Pre-study Analytical Method Validation: Comparison of Four Alternative Approaches Based on Quality-level Estimation and Tolerance Intervals

In industry and in laboratories, it is crucial to continuously control the validity of the analytical methods used to follow the products' quality characteristics. Validity must be assessed at two levels. The 'pre-study' validation aims at demonstrating be re use that the method will be able to achieve its objectives. The 'in-study' validation is intended to verify, by inserting quality control (QC) samples in routine runs, that the method remains valid over time. At these two levels, the analytical method will be claimed valid if it is possible to prove that a sufficient proportion of analytical results is expected to lie within given acceptance limits [-lambda, lambda] around the nominal value. This paper presents and compares four approaches to checking the validity of a measurement method at the pre-study level. They can be classified into two categories. In the first, a lower confidence bound for the estimated probability pi of a result lying within the acceptance limits is computed and compared with a given acceptance level. Maximum likelihood and delta methods are used to estimate the quality level pi and the corresponding estimator variance. Two approaches are then proposed to derive the confidence bound: the asymptotic maximum likelihood approach and a method proposed by Mee (Commun. Stat. Theory Methods 1988; 17(5):1465-1479). The second category of approaches checks whether a tolerance interval for hypothetical future measurements ties within the predefined acceptance limits [-lambda, lambda]. beta-expectation and beta-gamma-content tolerance intervals are investigated and compared in this context. These four approaches are illustrated on a bioanalytical HPLC-UV analytical process and compared through simulations. Copyright (C) 2008 John Wiley & Sons, Ltd.