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Is it Method Verification or Validation, or Just Semantics

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Deadline: March 29, 2017 | Date: March 29, 2017

Venue/Country: Online

Updated: 2017-03-09 15:13:58 (GMT+9)

Call For Papers - CFP

The Webinar will discuss the distinction between and requirements for method validation and method verification, to comply with ISO/IEC Standard 17025:2005 for laboratory accreditation in food/water microbiology. Quantitative and Qualitative methods have different performance measurement requirements and require different statistical analyses. Although method validation and method verification are related terms, they have very different analytical and statistical requirements particularly for compliance with ISO/IEC 17025:2005. Understanding these differences is essential for developing appropriate strategies for assessing a method’s fitness for purpose. This webinar will not only address the semantics, but will also discuss the appropriate analytical and statistical approaches to achieving successful verification and validation studies.

Why Should You Attend

Without a clear understanding of the different analytical approaches for verification and validation, laboratories often end up doing more unnecessary, costly work, with little benefit. Very often the inappropriate analytical strategy used is unacceptable to meet the requirements for accreditation and the effort needs to be repeated. Learn to do it right the 1st time!

Learning Objectives

Method performance characteristics.

Measuring and Monitoring Analytical competency

Food Categories and Food Types

Analytical requirements for Verification of Quantitative Methods

Analytical requirements for Verification of Qualitative Methods

Fitness for purpose

Who Will Benefit

- Microbiological bench analysts in food, water and pharmaceutical laboratories

- QA managers

- Laboratory managers/supervisors

- QC practitioners

For More Info, Please Click below URL:

Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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