Strategies for Validation Extensions - It is essential to understand the critical elements of validation extensions to ensure accurate process or product quality measurements. - BioPharm International

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Strategies for Validation Extensions
It is essential to understand the critical elements of validation extensions to ensure accurate process or product quality measurements.


BioPharm International


Analytical Method Comparability


Table 2. General guidance for using appropriate statistics to assess method comparability from validation characteristics per ICH Q2(R1)
Because we need to demonstrate equality or improvement whenever approved methods are replaced, which and how are method performance characteristics compared? Table 2 provides guidance on which validation characteristics to use for comparability protocols for each assay type per ICH Q2(R1). All qualitative tests should contain a comparison of hit-to-miss ratios (for "specificity") between the approved method and the new method. If a qualitative limit test is exchanged, the detection limit (DL) of the new method should be compared and should be equal or lower for the new method. For all quantitative methods, the method performance characteristics accuracy and precision (intermediate precision) should be compared.8

It is of great regulatory concern whether results may change overall by drifting (change in "accuracy" or "matching") or by an increase in data spreading ("intermediate precision"). An increase in data spreading or lack of precision will mostly increase the likelihood of observing cases 1B or 2B and should be avoided. A drift in results or "lack of matching" may require a change in the specifications. This drift in release results can occur in two directions, lower or higher results. Both directions are not acceptable outcomes for the demonstration of accuracy, and testing for equivalence between methods is therefore correct.8 The goal of comparisons of other characteristics (e.g., DL) is different as at least two outcomes are acceptable that is to be equivalent or superior meaning a lower DL.8 A third comparison category is the demonstration of noninferiority and is usually the easiest to pass for comparability. However, we should keep in mind that the use of any of the comparability categories (noninferiority, equivalence, superiority) using ICH E9 and Committee for Proprietary Medicinal Products (CPMP) guidance documents should be properly chosen and justified.8,11–13 In other words, noninferiority testing may be justified for the comparison of some primary characteristic, such as DL, if other secondary criteria (e.g., increased number of tests or test samples) can compensate for the small level of inferiority of the primary comparison characteristic.8

Quantitative limits (QLs) could also be compared. However, both QLs would have to be estimated by the same principle (e.g., estimated by regression analysis). A low QL is desirable because it will let us quantitatively report and monitor low-value results by SPC. There are several ways to compare QLs. For example, we could compare the regression coefficients of both linear assay response curves to estimate both QLs and would also get a general idea how accuracy and precision characteristics compare over the assay range. Table 2 constitutes a general guidance. Particular examples for non-inferiority, equivalence, and superiority testing to demonstrate method comparability were provided and discussed elsewhere.8

No matter which comparability category we may use for a statistical comparison (with p = 0.05), a protocol should provide the design of experiments to be done and the pre-specified value for the allowable difference in results. The prespecified maximum allowable difference is illustrated in CPMP's Points to Consider on the Choice of Non-Inferiority Margin.13 The allowable difference should be set similar to AMV or AMT. The difference should be set and justified by relating specifications to SPC data and considering the likelihood of observing any of the four cases (1A, 1B, 2A, and 2B).8


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