Statistical comparison of quality attributes_a range-based approach

TL;DR

This paper introduces a new statistical framework for comparing product quality attributes considering variability, including a novel covering-test, to determine product similarity, especially useful in regulated industries like pharmaceuticals.

Contribution

It presents a range-based comparison approach using the kappa-cover concept and a new statistical test, the covering-test, for assessing product similarity.

Findings

The covering-test has good statistical properties with small samples.

Simulations confirm the test's effectiveness in power and size.

Application to pharmaceutical data demonstrates practical utility.

Abstract

A novel approach for comparing quality attributes of different products when there is considerable product-related variability is proposed. In such a case, the whole range of possible realizations must be considered. Looking, for example, at the respective information published by agencies like the EMA or the FDA, one can see that commonly accepted tests together with the proper statistical framework are not yet available. This work attempts to close this gap in the treatment of range-based comparisons. The question of when two products can be considered similar with respect to a certain property is discussed and a framework for such a statistical comparison is presented, which is based on the proposed concept of kappa-cover. Assuming normally distributed quality attributes a statistical test termed covering-test is proposed. Simulations show that this test possesses desirable statistical properties with respect to small sample size and power. In order to demonstrate the usefulness of the suggested concept, the proposed test is applied to a data set from the pharmaceutical industry