Dan O’Leary will present a webinar for Compliance on Line on the statistical concepts that underlie process validation. Go to http://www.complianceonline.com for registration information.
Process validation is an important element in medical device manufacturing. This webinar looks at the underlying statistical concepts to perform an effective process validation. The webinar examine elements of the FDA regulations for process validation (21 CFR §820.75) as well as the corresponding requirements in ISO 13485.
When you cannot (or do not) fully verified process results by subsequent inspection and test this leads to sampling plans. We discuss the use of attribute sampling plans in this context.
When you validate the process with a high degree of assurance, this means your process achieves a certain process capability. We discuss the concepts of process capability, especially the use of Cp and Cpk.
Operational Qualification (OQ) explores the parameter space that defines the process and selects challenge points as part of the qualification protocol. This naturally leads to Designed Experiments as the exploratory tool.
Lastly, Risk Management (ISO 14971) includes production information. This leads directly to validated processes since these are often the production processes that carry the greatest risk.
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 requirement is to validate the process with a high degree of assurance. This, coupled with the process validation definition that a process consistently produces a result or product meeting its predetermined specifications, leads to a statistical definition. A process that consistently produces a conforming output is capable. This leads to using process capability indices, Cp and Cpk as the goal for a validated process.
Designed experiments determine the limits of the parameter space for the process. The same techniques, especially full and fractional factorial experiments, can establish “worst case” conditions that become challenge points for the Operational Qualification (OQ) phase of process validation.
Risk Management, as defined in ISO 14971, requires the inclusion of production processes. Processes that require validation have the greatest risk, since they are not fully verified. In addition, they often involve the production process with the greatest risk, such as sterilization.
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 seminar covers the tools necessary to use the statistical model.