|(If you can't find the mistake, the answer is at the bottom of this post)|
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 this first instalment we will consider some mistakes associated with ‘Specificity’. This characteristic is evaluated for both qualitative and quantitative methods but the aim is different for each. For qualitative methods, the aim is to demonstrate that the method can provide the correct information, e.g., an identification method. For quantitative methods, the aim is to demonstrate that the final result generated by the method is not affected by all the potential interferences associated with the method.
Generally, I find that mistakes relating to specificity arise from a basic lack of understanding about what is required to demonstrate that the method is satisfactory. I have selected the following three examples as being ones that I regularly encounter when advising people on method validation, during both consultancy and training courses.
1. Not setting appropriate acceptance criteria
2. Not investigating all the potential interferences
3. Not considering potential changes that could occur in the sample/method being tested
Mistake 1: Not setting appropriate acceptance criteriaWhen the results of a validation study don’t comply with the acceptance criteria defined in the protocol, then either the method is not suitable for its intended use, or the acceptance criteria set in the protocol were inappropriate. I am often asked for help on how to explain why it’s okay that results did not meet the acceptance criteria, and not just for specificity. The usual reason for this problem is that generic acceptance criteria were used, typically predefined in an SOP, and no evaluation of their suitability to the method being validated was performed.
Example 1: An identification method by FTIR, which was based on a percentage match with reference material spectra in a database, was being validated. The validation failed because the acceptance criteria for the percentage match was set at 98% and the match in the validation study was always in the region of 97%. On investigation it was determined that the percentage match of 98% had no scientific justification, it was just what had been used before. No investigation of the method had been performed prior to the validation.
Example 2: A chromatographic impurities method was being validated. The method validation SOP defined that impurity peaks should have a resolution of 1.5 and thus an acceptance criterion of 1.5 was set in the validation protocol. During the validation study, one of the impurity peaks had a resolution of 1.4. On review of the method development information, it was found that the resolution of this peak was always around 1.4 and the chromatography had been considered acceptable but this information had not made it into the validation protocol.
TIP: Review all the acceptance criteria defined in the validation protocol against what is known about the method. Assess whether the criteria are reasonable, in terms of the method capability and what is considered acceptable. The use of generic acceptance criteria can be a very useful strategy as long they are used in a scientific manner by assessing what is known about the actual method being validated.
Mistake 2: Not investigating all the potential interferencesIn order to demonstrate that the final result generated by the method is not affected by potential interferences, it is essential that all the potential interferences are considered. This can sometimes be difficult for complex sample matrices so it is important to identify the constituents of the sample matrix as fully as possible. Additionally, it is easy to overlook other sources of interferences that may be introduced as part of the method such as solvents, buffers, derivatisation reagents, etc.
TIP: Carry out a thorough review of all potential interferences when designing the validation protocol, particularly if the sample matrix is complex in nature, or if the sample preparation involves the use of multiple reagents.
Mistake 3: Not considering potential changes that could occur in the sample/method being testedThe potential interferences that are present in a sample matrix can change due to changes in the sample composition. The most common example of this situation is probably sample degradation. In situations where a method will be used for samples of different ages, such as in a stability programme, it is essential that this is taken into account during validation and that it is demonstrated that the method can be used for any sample which may require analysis.
This means that for some methods, particularly those which are considered to be stability indicating, the specificity section of the validation protocol should include experiments to gather evidence to prove that the method may be successfully used for stability analysis. For methods which analyse the degradation products it would be expected that forced degradation studies were performed during method development to allow the creation of a method that can separate all the components of interest. For other methods this may not have been necessary in method development but a forced degradation study may now be required as part of method validation to demonstrate that the method is stability indicating.
TIP: Consider the long term use of a method when designing the validation protocol. What samples will be tested and are there any anticipated changes that could occur to the samples that would affect the potential interferences for the method? If the method is to be used for stability testing, are there any additional requirements, such as a degradation study?
In the next instalment, I will write about common validation mistakes for the method performance characteristic of robustness. 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. We also offer a course on developing stability indicating HPLC methods that includes strategies for forced degradation studies.
|Another amusing mistake! (Answer to puzzle at the top of this blog: the word 'the' is repeated in the question.)|