Mathematical modeling of pharmacokinetic data / David W.A. Bourne

Includes bibliographical references (pages 133-136) and index

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- Chapter 1: Why Model the Data? -- 1.1 Condense the Data -- 1.2 Exploring Mechanisms -- 1.3 Making Predictions -- Chapter 2: General Approach -- 2.1 General Method -- 2.2 Error in y Alone -- 2.3 Parameter Adjustments -- Chapter 3: Pharmacokinetic Models -- 3.1 Compartmental Models -- 3.2 Physiologically Based Models -- 3.3 Pharmacodynamic Models -- Chapter 4: Simulation of Data -- 4.1 Explicit Equations -- 4.2 Implicit Equations -- 4.3 Differential Equations -- 4.4 Integration Using Laplace Transforms -- 4.5 Numerical Integration of Differential Equations -- Chapter 5: Initial Estimates -- 5.1 Graphical Methods -- 5.2 Linear Regression -- 5.3 Curve Stripping -- 5.4 Area under the Curve Estimation -- 5.5 Deconvolution -- Chapter 6: Nonlinear Regression -- 6.1 Grid Search Method -- 6.2 Steepest Descent Method -- 6.3 Gauss-Newton Methods -- 6.4 Simplex Method -- 6.5 Local Minima -- Chapter 7: Weighting Schemes -- 7.1 Equal Weight -- 7.2 Variance Model -- 7.3 Iteratively Reweighted Least Squares -- 7.4 Extended Least Squares -- 7.5 Bayesian Methods -- 7.6 Analysis of Population Data -- Chapter 8: Evaluation of Program Output -- 8.1 Tabular Output -- 8.2 Graphical Output -- 8.3 Statistical Output -- Chapter 9: Experimental Design -- 9.1 Pilot Study -- 9.2 Identifiability-Sampling Sites -- 9.3 Optimal Sampling-Sampling Times -- 9.4 Model Testing -- Appendix -- References -- Index