PharmPK Discussion - Analysis of 3-treatment bioequivalence studies

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On 5 Mar 1999 at 11:02:46, "James D. Coyle" (coyle.at.dendrite.pharmacy.ohio-state.edu) sent the message


I am designing a three-treatment, three-period, crossover bioequivalence
study.  I'm familiar with the FDA-supported "two one-sided t-tests approach"
(or the equivalent "90% confidence interval approach") to analyzing data
from a two-treatment, two-period, crossover  bioequivalence study and the
corresponding sample size tables.  I've been unable to find any information
on what modifications need to be made when this approach is extended to a
three-treatment design.  Does anyone have any insights?

Thanks in advance for any help you can give!

Jim Coyle

James D. Coyle, Pharm.D.
Assistant Professor
College of Pharmacy, The Ohio State University
500 W. 12th Ave.
Columbus, OH  43210
Telephone:  (614) 292-7103
FAX :           (614) 292-1335
E-mail:         Coyle.1.-at-.osu.edu

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On 6 Mar 1999 at 16:56:21, David_Bourne (david.-a-.pharm.cpb.uokhsc.edu) sent the message

[Two replies - db]

From: Mallikaarjun Suresh 
To: "'PharmPK.-at-.pharm.cpb.uokhsc.edu'" 
Subject: RE: PharmPK analysis of 3-treatment bioequivalence studies
Date: Fri, 5 Mar 1999 14:00:59 -0500
MIME-Version: 1.0

The following references address this issue :

1.  Chow SC, Liu JP -  On Assessment of Bioequivalence Under a Higher-Order
Crossover Design, J Biopharm Stats, 2(2), 239-256, 1992
2.  Chen KW, Chow SC, Li G - A Note on Sample Size Determination for
Bioequivalence Studies with Higher-Order Crossover Designs, JPB, 25(6),
753-765, 1997

Suresh

Suresh Mallikaarjun, Ph.D.
Assistant Director
Clinical PK//PD and Metabolism
Otsuka America Pharmaceuticals

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X-Originating-IP: [130.238.41.37]
From: "shuqiu zhang" 
To: PharmPK.-a-.pharm.cpb.uokhsc.edu
Subject: Re: PharmPK analysis of 3-treatment bioequivalence studies
Date: Sat, 06 Mar 1999 13:15:33 CET
Mime-Version: 1.0

Hi Jim Coyle,
Recently I also worked on statistic analysis for my clinical trial data
=2E As my knoweledge, I think you could use ANOVA, by post hoc or special
contrast method you can compare every  pair comparision.
Shuqiu

Shuqiu Zhang
Sernander v=E4g 2:241, s-752 61 Uppsala,Sweden
Tel:4618-4714304(o),Fax:4618-4714003

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