This webinar will discuss setting up statistically justified sampling plans for process validation. The discussion will also involve using the sampling plan to set acceptance criteria for process validation. Setting acceptance criteria for test method validation will also be presented.
WHY SHOULD YOU ATTEND?
All companies in the pharmaceutical and medical device space are required to implement formal and statistically justified sampling plans and acceptance criteria for validation. Many companies do not have dedicated statistics departments, so it is up to the validation or quality engineer to develop sampling plans. This training will be a simple step-by-step method of developing statistically justified sampling plans and acceptance criteria.
This webinar will discuss methods for setting up sampling plans depending on the risk profile of the final product or production step. It will go into using the sampling plan to set statistically justified acceptance criteria for the validation. Also presented will be setting confidence levels and spreading that confidence level out over multiple runs. Setting statistically justified acceptance criteria for test method validation will also be discussed.
AREA COVERED
- What is Sampling
- Sampling is the ability to make a quality determination on a large number of things without direct examination of each thing
- Validation Sampling
- Not the same as lot acceptance sampling
- Differences
- Setting up a Validation Sampling Plan
- Pre-Sampling Determinations
- Steps to setting up sampling plans
- Variables vs. Attributes Sampling Plans
- The Concept of Acceptance Criteria
- Variance, How much is too much
- How to measure variance and why
- Use of Process Capability
- The concept of process capability
- Cp vs CpK
- How to use process capability to set acceptance criteria
WHO WILL BENEFIT?
- QA professionals
- Technical scientists
- Production staff
- Statisticians involved in validation
from Medical Device and Pharmaceutical Companies
All companies in the pharmaceutical and medical device space are required to implement formal and statistically justified sampling plans and acceptance criteria for validation. Many companies do not have dedicated statistics departments, so it is up to the validation or quality engineer to develop sampling plans. This training will be a simple step-by-step method of developing statistically justified sampling plans and acceptance criteria.
This webinar will discuss methods for setting up sampling plans depending on the risk profile of the final product or production step. It will go into using the sampling plan to set statistically justified acceptance criteria for the validation. Also presented will be setting confidence levels and spreading that confidence level out over multiple runs. Setting statistically justified acceptance criteria for test method validation will also be discussed.
- What is Sampling
- Sampling is the ability to make a quality determination on a large number of things without direct examination of each thing
- Validation Sampling
- Not the same as lot acceptance sampling
- Differences
- Setting up a Validation Sampling Plan
- Pre-Sampling Determinations
- Steps to setting up sampling plans
- Variables vs. Attributes Sampling Plans
- The Concept of Acceptance Criteria
- Variance, How much is too much
- How to measure variance and why
- Use of Process Capability
- The concept of process capability
- Cp vs CpK
- How to use process capability to set acceptance criteria
- QA professionals
- Technical scientists
- Production staff
- Statisticians involved in validation
from Medical Device and Pharmaceutical Companies
Speaker Profile
Alan M Golden has over 30 years of experience in the medical device industry, both in basic research and 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 wherein 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 …
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