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Pharmacokinetic-Pharmacodynamic Modeling and Simulation [electronic resource] /by Peter L. Bonate.

by Bonate, Peter L [author.]; SpringerLink (Online service).
Material type: materialTypeLabelBookPublisher: Boston, MA : Springer US, 2006.Description: XII, 387 p. online resource.ISBN: 9780387271996.Subject(s): Medicine | Toxicology | Biomedicine | Pharmacology/ToxicologyDDC classification: 615 Online resources: Click here to access online
Contents:
The Art of Modeling -- Linear Models and Regression -- Nonlinear Models and Regression -- Variance Models, Weighting, and Transformations -- Case Studies in Linear and Nonlinear Modeling -- Linear Mixed Effects Models -- Nonlinear Mixed Effects Models: Theory -- Nonlinear Mixed Effects Models: Practical Issues -- Nonlinear Mixed Effects Models: Case Studies.
In: Springer eBooksSummary: This book presents both the art and science behind pharmacokinetic-pharmacodynamic modeling. Using a building-block approach, the author starts from linear and nonlinear models at the individual level and proceeds to develop more complex linear and nonlinear mixed effects models at the population level, with particular emphasis on showing the interrelationships between the various model types. The theory behind the methods are illustrated using real data drawn from the literature and from the author’s own experiences in drug development. Data are analyzed using a variety of software, including SAS, WinNonlin, SAAM II, and NONMEM. A key component of the book is to show how models are accepted and rejected, ultimately leading to a useful and informative model that can be utilized using computer simulation to answer "what-if" questions.
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The Art of Modeling -- Linear Models and Regression -- Nonlinear Models and Regression -- Variance Models, Weighting, and Transformations -- Case Studies in Linear and Nonlinear Modeling -- Linear Mixed Effects Models -- Nonlinear Mixed Effects Models: Theory -- Nonlinear Mixed Effects Models: Practical Issues -- Nonlinear Mixed Effects Models: Case Studies.

This book presents both the art and science behind pharmacokinetic-pharmacodynamic modeling. Using a building-block approach, the author starts from linear and nonlinear models at the individual level and proceeds to develop more complex linear and nonlinear mixed effects models at the population level, with particular emphasis on showing the interrelationships between the various model types. The theory behind the methods are illustrated using real data drawn from the literature and from the author’s own experiences in drug development. Data are analyzed using a variety of software, including SAS, WinNonlin, SAAM II, and NONMEM. A key component of the book is to show how models are accepted and rejected, ultimately leading to a useful and informative model that can be utilized using computer simulation to answer "what-if" questions.

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