title: Multivariate equivalence tests for use in pharmaceutical development.
abstract: Statistical equivalence analyses are well-established parts of many studies in the biomedical sciences. Also in pharmaceutical development and manufacturing equivalence testing methods are required in order to statistically establish similarities between machines, process components, or complete processes. This article presents a choice of multivariate equivalence testing procedures for normally distributed data as generalizations of existing univariate methods. In all derived methods, variability is interpreted as nuisance parameter. The use of the proposed methods in pharmaceutical development is demonstrated with a comparative analysis of dissolution profiles.
authors.affiliation: a Boehringer Ingelheim GmbH & Co. KG , Ingelheim , Germany.
authors.forename: Thomas
authors.initials: T
authors.lastname: Hoffelder
authors.forename: Rüdiger
authors.initials: R
authors.lastname: Gössl
authors.forename: Stefan
authors.initials: S
authors.lastname: Wellek
mesh_terms: D003627:Data Interpretation, Statistical; D004345:Drug Industry / Q000379:methods / Q000592:standards / Q000706:statistics & numerical data*; D015999:Multivariate Analysis; D016011:Normal Distribution; D004364:Pharmaceutical Preparations / Q000032:analysis / Q000737:chemistry / Q000592:standards*; D012107:Research Design / Q000706:statistics & numerical data*; D012995:Solubility
chemical_list: D004364:Pharmaceutical Preparations
keywords: Delta method; Dissolution profiles; Mahalanobis distance; Multivariate equivalence testing; Principle intersection–union; Similarity factor; Two-sample design