Basic Validation Statistics for Non - Statisticians
Alan has over 30 years of experience in the medical device industry, both in basic research and in quality assurance. Alan spent 31 years at Abbott Laboratories. For the first 16 years as part of diagnostics R&D, he developed recombinant proteins used in diagnostics tests, received three US patents and published numerous papers and abstracts. Alan then transitioned to a quality assurance role where in both the Abbott Diagnostics and Abbott Molecular divisions, he was responsible for quality assurance for new product development, on-market product support and operations.
Alan’s quality assurance experience extends from design control, change control, risk management, CAPA, process and test method validation and statistics. He has been lecturing on these topics worldwide for over 10 years.
Alan retired from Abbott in 2018 and now runs Design Quality Consultants, providing training, workshops and seminars in many areas of quality assurance.
Alan received his BS degree in Microbiology from the University of Michigan and his MS degree in Molecular Biology and Immunochemistry from the University of Illinois.
In this program, we will discuss the common statistics tools and techniques used in validation. Through real world examples and interactive exercises, we will demonstrate the basic concepts of statistics and how to apply them to your validation projects. Discussion will center around measures of variance, sample distributions, and expressions of variance. The session will conclude with a discussion of the concept of process capability and using process capability to set acceptance criteria for validation.
Areas Covered
- Introduction
- What is Statistics
- Why do you need Statistics for Validation?
- Regulatory expectations - The Concept of Variance (and why it is important)
- Sources of variance
- Measuring variance
- Normal and non-normal distributions
- Measuring Variance - Expressing Variance
- Variance
- Standard deviation
- Interactive exercise: Measuring Variance
- Coefficient of variation - Process Capability
- Can your system do what you want (need) it to do?
- Measuring capability
- Using capability to set acceptance criteria for validation - Conclusion and Discussion
Who Should Attend
Validation engineers, R&D scientists, quality professionals and production personnel involved in validation activities.
Why Should You Attend
This webinar will be useful to validation engineers, R&D scientists, quality professionals and production personnel involved in validation activities. Validation professionals in both medical device and pharmaceutical industries will benefit.
A basic understanding of statistics is critical to evaluate a validation protocol prior to execution and to correctly interpret the data during and after the run.
Topic Background
A basic understanding of statistics describing variation and how to measure it is fundamental to setting up a good validation program.
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$200.00
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