Validation Sampling Plans

Validation sampling plans need to be statistically justified, and the acceptance criteria that go with them have to stand up too. This 60-minute validation sampling plans webinar shows how to set both up for process validation.

You'll learn how validation sampling differs from lot acceptance sampling, what to decide before sampling, and the steps for building a plan based on the risk profile of the final product or production step. The session compares variables and attributes sampling plans and covers how to set confidence levels and spread them over multiple runs.

It then explains variance, process capability (Cp vs Cpk) and how to use them to set acceptance criteria, including for test method validation.

• Explain how validation sampling differs from lot acceptance sampling
• Set up a statistically justified sampling plan based on risk
• Choose between variables and attributes sampling plans
• Set confidence levels and spread them across multiple runs
• Measure variance and use Cp and Cpk to set acceptance criteria
• Set statistically justified acceptance criteria for test method validation

What is sampling

• Making a quality judgment about many items without examining each one

Validation sampling

• How it differs from lot acceptance sampling

Setting up a validation sampling plan

• Pre-sampling determinations
• Steps to set up a sampling plan
• Variables vs attributes sampling plans

Acceptance criteria

• The concept of acceptance criteria
• Variance: how much is too much
• How and why to measure variance

Using process capability

• The concept of process capability
• Cp vs Cpk
• Using process capability to set acceptance criteria

Pharmaceutical and medical device companies must have formal, statistically justified sampling plans and acceptance criteria for validation. Many have no dedicated statistics department, so the work falls to validation or quality engineers. This training offers a simple, step-by-step method.

It suits QA professionals, technical scientists, production staff and statisticians involved in validation at medical device and pharmaceutical companies.

• QA professionals
• Technical scientists
• Production staff
• Statisticians involved in validation

from Medical Device and Pharmaceutical Companies

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 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.