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Activity Number:
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66
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Type:
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Contributed
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Date/Time:
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Sunday, July 29, 2007 : 4:00 PM to 5:50 PM
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Sponsor:
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Biopharmaceutical Section
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| Abstract - #308815 |
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Title:
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Semiparametric Mixed Analysis on PK/PD Models Using Differential Equations
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Author(s):
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Yi Wang*+ and Kent Eskridge and Shunpu Zhang
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Companies:
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University of Nebraska-Lincoln and University of Nebraska-Lincoln and University of Nebraska-Lincoln
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Address:
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4300 Holdrege Street A201, Lincoln, NE, 68503,
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Keywords:
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semiparametric ; ODEs ; spline-enhanced ; nonlinear mixed models
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Abstract:
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Motivated by the use of semiparametric nonlinear mixed-effects modeling on longitudinal data, we develop a new ordinary differential equations (ODEs) based method designed for general PK/PD models, which are not addressed by Ke and Wang (2001) and Li et al. (2002). In our method the part of ODEs is relaxed and assumed to be nonparametric functions that will be decided by data and estimated nonparametrically using splines. This setup makes identification of structural model misspecification feasible by quantifying the model uncertainty and provides flexibility for accommodating possible structural model deficiencies, which are accomplished by implementing the spline-enhanced differential equations in a nonlinear mixed-effects modeling setup. We illustrate the method with an application to cefamandole data and we evaluate its performance through simulation.
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