Where do the Acceptance Criteria in Method Validation Come From? - Webinar Recording

Описание к видео Where do the Acceptance Criteria in Method Validation Come From? - Webinar Recording

This video is a recording of a webinar originally presented by Oona McPolin of Mourne Training Services Ltd on the 29th July 2020. An additional session was delivered on the 12th August 2020.

One of the most difficult tasks when writing an analytical method validation protocol is to set suitable acceptance criteria, particularly for the characteristics of accuracy and precision. It sometimes seems that the values are just plucked out of the air! Available guidance documents, such as ICH Q2(R1), don't mention any numbers. In this webinar we looked at the relationship between inherent analytical error and validation acceptance criteria to give an understanding of where typical values come from.

Mourne Training Services Ltd provide a range of courses on the topic of analytical method validation, visit the website for more information: https://mournetrainingservices.com/co...

Validation, verification and transfer course for pharmaceuticals: https://mournetrainingservices.com/me...
Validation, verification and transfer course for bipharmaceuticals: https://mournetrainingservices.com/me...

Navigation:
0:00 Introduction
0:12 Webinar info
4:51 What are Acceptance Criteria?
6:39 General Recommendations
7:48 How do you decide what acceptance criteria to set in your protocol?
9:53 Acceptance Criteria are required for the Method Performance Characteristics (referred to as 'Validation Characteristics in ICH Q2)
10:07 Quantitative Methods
12:21 What is 'Error'?
13:11 Types of inherent error
14:29 Random Errors
15:02 Statistical treatment of random error
15:45 Example of a Random Error
20:23 Systematic Errors
20:42 Example of a Systematic Error
24:24 Which is the correct integration approach in this situation?
31:19 Uncertainty of Measurement
33:02 Measurement Uncertainty References
33:56 Magnitude of Analytical Error Example
36:25 Typical values for Accuracy (Trueness)
38:12 Typical Criteria in Pharma Expressed as % Recovery
39:47 Typical Values for Precision
41:46 Summary of key points

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