2-day In-person Seminar

FDA Based Guidelines on Statistical Sampling Plans

By Steven Walfish

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Group participations

Overview

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Course "FDA Based Guidelines on Statistical Sampling Plans" has been pre-approved by RAPS as eligible for up to 12 credits towards a participant's RAC recertification upon full completion.
Overview:

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.


Who will benefit:
This course is developed to provide valuable assistance to all regulated companies that need to understand their processes including companies: The employees who will benefit include:
Why you should attend:
This course will help you to use statistics correctly and minimize compliance risk.

Agenda


Day One
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

Lecture 2: 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
Lecture 3: 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

Lecture 4: 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 Two
Lecture 5: 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
Lecture 6: 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
Lecture 7: 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
Lecture 8: 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

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Group participations
Get fabulous discounts by participating in groups of two or more.
Send two attendees: Get a discount of 10%!
Send three to six attendees: Get a grand discount of 20%!
Send seven to 10 attendees: Get a great discount of 25%!
Send more than 10 attendees: Get a whopping discount of 30%!
To avail the above group discounts, all the participants should register by making a single payment

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Venue


Location: Singapore
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Hotel: Mandarin Orchard Singapore   333 Orchard Road, Singapore 238867    
Tel: (65) 6235 7788

Speaker


Steven Walfish

President, Statistical Outsourcing Services

Mr. Steven Walfish is the President of Statistical Outsourcing Services, a consulting company that provides statistical analysis and training to FDA regulated industries. Prior to starting Statistical Outsourcing Services, Mr. Walfish was the Senior Manager Biostatistics, Non-clinical at Human Genome Sciences in Rockville MD. Prior to joining HGS, Mr. Walfish was a Senior Associate at PricewaterhouseCoopers specializing in the pharmaceutical industry. Mr. Walfish was Manager of Non-Clinical Statistics at Chiron Diagnostics. Mr. Walfish brings over 20 years of industrial expertise in the development and application of statistical methods for solving complex business issues including data collection, analysis and reporting.

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