statistics to Specification Setting

• Setting appropriate product specifications
• Determine FDA requirements for OOS results
• Determine how to best investigate OOS results
• Introduction to Interval Estimation
  • Confidence Interval
  • Tolerance Interval
• Outlier Analysis

Exercise: Setting Statistical Based Specifications

Regression analysis and variance components

• Correlation
• Linear models
• New Patient Rights
• Residual analysis
• Lack of fit
• Hazards of regression
• Multiple regression
• Non-linear regression (4-parameter models)
• Analysis of stability data including shelf life estimation

Implement Design of Experiments (DOE)

• Design experiments appropriately and effectively
• Ensure that experiments are reproducible
• Improve process capability by reducing variability
• Analysis of variance

Exercise: Mock Experimental Design

Day 2 Schedule:

Lecture 1:

Validate your Testing Methods using Statistics

• Analyze ICH guidelines (Q2A & Q2B)
• Ensure robustness and ruggedness of your method
• Develop protocols based on sound statistical methods
• Quantify validation characteristics:
  • linearity - range
  • accuracy - limit of detection (LOD)
  • precision - limit of quantitation (LOQ)
• Regression analysis and variance components
• Analysis of Stability data.

Exercise: Analysis of a Method Validation Study Including Protocol Development

Trending Analysis

• Define Statistical Process Control (SPC)
• Determine how SPC can be applied to and help your process
• Identify the benefits of using SPC
• Trend Analysis
• Comply with FDA Requirements for Process Analytical Technology (PAT)
• Define Process analytical technologies and identify related tools
• Identify the role statistics play in the PAT framework
• Comply with the FDA's 2004 PAT draft guidance requirements
• Process Analytical Technology

Exercise: Review and Critique a Sample SPC Control Chart

Design a Statistically Sound Sampling Plan

• Define different types of sampling
  • random
  • stratified
  • composite
• Create and justify your sampling plan
• Account for sampling and measurement error
• Determine the relationship between sample size, statistical precision, and statistical power

Exercise: Create a Mock Sampling Plan

Statistically Analyze Annual Product Review (APR) Data

• Examine statistical techniques relevant to APRs
• Use descriptive statistics to present the data
• Use graphs and plots effectively
• Interpret statistical data to identify trends and deviations

Exercise: Apply Learned Statistical Techniques to Real-World Data

Discussion: Wrap-up Question and Answer Session

Instructors Profile:

Steven Walfish

Mr. Steven Walfish brings is the founder and President of Statistical Outsourcing Services. He brings nearly 20 years of industrial experience providing statistical solutions to complex business problems. Mr. Walfish was Senior Manager Biostatistics, Nonclinical at Human Genome Sciences in Rockville MD. Mr. Walfish has held positions with PricewaterhouseCoopers, Chiron Diagnostics and Johnson & Johnson. Mr. Walfish holds a Bachelors of Arts in Statistics from the University of Buffalo, Masters of Science in Statistics from Rutgers University and an Executive MBA from Boston University.

More Seminar Information

Global Compliance Panel Summary This seminar will be highly interactive and participative. Participants apply their learning of statistics to real-world example data sets. The program begins by providing a basic overview of the most common statistical tools and terms. Delivery Method  Seminar Who Should Attend • Data Analysts • Research Scientists • Quality Professionals • Regulatory/Compliance Professionals • Laboratory Managers • HR Professionals • Project Managers • Design and Development Engineers • Software Engineers • Process Owners • Quality Engineers • Quality Auditors • Medical Affairs Professionals • Process Scientists/Engineers

All Date/Location Information