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Activity Number:
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370
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Type:
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Topic Contributed
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Date/Time:
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Wednesday, August 1, 2007 : 8:30 AM to 10:20 AM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #309320 |
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Title:
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A Semiparametric Response Surface Model for Assessing Drug Interaction
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Author(s):
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Maiying Kong*+ and J. Jack Lee
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Companies:
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University of Louisville and The University of Texas M.D. Anderson Cancer Center
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Address:
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Bioinformatics and Biostatistics, Louisville, KY, 40202,
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Keywords:
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drug interaction ; synergy ; semiparametric model ; bootstrap method
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Abstract:
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Existing response surface models for assessing drug interactions are not adequate to capture the complex patterns when synergy, additivity, or antagonism exist for two drug combinations. We propose a two-component semiparametric response surface model with a parametric function to describe the additive effect of a combination dose and a nonparametric function to capture the departure from the additive effect. The nonparametric function is estimated using the technique developed in thin plate splines, and the pointwise confidence interval for this function is constructed based on bootstrap method. The proposed semiparametric model offers an effective way of formulating the additive effect while allowing the flexibility of modeling a departure from additivity. Example and simulations are given to illustrate that the proposed model performs very well.
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