Objectives of the Presentation
Why Should you Attend
- Learn the difference between corrective action and preventive action - a pervasive problem
- Understand the requirements from QSR and the expectations FDA set
- How to pick the appropriate data analysis techniques from ISO/TR 10017:2003
- Use the GHTF guidance document to design and implement your improvement program
- Review FDA Warning Letters that illustrate the issues device manufacturers face
Corrective and Preventive action is the most frequently cited section in device Warning Letters and data analysis is the most frequently cited subsection. This suggests that device manufacturers need to understand FDA’s expectations and meet them with a robust approach to data analysis. However, data analysis is more than a regulatory requirement. It is an effective method for a device manufacturer to identify problems, analyze their causes, and take action. These activities can reduce cost and increase customer satisfaction. For example, a Warning Letter points out that 17% of complaints were returns for shipping the wrong product. It concludes, "This [problem] was not identified, no investigation was performed, and no corrective action was taken."
With the appropriate framework and analysis tools, the company could have found the problem, eliminated the cost and prevented the customer dissatisfaction. Instead, an FDA Investigator uncovered the issue; now the company must take additional action (and allocate resources) to address the Warning Letter.
This presentation helps you understand the issues and take action. For example, some companies believe there is a requirement to ‘trend’ the data. However, FDA-CDRH says that is only one tool among the many statistical analysis techniques. You will learn about a recommended set of techniques and why trending is only among many viable methods.
The Global Harmonization Task Force has a guidance document that provides a framework for implementation. The webinar covers this framework and explains how you could use it to implement an effective system.
Who will Benefit
- Senior management
- Regulatory affairs
- Quality assurance
- R&D and engineering
- Data analysts
Participants receive a checklist to help implement a data analysis program.