Friday, 18 May 2018

Common Mistakes in Method Validation and How to Avoid Them - Part 3: Accuracy


The validation of analytical methods is undoubtedly a difficult and complex task. Unfortunately this means that mistakes are all too common. As a trainer and consultant in this area I thought it might be useful to take a look at some common mistakes and how to avoid them. In this series of articles I will pick out some examples for discussion related to the method performance characteristics as listed in the current ICH guidance, ICH Q2(R1), namely: Specificity; Robustness; Accuracy; Precision; Linearity; Range; Quantitation limit; and Detection limit.
In previous articles I wrote about some common mistakes associated with ‘Specificity’ and 'Robustness'. This time I’ll take a look at ‘Accuracy’. The common mistakes that I have selected for discussion are:
1.       Not evaluating accuracy in the presence of the sample matrix components
2.       Performing replicate measurements instead of replicate preparations
3.       Setting inappropriate acceptance criteria
The definition of accuracy given in the ICH guideline is as follows: ‘The accuracy of an analytical procedure expresses the closeness of agreement between the value which is accepted either as a conventional true value or an accepted reference value and the value found.’ This closeness of agreement is determined in accuracy experiments and expressed as a difference, referred to as the bias of the method. The acceptance criterion for accuracy defines how big you are going to let the bias be and still consider the method suitable for its intended purpose.
The term accuracy has also been defined by ISO to be a combination of systematic errors (bias) and random errors (precision) and there is a note about this in the USP method validation chapter, <1225>: ‘A note on terminology: The definition of accuracy in 1225 and ICH Q2 corresponds to unbiasedness only. In the International vocabulary of Metrology (VIM) and documents of the International Organization for Standardization (ISO), accuracy has a different meaning. In ISO, accuracy combines the concepts of unbiasedness (termed “trueness”) and precision.’
From the point of view of performing validation, the difference in the definitions doesn’t make a lot of difference, we usually calculate both bias and precision from the experimental data generated in accuracy experiments. Personally I prefer the ISO definition of accuracy.
Mistake 1: Not evaluating accuracy in the presence of the sample matrix components
Since the purpose of the accuracy experiments is to evaluate the bias of the method, the experiments that are performed need to include all the potential sources of that bias. This means that the samples which are prepared should be as close as possible to the real thing. If the sample matrix prepared for the accuracy experiments is not representative of the real sample matrix then a source of bias can easily be missed or underestimated.
TIP: The samples created for accuracy experiments should be made to be as close as possible to the samples which will be tested by the method. Ideally these ‘pseudo-samples’ will be identical to real samples except that the amount of the component of interest (the true value) is known. This can be very difficult for some types of sample matrix, particularly solids where the component of interest is present at low amounts (e.g., impurities determination).
For impurities analysis, it may be necessary to prepare the accuracy samples by using spiking solutions to introduce known amounts of material into the sample matrix. Although this carries the risk of ignoring the potential bias resulting from the extraction of the impurity present as a solid into a solution, there isn’t really a workable alternative.
Mistake 2: Performing replicate measurements instead of replicate preparations
Performing replicate preparations of accuracy ‘pseudo-samples’ allows a better evaluation of what differences in the data are due to the bias and what are due to variability of the method, the precision. A minimum of 9 replicates are advised by the ICH guidance and these should be separate preparations. For solids, this could be 9 separate weighings into 9 separate volumetric flasks, as per the method.
However, the preparation does depend on the nature of the sample matrix and the practicality of controlling the known value for the component of interest. As discussed above, sometimes in the case of impurities methods, solutions may be required for practical reasons even though the sample matrix exists as a solid. In this case 9 separate weighings does not offer more representative ‘pseudo-samples’ and thus a single stock solution for the impurity would probably be a better choice.
TIP: Assess the sample matrix and try to prepare separate replicates when possible so that the data produced is as representative as possible and includes typical sources of variability.
Mistake 3: Setting inappropriate acceptance criteria
As mentioned previously, the acceptance criterion for accuracy is based on how much bias you will allow in the results from the method. It is obviously better not to have any bias in a method but there is always a certain amount of potential bias associated with the combination of the sample matrix, the level of the components of interest in the sample, and the instrumentation used for the measurement. For the method to be capable the bias needs to be less than the specification for the result. For example, if a drug substance specification requires that there must be between 99 to 101 %w/w of the drug present, then a method which has a bias of 2% is not going to be acceptable.
TIP: Make sure that the acceptance criteria set for accuracy in method validation are compatible with the requirements for the method, and in particular, the specification for the test.
References
1.       ICH Q2 (R1): Validation of Analytical Procedures: Text and Methodology, 2005, www.ich.org
2.       USP <1225> Validation of Compendial Methods, www.usp.org
In the next instalment, I will write about common validation mistakes for the method performance characteristic of precision. If you would like to receive the article direct to your inbox, then sign up for our eNewsletter. You will receive lots of helpful information and you can unsubscribe at any time. We never pass your information on to any third parties.
If you would like to learn more about method validation, and method transfer, then you may be interested in the 3 day course on the topic from Mourne Training Services Ltd. The course has two versions, one applied to small, traditional pharmaceutical molecules and one for large, biological/biotechnology derived molecules. Visit the MTS website for more information.

   

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