This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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670
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Biopharmaceutical Section
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Abstract - #306513 |
Title:
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A Simulation Study to Compare Modeling Approaches for Dose Proportionality Data
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Author(s):
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Andrea Maes*+ and Wen-Lin Luo and Yu Ding and Deborah Panebianco
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Companies:
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Novartis Pharmaceuticals Corporation and Merck & Co., Inc. and Merck Research Laboratories and Merck & Co., Inc.
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Address:
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180 Park Ave, Building 104-2K27, Florham Park, NJ, 07932,
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Keywords:
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Pharmacokinetics ;
Power model ;
Contrasts
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Abstract:
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A dose proportionality study is conducted during drug development to support a claim of linear pharmacokinetics in the label. Dose dependent pharmacokinetic (PK) parameters from the study are often analyzed using a power model in which log(PK) data are regressed onto log(dose). An estimate of the slope and its confidence interval (CI) are calculated from the model with 1 reflecting proportionality. Through simulation, we compare the power and type I error of asserting proportionality after modeling log(dose) as a continuous versus categorical factor in a linear mixed model. The slope is estimated through contrasts in the latter approach. Variance heterogeneity and slight deviations from log-scale linearity are also considered. Results show that the contrast method has greater power and closer to nominal CI coverage under slight non-linearity, but may be more sensitive to heterogeneity.
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