Literature DB >> 1876786

Sample sizes for bioequivalence studies.

C M Metzler1.   

Abstract

In recent years a number of decision rules, based on sound statistical principles, have been proposed for deciding if a test formulation is bioequivalent to a reference formulation. The decision rule based on confidence intervals has been accepted by regulatory agencies, at least by the Food and Drug Administration of the United States. A useful property of this decision rule is that the regulatory agency need not require a certain sample size, since the level of protection against wrongly deciding bioequivalence is set by the choice of the alpha level used to compute the confidence intervals. The manufacturer claiming bioequivalence is concerned about sample size, for sample size determines the probability of falsely deciding non-bioequivalence when the test formulation does indeed have an acceptable relative bioavailability. Curves of probability of rejecting bioequivalence have been computed for error coefficient of variation of 10, 20 and 30 per cent, for relative bioavailability from 70 to 130 per cent, and for protection levels of 90 and 95 per cent. These curves can be used for choosing the sample size for a bioequivalence study.

Mesh:

Year:  1991        PMID: 1876786     DOI: 10.1002/sim.4780100617

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  3 in total

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Journal:  Exp Clin Psychopharmacol       Date:  2010-08       Impact factor: 3.157

2.  Differential influences of ethanol on early exposure to racemic methylphenidate compared with dexmethylphenidate in humans.

Authors:  Kennerly S Patrick; Arthur B Straughn; Owen T Reeves; Hilary Bernstein; Guinevere H Bell; Erica R Anderson; Robert J Malcolm
Journal:  Drug Metab Dispos       Date:  2012-10-25       Impact factor: 3.922

3.  Ethanol Interactions With Dexmethylphenidate and dl-Methylphenidate Spheroidal Oral Drug Absorption Systems in Healthy Volunteers.

Authors:  Hao-Jie Zhu; Kennerly S Patrick; Arthur B Straughn; Owen T Reeves; Hilary Bernstein; Jian Shi; Heather J Johnson; Joshua M Knight; Aaron T Smith; Robert J Malcolm; John S Markowitz
Journal:  J Clin Psychopharmacol       Date:  2017-08       Impact factor: 3.153

  3 in total

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