Outlier detection in bioavailability/bioequivalence studies

Abstract

This paper concerns techniques for detection of a potential outlier or extreme observation in a bioavailability/bioequivalence study. A bioavailability analysis that includes possible outlying values may affect the decision on bioequivalence. We consider a general crossover model that takes into account period and formulation effects. We derive two test procedures, the likelihood distance and the estimates distance, to detect potential outliers. We show that the two procedures relate to a chi-square distribution with three degrees of freedom. The main purpose of this paper is to exhibit and discuss these two general approaches of outliers detection in the context of a bioavailability/bioequivalence study. To illustrate these approaches, we use data from three-way crossover experiment in the pharmaceutical industry that concerned the comparison of the bioavailability of two test formulations and a standard (reference) formulation of a drug. This example demonstrates the influence of an outlying value in the study of bioequivalence.

Critical appraisal of biosimilar filgrastim (Nivestim™) for febrile and chemotherapy-induced neutropenia

“…However, for several pharmacokinetic parameters, bioequivalence could only be concluded when outliers (as are commonly observed in these type of studies) were excluded. 33,34 Bioequivalence could not be shown for C max at day 5, even when outliers were excluded. There was also some slight variability between the two agents in terms of T max at day 5 at both dose levels.…”

Comparison of the pharmacodynamic profiles of a biosimilar filgrastim and Amgen filgrastim: results from a randomized, phase I trial

“…However, for several PK parameters, bioequivalence could only be concluded when outliers (as are commonly observed in studies of this kind [12, 13]) were excluded. Bioequivalence could not be shown for C max at day 5, even when outliers were excluded.…”

Nonparametric Validation of Similar Distributions and Assessment of Goodness of Fit

“…In Section 4, we show that this test can be used as a nonparametric test for population as well as average equivalence. In particular, the¯exible choice of trimming allows robust bioequivalence assessment which is required in many practical situations (see Chow and Tse (1990)). Crucial for the success of a nonparametric equivalence test is the choice of the measure of discrepancy between probability distributions.…”