Question? Prior Method Validation (To design a Protocol)

 CONSIDERATIONS PRIOR TO METHOD VALIDATION

Test method validation is a requirement for entities engaging in the testing of pharmaceutical products for the purpose of drug exploration,development, and manufacture for human use. It also of great value for any type of routine testing that requires consistency and accuracy.

Procedure validation is a cornerstone in the process of establishing an analytical procedure. The aim   of procedure validation is to demonstrate that the procedure, when run under standard conditions, will satisfy the requirement of being fit for use. To maximize the likelihood of a successful validation,         It is imperative that all aspects of the procedure be well understood prior to the validation. Surprising discoveries (whether "good" or "bad") during validation should be carefully evaluated to determine whether the procedure was adequately developed. Moreover, pre-validation work can reveal suitable approaches to reduce the total size of the validation experiment without increasing the risk of drawing the wrong conclusion. General principles and plans for sample preparation, general principles, experimental design, data collection, statistical evaluation, and choice of acceptance criteria should be documented in a validation experimental protocol signed before initiation of the formal validation.

Questions considered prior to validation may include the following:

·         What are the allowable ranges for operational parameters, such as temperature and time, that impact the performance of the analytical procedure?

o    Robustness of these ranges can be determined using a statistical design of experiments (DOE).

·         What are the ruggedness factors that impact precision?

o    Factors such as analyst, day, reagent lot, reagent supplier, and instrument that impact the precision of a test procedure are called ruggedness factors. When ruggedness factors impact precision, reportable values within the same ruggedness grouping (e.g., analyst) are correlated. Depending on the strength of the correlation, a statistical analysis that appropriately accounts for this dependence may be necessary. Ruggedness factors can be identified empirically during pre-validation or based on a risk assessment.

·         Are statistical assumptions regarding data analysis reasonably satisfied?

o    These assumptions may include such factors as normality, homogeneity of variance, and independence. It is useful during pre-validation to employ statistical tests or visual representations to help answer these questions.

·         What is the required range for the procedure?

o    The range of an analytical procedure is the interval between the upper and lower levels of an analyte that has been demonstrated to be determined with a suitable level of precision, accuracy, and linearity using the procedure as written.

·     Do accepted reference values or results from an established procedure exist for validation of accuracy?

o    If not, as stated in International Council for Harmonisation (ICH) Q2, accuracy may be inferred once precision, linearity, and specificity have been established.

·   How many individual determinations will compose the reportable value, and how will they be aggregated?

o    To answer this question, it is necessary to understand the contributors to the procedure variance and the ultimate purpose of the procedure. Estimation of variance components during pre-validation provides useful information for making this decision.

·         What are appropriate validation acceptance criteria?

o    The validation succeeds when there is statistical evidence that the assay is no worse than certain pre-specified levels for each relevant validation parameter.

       What defines the assay as fit for use, and how does this relate to acceptance criteria?

·         How large a validation experiment is necessary?

o    Validation experiments should be properly powered to ensure that there are sufficient data to conclude that the accuracy and precision can meet pre-specified acceptance criteria. Computer simulation is a useful tool for performing power calculations.

o    Efficiencies (both cost and statistical) can be gained if assessment of linearity, accuracy, and precision can be combined.

    On the basis of the answers to these and similar questions, one can design a suitable validation experimental protocol.