Design of Experiments – DOE

WEBINAR

Course description

Suppose you are designing or manufacturing a complex medical instrument, like a diagnostic device. There are many things to consider for design inputs or process settings. You can easily start talking about the need for hundreds of experiments to get your arms around this problem.

Key questions are:. What parameters are key to quality? How do we quickly and efficiently identify these parameters? How do we decide on strategies to optimize results? This webinar is focused on a “Faster, Better, Cheaper” methodology.

A broad variety of industries have applied Design of Experiments (DOE) to improve their products and, at the same time, have greatly reduced their process development costs. For medical device and pharmaceutical firms, this is invaluable with Design Control and Process Validation efforts. It even has value for Validation of Analytical Processes. This webinar will assist FDA-regulated manufacturers who have to conform to Process Validation requirements and the related guidance provided by the Global Harmonization Task Force (GHTF).

You will have an opportunity to hear directly from an industry expert on this valuable methodology. It also provides a forum where you can ask questions and get answers. The presenter has over 25 years of experience helping a broad variety of firms apply statistics tools and techniques, including DOE.  The presenter’s keep-it-simple approach fosters understanding and application. No knowledge of DOE is needed.

Program

Over the course of two hours, the program will:

• Explore the application of Design of Experiments (DOE) for both Design Control and Process Validation
• Provide a mapping of DOE techniques to Design Control and Process Validation activities
• Provide examples of industry best practices using DOE
• Demonstrate how DOE supports regulatory compliance

Who should attend

 This material will appeal to quality professionals and managers. Instruction is targeted to professionals involved in meeting Design Control and Process Validation requirements such as: members of research and development teams, process and manufacturing engineers, line operators, lab technicians, quality engineers, regulatory affairs specialists, and members of the leadership team. No knowledge of statistics is required to understand and apply the material presented.

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