Скачать с ютуб Where do the Acceptance Criteria in Method Validation Come From? - Webinar Recording в хорошем качестве

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