Faculty: Alan M. Golden ‎ ‎ ‎‎ ‎ ‎ |‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ ‎ Code: FDB3590


  • Date: 1/30/2023 11:00 AM - 1/30/2023 12:00 PM
  • Location: Online Event

Tickets


Ticket Type
Qty
Live- Single
$250.00
0
For ONE Participant – Live session only
Live Corporate
$790.00
0
For Maximum of 10 participants – Live session only
Recording - Single
$390.00
0
Recording access for ONE participant (viewer) – Unlimited viewing access for 6 months
Recording - Corporate
$1400.00
0
Recording access (Multiple licenses) for up to 10 participants – Unlimited viewing access for 6 months

Total

$0.00

Description

This webinar will discuss setting up statistically justified sampling plans for process validation. 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:

Companies in the pharmaceutical and medical device space are required to implement statistically justified sampling plans for validation. 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.

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 a simple step by step method of developing statistically justified sampling plans and acceptance criteria.

Areas Covered in the Session:

Why validate

  • Brief review of what validation means
  • Brief review of regulations and guidance around validation

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

Setting acceptance criteria for

  • Test Method Validation
  • Process Validation
  • Risk based acceptance sampling

Using acceptance sampling to set acceptance criteria


Who Should Attend:

  • Quality Assurance Departments
  • Quality Control Departments
  • Engineering Departments
  • Production Departments
  • Validation Departments
  • Technical Scientists
  • Statisticians involved in Validation

Course Director: ALAN M. GOLDEN

 

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.