Vangelis Karalis1, Panos Macheras. 1. Laboratory of Biopharmaceutics-Pharmacokinetics Faculty of Pharmacy, National and Kapodistrian University of Athens, Panepistimiopolis, Athens 15771, Greece. vkaralis@pharm.uoa.gr
Abstract
PURPOSE: Unveil the properties of a two-stage design (TSD) for bioequivalence (BE) studies. METHODS: A TSD with an upper sample size limit (UL) is described and analyzed under different conditions using Monte Carlo simulations. TSD was split into three branches: A, B1, and B2. The first stage included branches A and B1, while stage two referred to branch B2. Sample size re-estimation at B2 relies on the observed GMR and variability of stage 1. The properties studied were % BE acceptance, % uses and % efficiency of each branch, as well as the reason of BE failure. RESULTS: No inflation of type I error was observed. Each TSD branch exhibits different performance. Stage two exhibits the greatest % BE acceptances when highly variable drugs are assessed with a low starting number of subjects (N₁) or when formulations differ significantly. Branch A is more frequently used when variability is low, drug products are similar, and a large N₁ is included. BE assessment at branch A is very efficient. CONCLUSIONS: The overall acceptance profile of TSD resembles the typical pattern observed in single-stage studies, but it is actually different. Inclusion of a UL is necessary to avoid inflation of type I error.
PURPOSE: Unveil the properties of a two-stage design (TSD) for bioequivalence (BE) studies. METHODS: A TSD with an upper sample size limit (UL) is described and analyzed under different conditions using Monte Carlo simulations. TSD was split into three branches: A, B1, and B2. The first stage included branches A and B1, while stage two referred to branch B2. Sample size re-estimation at B2 relies on the observed GMR and variability of stage 1. The properties studied were % BE acceptance, % uses and % efficiency of each branch, as well as the reason of BE failure. RESULTS: No inflation of type I error was observed. Each TSD branch exhibits different performance. Stage two exhibits the greatest % BE acceptances when highly variable drugs are assessed with a low starting number of subjects (N₁) or when formulations differ significantly. Branch A is more frequently used when variability is low, drug products are similar, and a large N₁ is included. BE assessment at branch A is very efficient. CONCLUSIONS: The overall acceptance profile of TSD resembles the typical pattern observed in single-stage studies, but it is actually different. Inclusion of a UL is necessary to avoid inflation of type I error.
Authors: Sam H Haidar; Barbara Davit; Mei-Ling Chen; Dale Conner; LaiMing Lee; Qian H Li; Robert Lionberger; Fairouz Makhlouf; Devvrat Patel; Donald J Schuirmann; Lawrence X Yu Journal: Pharm Res Date: 2007-09-22 Impact factor: 4.200