Decision protocol for checking robustness with previous outlier detection in the validation of analytical methods

Abstract A general procedure based on variation of experimental design for checking robustness in the validation of analytical methods is presented. This procedure, which is easy to apply, consists in estimating the main total effects, in detecting outliers, checking the curvature and in determining the main side effects. Two methodologies based on the analysis of a) the residuals from the reduced model and b) the replicates from the reconstructed design were employed for the detection of outliers. In further studies, general experimental design principles were applied using two- and three-level factorial designs. In some cases, a dummy variable was introduced in order not to modify the structure of the designs utilized.