PURPOSE: To provide tables of sample sizes which are required, by the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA), for the design of bioequivalence (BE) studies involving highly variable drugs. To elucidate the complicated features of the relationship between sample size and within-subject variation. METHODS: 3- and 4-period studies were simulated with various sample sizes. They were evaluated, at various variations and various true ratios of the two geometric means (GMR), by the approaches of scaled average BE and by average BE with expanding limits. The sample sizes required for yielding 80% and 90% statistical powers were determined. RESULTS: Because of the complicated regulatory expectations, the features of the required sample sizes are also complicated. When the true GMR = 1.0 then, without additional constraints, the sample size is independent of the intrasubject variation. When the true GMR is increased or decreased from 1.0 then the required sample sizes rise at above but close to 30% variation. An additional regulatory constraint on the point estimate of GMR and a cap on the use of expanding limits further increase the required sample size at high variations. Fewer subjects are required by the FDA than by the EMA procedures. CONCLUSIONS: The methods proposed by EMA and FDA lower the required sample sizes in comparison with unscaled average BE. However, each additional regulatory requirement (applying the mixed procedure, imposing a constraint on the point estimate of GMR, and using a cap on the application of expanding limits) raises the required number of subjects.
PURPOSE: To provide tables of sample sizes which are required, by the European Medicines Agency (EMA) and the U.S. Food and Drug Administration (FDA), for the design of bioequivalence (BE) studies involving highly variable drugs. To elucidate the complicated features of the relationship between sample size and within-subject variation. METHODS: 3- and 4-period studies were simulated with various sample sizes. They were evaluated, at various variations and various true ratios of the two geometric means (GMR), by the approaches of scaled average BE and by average BE with expanding limits. The sample sizes required for yielding 80% and 90% statistical powers were determined. RESULTS: Because of the complicated regulatory expectations, the features of the required sample sizes are also complicated. When the true GMR = 1.0 then, without additional constraints, the sample size is independent of the intrasubject variation. When the true GMR is increased or decreased from 1.0 then the required sample sizes rise at above but close to 30% variation. An additional regulatory constraint on the point estimate of GMR and a cap on the use of expanding limits further increase the required sample size at high variations. Fewer subjects are required by the FDA than by the EMA procedures. CONCLUSIONS: The methods proposed by EMA and FDA lower the required sample sizes in comparison with unscaled average BE. However, each additional regulatory requirement (applying the mixed procedure, imposing a constraint on the point estimate of GMR, and using a cap on the application of expanding limits) raises the required number of subjects.
Authors: Barbara M Davit; Mei-Ling Chen; Dale P Conner; Sam H Haidar; Stephanie Kim; Christina H Lee; Robert A Lionberger; Fairouz T Makhlouf; Patrick E Nwakama; Devvrat T Patel; Donald J Schuirmann; Lawrence X Yu Journal: AAPS J Date: 2012-09-13 Impact factor: 4.009
Authors: Akshanth R Polepally; Haoyu Wang; Patrick J Marroum; Mukul Minocha; Balakrishna Hosmane; Amit Khatri; Sven Mensing; Thomas J Podsadecki; Daniel E Cohen; Walid M Awni; Rajeev M Menon Journal: AAPS J Date: 2017-07-06 Impact factor: 4.009
Authors: J Garcés-Eisele; A Ruiz-Argüelles; Larisa Estrada-Marín; Virginia Reyes-Núñez; R Vázquez-Pérez; Olga Guzmán-García; R Coutiño-Medina; Leticia Acosta-Sandria; Beatriz Cedillo-Carvallo Journal: Indian J Pharm Sci Date: 2014-07 Impact factor: 0.975