PURPOSE: The FDA has proposed replacing the current average bioequivalence criterion with population and individual bioequivalence criteria that consider variances in addition to the difference of averages. One of these variances in the individual bioequivalence criterion measures subject-by-formulation interaction, the extent to which the test-reference difference varies from person to person. This paper discusses conceptual and statistical issues raised in various publications and presentations with respect to the presence and estimation of such an interaction. METHODS: We focus on the importance of subject-by-formulation interaction, an understanding of what is a large interaction, and the assessment of the magnitude of this interaction in bioequivalence studies. Simulation studies, examples from the literature, and data from FDA files are used to demonstrate the magnitude of the interaction and its distribution under various conditions. RESULTS: The concept of a large interaction is tied to the concept of a large mean difference. We suggest that an interaction greater than 0.15 is a conservative criterion for a large interaction. Magnitudes of estimated interaction are affected by variability, sample size, and the selection of data sets that pass average bioequivalence. CONCLUSIONS: Examples of substantial interactions are beginning to appear. More data is needed before reaching definitive conclusions regarding the frequency and importance of observed interactions.
PURPOSE: The FDA has proposed replacing the current average bioequivalence criterion with population and individual bioequivalence criteria that consider variances in addition to the difference of averages. One of these variances in the individual bioequivalence criterion measures subject-by-formulation interaction, the extent to which the test-reference difference varies from person to person. This paper discusses conceptual and statistical issues raised in various publications and presentations with respect to the presence and estimation of such an interaction. METHODS: We focus on the importance of subject-by-formulation interaction, an understanding of what is a large interaction, and the assessment of the magnitude of this interaction in bioequivalence studies. Simulation studies, examples from the literature, and data from FDA files are used to demonstrate the magnitude of the interaction and its distribution under various conditions. RESULTS: The concept of a large interaction is tied to the concept of a large mean difference. We suggest that an interaction greater than 0.15 is a conservative criterion for a large interaction. Magnitudes of estimated interaction are affected by variability, sample size, and the selection of data sets that pass average bioequivalence. CONCLUSIONS: Examples of substantial interactions are beginning to appear. More data is needed before reaching definitive conclusions regarding the frequency and importance of observed interactions.
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: Roger L Williams; Adrian F Bristow; Walter W Hauck; V Srini Srinivasan; Tina Morris; Fouad Atouf; Michael Ambrose; Koduru V Surendranath; Ranjan Chakrabarty; Krishna Menon Journal: AAPS J Date: 2014-04-02 Impact factor: 4.009
Authors: M-L Chen; A B Straughn; N Sadrieh; M Meyer; P J Faustino; A B Ciavarella; B Meibohm; C R Yates; A S Hussain Journal: Pharm Res Date: 2006-10-18 Impact factor: 4.580