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 ananlytica method validation, visit the website for more information: mournetrainingservices.com/co...
Validation, verification and transfer course for pharmaceuticals: mournetrainingservices.com/me...
Validation, verification and transfer course for bipharmaceuticals: 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

[@tanvirahmedsohag4086]

Thanks for the HPLC calculator I use it a lot

[@MTStraining]

Delighted that you are finding the calculator useful! Thank you for the feedback.

[@phelanapostol1275]

Hello, regarding the criteria for the accuracy and precision, what if I am analyzing an analyte with a true concentration of 5000ppm and I quantify it using external calibration with an analytical range of 1ppm to 10ppm, wherein the sample mass was 0.5grams and the total dilution factor of 500 to fit the sample in the calibration curve, what will be my acceptance criteria for accuracy? is it on the level of the analytical range (1-10ppm) or on the level of 5000ppm?

[@MTStraining]

The error that arises as a result of the sample preparation (which includes the dilution step) will relate to the proportion of the component present in the sample, therefore I would advise that you base your acceptance criteria on the actual test material concentration, i.e. 5000ppm

[@inticorrientes3129]

what about Horwitz Ratio as a precision acceptance criteria? what should I look in order to know if it is a good criteria for a particular method?

[@MTStraining]

The examples of acceptance criteria for precision that were presented towards the end of the webinar were actually calculated using the Horwitz equation (RSDR = 2^(1 - 0.5logC)) and I do think that it is a good tool for estimating the expected precision for a given sample. It tends to be slightly pessimistic at high concentrations, and more noticeably so at low trace concentrations.

[@satnamom4667]

Hello mam, I like your webinar very much. I have one query... During precision studies, we carry out 6 replicate analysis. The %rsd of these should be calculated of rounded values or unrounded values?

[@MTStraining]

I would advise that the data is expressed in the same way as when you are following the method for a routine analysis. This would typically involve using data with one more decimal place than the final result. For example, if the method is performed in duplicate it is typical to calculate the mean (reportable value) using the unrounded results for each of the duplicate determinations, and then round.

[@satnamom4667]

@@MTStraining thank you for your response ma'am. But my concern is during routine analysis, the final rounded figure is declared. So while precision studies during validation, the rsd shoud be calculated of 6 rounded off values.... Do you agree? Can you please share me your email id so that I can share a live case....

[@dmahmood1991]

@@satnamom4667 Nooooo, dont round!!! All calculations should be done using 5 s.f. (as a guide) once you have calculated then you can round. A lot of calculations are based on the fact that data is normally distributed... however, if all your data is 2.2, 2.2, 2.2, 2.2, 2.2, 2.2 you would have no standard deviation which is obviously not correct. Therefore you are losing valuable information by rounding.

[@thehealer8330]

this webinar did not provide any information regarding acceptance limit or criteria for validation parameter?? from usp or fda or ich. guideline for acceptance criteria for each parameter of method validation especially accuracy

[@MTStraining]

Hi Muhammad, The simple reason for that is that there are no acceptance criteria provided in the guidelines from ICH and FDA. The purpose of this video is to help you understand the values that people typically use.

[@shoaibfaraizi]

Ad hominem.