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Introduction to Analytical Validation class room course
1 Day Course

This one day course covers all the basics required to produce an analytical development protocol, implement validation studies and report to regulatory guidelines.
You will learn the absolute essentials of each technique and using our unique multi-media examples and tutorial exercises you will begin to use new knowledge and ideas right away.

  • We limit numbers to 20 per course so that each delegate gets the opportunity to ask questions and fully participate in tutorial exercises
  • When delivered on-site we can design the course material to suit your specific training needs
  • Customisable written assessments are available if required

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“Method validation is the process of defining an analytical requirement, and confirming that the method under consideration has performance capabilities consistent with what the application requires. Implicit in this is that it will be necessary to evaluate the method’s performance capabilities.”

This course introduces all the critical analytical parameters covered during a method validation study, highlighting all applicable regulatory guidance and detailing how the protocol should be carried out and reported. All required statistics are also introduced and explained.

Who is this course for

This course is for LC or GC method developers who need to provide evidence of the reliability of analytical methods or to ensure that “off-the-shelf” validated methods are being used correctly.

Previous knowledge

Good knowledge of chromatography and statistical analysis is advantageous.

What you will learn

  • What is analytical best practice
  • What is method validation
  • Who defines method validation requirements
  • What is the relation between method development and validation
  • Statistical methods and tests used during validation

Defining extent and scope of Validation studies Equipment

  • Overview of Equipment Validation

Documentation
Sources of error
Experimental design for Analytical Method Validation
Statistical methods and tests for Validation
Validation Parameters

  • Selectivity
  • Linearity
  • Accuracy
  • Precision
  • Sensitivity
  • Robustness

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