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Statistical Concepts of Process Validation
This process validation training will look at the underlying statistical concepts to perform an effective process validation. The webinar will examine elements of the FDA regulations for process validation (21 CFR 820.75) as well as the corresponding requirements in ISO 13485.
Why Should You Attend:
The FDA’s quality system regulation requires device manufacturers to validate processes when they don’t fully verify the resulting output. Based on Warning Letters, the FDA expects manufacturers to validate processes when the output check uses sampling instead of 100% inspection.
The presentation looks at these aspects of process validation using the unifying approach of a statistical model. Rather than a fundamental examination of how to perform process validation, this webinar will disclose tools necessary to use the statistical model. Further, when you validate the process with a high degree of assurance, this means your process achieves a certain process capability. This course will discuss the concepts of process capability, especially the use of Cp and Cpk.
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 will present 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?
The presentation will conclude by highlighting 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.
- Understand the QSR requirements for process validation
- Explain FDA’s approach as documented in Warning Letters
- Understand the ISO 13485 requirements for process validation
- State the statistical model that links process input and process output
- Link sampling verification to the process model
- Understand the role of process capability and describe the desired values of the indices
- Understand the role of designed experiments in determining the input parameter space
- Describe the role of challenge points in operational qualification
- Recognize the role of process validation in risk management
Areas Covered in the Webinar:
- 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:
This webinar is for people involved in the validation of production processes. Validation requirements start in the design output (setting the requirements), continues to design transfer (where the requirements are set as process parameters), and finally to process validation to ensure the resulting output achieves the requirements. People in the following roles can especially benefit from this webinar:
- Quality Managers
- Quality Engineers
- Production Managers
- Production Supervisors
- Manufacturing Engineers
- Production Engineers
- Design Engineers
- Process Owners
Daniel O'Leary is the president of Ombu Enterprises, LLC, a company offering training and execution in operational excellence, focused on analytical skills and a systems approach to operations management. Mr. O'Leary has more than 30 years’ experience in quality, operations, and program management in regulated industries including aviation, defense, medical devices, and clinical labs. He has a master’s degree in mathematics; is an ASQ certified biomedical auditor, quality auditor, quality engineer, reliability engineer, and six sigma black belt; and is certified by APICS in resource management.
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 will illustrate 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.
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.
ComplianceOnline would process/provide refund if the Live Webinar has been cancelled. The attendee could choose between the recorded version of the webinar or refund for any cancelled webinar. Refunds will not be given to participants who do not show up for the webinar. On-Demand Recordings can be requested in exchange.
Webinar may be cancelled due to lack of enrolment or unavoidable factors. Registrants will be notified 24hours in advance if a cancellation occurs. Substitutions can happen any time.
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