Overview: This webinar covers the statistical methods used to calculate sample sizes for both attribute and variables data.

Methods for collecting the sample will be covered.  Every sampling plan has risks. This webinar covers how to calculate Type I and Type II errors. A discussion of how the FDA views sampling plans, especially for validation and acceptance activities.  Sample size to ensure a certain level of process capability will be covered.

Areas Covered in the Session:

• How to collect a sample
  
• What are the two types of error (Type I and Type II)
  
• How to calculate sample sizes for variables data
  
• How to calculate sample sizes for attribute data
  
• Using confidence intervals on Cpk to calculate a sample size
  
• Using binomial confidence intervals

Who Will Benefit:

• Management
  
• Research and Development
  
• Regulatory Affairs personnel
  
• Quality assurance/quality control personnel
  
• Auditors and inspectors

Overview: There are several methods to trend data to highlight both the preventative and corrective nature of the system.

Plotting data over time is a good visual method to identify trends. Statistical Process Control (SPC) techniques such as control charts give an objective method to identify trends. A discussion of out of trend versus out of specification will be covered.

Areas Covered in the Session:

• Run charts
  
• Control charts for variables
  
• Control charts for attributes
  
• Regression analysis
  
• Using control charts to estimate capability

Who Will Benefit:

• Management
  
• Research and Development
  
• Regulatory Affairs personnel
  
• Quality assurance/quality control personnel
  
• Auditors and inspectors

Overview: The FDA QSR requires device manufacturers to validate processes when the manufacturer cannot "fully verify the output". The manufacturer must validate these processes with a "high degree of assurance".

The presentation explores the statistical underpinnings of these two phrases. To "fully verify the output" relates to the use of statistical sampling plans, while "high degree of precision" relates to process capability. The presentation illustrates the statistical concepts. The Global Harmonization Guidance document on process validation shows the application of statistical techniques. In particular, the guidance explains the use of design experiments (DOE) to establish process parameters and develop challenge points for the Operational Qualification (OQ) phase. The guidance explains the concepts of process capability showing the relationship between the process statistical characterization and the engineering specification transferred from design. Statistical Process Control (SPC) is an important technique in the Performance Qualification (PQ) phase of validation. The presentation concludes by showing the strong relationship between validated processes and Risk Management. ISO 14971:2007 requires that production (and post-production) information go back to Risk Assessment to help complete the life cycle. Validated processes, where the manufacturer cannot fully verify the output, present a risk of product “escape”. Statistical information of each lot from a validated process should be part of the Risk Management File.

Why you should attend:
If you conduct process validation, you need to ensure that your results are valid. Beyond the regulatory requirements, statistical approaches will help you achieve the desired result - processes that produce only conforming material. This is the essence of the statistical approach. This webinar presents the statistical approach that will help you validate your processes. Your team should attend this webinar if you cannot easily answer these questions.

• Can you give the statistical rational for you verification sampling plans?
  
• Can you state the desired and actual process capability you need to achieve?
  
• Can you list the worst-case input parameter combination for your process?
  
• Do you know how to determine challenge points for your process?
  
• Have you set action limits for your process inputs?

Areas Covered In the Seminar:

• QMS Requirements for Process Validation
  • FDA’s QSR (21 CFR §820.75)
  • ISO 13485:2003
• The Statistical Process Model
  • Relating input to output
• The Process Output
  • Sampling Inspection
  • Process Capability
• The Process Input Parameters
  • Design of Experiments
  • The Challenge Points
• Risk Management
  • Production Information
  • Validated Processes as High Risk

Who will benefit: People in the following roles can especially benefit from the knowledge in this webinar:

• Quality Managers
• Quality Engineers
• Production Managers
• Production Supervisors
• Manufacturing Engineers
• Production Engineers
• Design Engineers
• Process Owners