Measurement uncertainty and risk of false decisions for similarity factor (f2): Boostrapping method or spreadsheet?

Abstract

The similarity factor (f₂) is a key metric to compare generic and reference drug and to obtain biowaivers of bioequivalence studies of Active Product Ingredient (API) in dissolution testing. Yet, its statistical limitations - including low power and undefined confidence levels - restrict its reliability. Therefore, Bootstrapping is a widely used approach for establishing Confidence Interval for f₂. Nevertheless, this approach is not user-friendly for non-statisticians, and to obtain the uncertainty related to the risk assessment of the f₂ in the dissolution testing requires additional steps. In this investigation, we propose the Kragten spreadsheet method as a practical alternative to Bootstrapping approach in the evaluation of the consumer's risk. Comparative analysis was performed under six scenarios of API's, involving reference/test drugs and registered/new formulations. All six groups met regulatory criteria (f₂>50 %), while 95 % confidence intervals from both statistical methods showed agreement, confirming methodological reliability. Despite all groups achieved the f₂>50 %, the range obtained through Bootstrapping and Kragten methods determined that three scenarios (A, C, and E) presented elevated consumer risk (>5 %), highlighting limitations of f₂ alone. Also, the differences between both methodologies were measured. For Bootstrapping, 50 iterations per 10.000 simulations showed no statistically significant differences from Kragten (p > 0.05), establishing method equivalence for symmetrical dissolution data. The findings advocate combining f₂ with uncertainty analysis for risk assessment in dissolution testing.