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Sampling: How Much Is Enough for Process Validation?
Does the US Food and Drug Administration (FDA) ever make a mistake? In the Preamble to the Quality System Regulation (21 CFR 820, Comment 85), they addressed sampling for Process Validation. Comment 85 says:
“The requirement for testing from the first three production lots or batches has been deleted…. The number three is, however, currently considered to be the acceptable standard.”
The FDA now admits that this guidance on a sample size of three is NOT statistically valid. They wish they could delete Comment 85 from the Preamble; however, to do this would take an act of the US Congress!
This webinar is targeted to professionals concerned with a specific application of valid statistical techniques to satisfy Process Validation requirements of the FDA’s Quality System Regulation. Sampling a product or process and measuring a quality characteristic is an efficient way to make an inference about the quality of all products or the entire process. Simply put, if it is too expensive to measure everything, then you would be wise to sample and measure a subset. If you decide to sample, then comes the age-old question: “How much is enough?”
This fast-paced webinar will cover the details of application without the burden of statistical complexity. Analysis results from popular statistical software programs will be illustrated. The presenter’s “keep-it-simple” approach will avoid statistical complexity – participants do not need to have a background in statistics.
While the subject of this webinar is a key input to developing Acceptance Sampling Plans, it will not formally cover that subject. Acceptance Sampling Plans may be formally covered in future webinars.
The key to establishing Sample Size is to quantify the risks involved in making a decision on the quality of a product or process. At the end of this webinar, participants will be able to:
- Create a risk-based Sampling Plan for a new production process
- Apply fundamental statistical methods and tools for analyzing a production process
- Describe the factors that influence sample size selection
- Formulate risk-based decisions on the quality of a product or process
- Express the risk involved in a data-based decision
- Regulatory Context
- Quality System Regulation 21 CFR 820 and Preamble Comments
- GHTF Guidance for Process Validation
- Significant Trends and Warning Letters
- Demonstration of Best Practices
- Estimating Process Capability
- Graphical Tools
- Common Pitfalls
- Designing a Sampling Plan for New Production Processes
- A Checklist Approach
- Applying Statistical Methods & Tools
- Sample Size Considerations
- Applying Valid Statistical Software
- Expressing a Risk-Based Decision
- Question and Answer Period
Who should attend:
This webinar is targeted to professionals concerned with the application of Sampling to meet the Process Validation requirements of the FDA's Quality System Regulation. The content should have great value to involved with: process development; manufacturing, process, and quality engineering; operations; quality assurance; quality control; and regulatory compliance. Through this overview of sampling, managers and members of the leadership team would see how value is added to a product or process.
There are no prerequisites for this webinar. No background in statistics is necessary.
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Peter Knepell, PhD
March 22, 2019
14.30 - 16.30 (120 min) CET (Central European Time)
Price (excl. local VAT):
250 Euro for the first participant.
115 Euro for the following participants on the same registration and invoice.
Course handouts (PDF) and certificate of attendance is included.
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Cancellation policy for webinars:
Cancellations received less than 24 hours before the webinar will be charged 50% of the course fee.
If you for any reason is unable to attend, substitution is always possible and preferred. All cancellations and/or substitutions must have been communicated with and confirmed by us.
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Cancellation of webinars:
Courses may be cancelled by the organizer if bookings fail to reach minimum numbers. In such circumstances charged course fees will be refunded, credited, or granted to attend another course for the same value.