Alternative confidence intervals for the assessment of bioequivalence in four-period cross-over designs

Bioequivalence studies are conducted to demonstrate equivalence in the bioavailability of the active ingredient in different formulations. The U.S. Food and Drug Administration (FDA) requires pharmaceutical companies to show bioequivalence between different formulations or generic companies to show...

Full description

Saved in:
Bibliographic Details
Published in:Statistics in medicine 2002-07, Vol.21 (13), p.1825-1847
Main Authors: Quiroz, Jorge, Ting, Naitee, Wei, Greg C. G., Burdick, Richard K.
Format: Article
Language:English
Subjects:
Biological and medical sciences
Clinical trial. Drug monitoring
Computer Simulation
Computerized, statistical medical data processing and models in biomedicine
Confidence Intervals
Cross-Over Studies
Drugs, Generic - pharmacokinetics
General pharmacology
Humans
Medical sciences
Medical statistics
mixed model
Pharmacology. Drug treatments
Randomized Controlled Trials as Topic - methods
Therapeutic Equivalency
United States
United States Food and Drug Administration
variance components
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Bioequivalence studies are conducted to demonstrate equivalence in the bioavailability of the active ingredient in different formulations. The U.S. Food and Drug Administration (FDA) requires pharmaceutical companies to show bioequivalence between different formulations or generic companies to show bioequivalence between generic drugs and brand drugs before approval. A recent FDA guidance on bioequivalence proposes criteria for assessment of population bioequivalence (PBE) and individual bioequivalence (IBE) in a four‐period cross‐over design. In this paper, computer simulation is used to compare modified large sample (MLS) upper bounds with those proposed by the FDA to test for both PBE and IBE. The comparison criteria are the ability to maintain the stated test size and the simulated power of tests based on these bounds. Copyright © 2002 John Wiley & Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/sim.1151