Analytical method transfer: Improving interpretability with ratio-based statistical approaches

After assay validation in an originating laboratory, an analytical method needs to be transferred to one or several production laboratories, because measured outcomes among the laboratories must agree. To state agreement, the locations (e.g. means) must be equivalent and the production laboratory must be non-inferior to the originating one concerning scales (e.g. standard deviations). Here, parametric and non-parametric approaches based on marginal confidence intervals for the ratio of locations and the ratio of scales are presented. These intervals are appropriate for a matched pairs design without repeated measurements. Results of simulation studies investigating the power and the control of the type I error are shown and limits of the approaches are discussed. In addition, a Bland–Altman plot with tolerance intervals is proposed. As illustrated in the example proportional differences greatly improve the interpretation of the results compared to absolute differences.

► We propose statistical analyses based on relative differences for analytical method transfers.
► The approaches allow a biologically meaningful evaluation of accuracy in line with EMA/FDA recommendations.
► We present results of power and type I error simulations.
► Software (R code) is available and open source.