Stability Studies and Estimating Shelf Life with Regression Models
Steven Wachs Overview:
This webinar discusses the steps to set up a stability study and analyze the results to estimate the product's shelf life. The use of regression models to model the relationship between the response variable(s) and time are presented. Models useful for describing non-linear degradation over time are also presented. Additionally, methods for handling non-normal response data are also discussed. Finally, the use of accelerating variables to shorten the study time and the models required are introduced. The webinar includes several examples to illustrate the methods discussed.
Why you should Attend:
The webinar will provide useful methods and techniques for conducting a stability study and analyzing the resulting data for the purpose of estimating shelf life. Participants should be able to immediately apply the methods presented. An accurate shelf life is critical to reduce risk of defective products being utilized.
Areas Covered in the Session:
- Planning a Stability Study
- Determining Performance Specifications
- Defining & Determining Shelf Life
- Confidence Levels
- Life Data Analysis Approach for Determining Shelf Life
- Life Data Analysis with Accelerated Aging
- Regression Modeling (Linear and Non-Linear) to Assess Stability/Shelf Life
- Pooling Batches for Stability Studies
- Validating Model Assumptions
- Handing Non-Normal Response Data
- Introduction to Accelerated Stability Testing
- Issues & Guidelines
Who Will Benefit:
- R&D Personnel
- Product Development Personnel
- Quality Personnel
- Lab Testing Personnel
- Operations / Production Managers
- Quality Assurance Managers, Engineers
- Process or Manufacturing Engineers or Managers
- Program or Product Managers
Speaker Profile
Steve Wachs has 30 years of wide-ranging industry experience in both technical and management positions. Steve has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Steve is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Steve consults and provides workshops in industrial statistical methods worldwide. He also supports Integral Concepts’ Litigation / Expert Witness practice with data analysis.
Steve possesses an M.A. in Applied Statistics from University of Michigan (Ann Arbor), an M.B.A. from the Katz Graduate School of Business, University of Pittsburgh, and a B.S. in Mechanical Engineering from the University of Michigan (Ann Arbor).