[en] Quality by Design ; tolerance intervals ; Method Validation ; fit for purpose ; acceptance limits ; Quantitative impurity assays ; Content assays
[en] The concept of quality by design (QbD) has recently been adopted for the development of pharmaceutical processes to ensure a predefined product quality. Focus on applying the QbD concept to analytical methods has increased as it is fully integrated within pharmaceutical processes and especially in the process control strategy. In addition, there is the need to switch from the traditional checklist implementation of method validation requirements to a method validation approach that should provide a high level of assurance of method reliability in order to adequately measure the Critical Quality Attributes (CQAs) of the drug product. The intended purpose of analytical methods is directly related to the final decision that will be made with the results generated by these methods under study. The final aim for quantitative impurity assays is to correctly declare a substance or a product as compliant with respect to the corresponding product specifications. For content assays, the aim is similar: making the correct decision about product compliance with respect to their specification limits. It is for these reasons that the fitness of these methods should be defined, as they are key elements of the Analytical Target Profile (ATP). Therefore, validation criteria, corresponding acceptance limits and method validation decision approaches should be settled in accordance with the final use of these analytical procedures. This work proposes a general methodology to achieve this in order to align method validation within the QbD framework and philosophy. β-expectation tolerance intervals are implemented to decide about the validity of analytical methods. The proposed methodology is also applied to the validation of analytical procedures dedicated to the quantification of impurities or active product ingredients (API) in drug substances or drug products and its applicability is
illustrated with two case studies.