{"product_id":"introduction-to-population-pharmacokinetic-pharmacodynamic-analysis-with-nonlinear-mixed-effects-models-hardback-9780470582299","title":"Introduction to Population Pharmacokinetic \/ Pharmacodynamic Analysis with Nonlinear Mixed Effects Models (Hardback) 9780470582299","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eIntroduction to Population Pharmacokinetic \/ Pharmacodynamic Analysis with Nonlinear Mixed Effects Models\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eJoel S. Owen (Author), Jill Fiedler-Kelly (Author)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9780470582299, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 29 July 2014\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e320 pages\u003cbr\u003e23.6 x 15.5 x 2.3 cm, 0.567 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cem\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e“This book may make the “User Guide V experience” a story from the good old times for the next generation of pharmacometricians.”  (\u003ci\u003eCPT: Pharmacometrics \u0026amp; Systems Pharmacology\u003c\/i\u003e, 22 December 2014)\u003c\/p\u003e\u003c\/font\u003e\u003c\/em\u003e\u003c\/p\u003e\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003eThis book provides a user-friendly, hands-on introduction to the Nonlinear Mixed Effects Modeling (NONMEM) system, the most powerful tool for pharmacokinetic \/ pharmacodynamic analysis.\u003cbr\u003e • Introduces requisite background to using Nonlinear Mixed Effects Modeling (NONMEM), covering data requirements, model building and evaluation, and quality control aspects\u003cbr\u003e • Provides examples of nonlinear modeling concepts and estimation basics with discussion on  the model building process and applications of empirical Bayesian estimates in the drug development environment\u003cbr\u003e • Includes detailed chapters on data set structure, developing control streams for modeling and simulation, model applications, interpretation of NONMEM output and results, and quality control\u003cbr\u003e • Has datasets, programming code, and practice exercises with solutions, available on a supplementary website\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xiii\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 1 The Practice of Pharmacometrics 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003c\/p\u003e \u003cp\u003e1.2 Applications of Sparse Data Analysis 2\u003c\/p\u003e \u003cp\u003e1.3 Impact of Pharmacometrics 4\u003c\/p\u003e \u003cp\u003e1.4 Clinical Example 5\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 2 Population Model Concepts and Terminology 9\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 9\u003c\/p\u003e \u003cp\u003e2.2 Model Elements 10\u003c\/p\u003e \u003cp\u003e2.3 Individual Subject Models 11\u003c\/p\u003e \u003cp\u003e2.4 Population Models 12\u003c\/p\u003e \u003cp\u003e2.4.1 Fixed-Effect Parameters 13\u003c\/p\u003e \u003cp\u003e2.4.2 Random-Effect Parameters 14\u003c\/p\u003e \u003cp\u003e2.5 Models of Random Between-Subject Variability (L1) 17\u003c\/p\u003e \u003cp\u003e2.5.1 Additive Variation 17\u003c\/p\u003e \u003cp\u003e2.5.2 Constant Coefficient of Variation 18\u003c\/p\u003e \u003cp\u003e2.5.3 Exponential Variation 18\u003c\/p\u003e \u003cp\u003e2.5.4 Modeling Sources of Between-Subject Variation 19\u003c\/p\u003e \u003cp\u003e2.6 Models of Random Variability in Observations (L2) 19\u003c\/p\u003e \u003cp\u003e2.6.1 Additive Variation 20\u003c\/p\u003e \u003cp\u003e2.6.2 Constant Coefficient of Variation 21\u003c\/p\u003e \u003cp\u003e2.6.3 Additive Plus CCV Model 22\u003c\/p\u003e \u003cp\u003e2.6.4 Log-Error Model 24\u003c\/p\u003e \u003cp\u003e2.6.5 Relationship Between RV Expressions and Predicted Concentrations 24\u003c\/p\u003e \u003cp\u003e2.6.6 Significance of the Magnitude of RV 25\u003c\/p\u003e \u003cp\u003e2.7 Estimation Methods 26\u003c\/p\u003e \u003cp\u003e2.8 Objective Function 26\u003c\/p\u003e \u003cp\u003e2.9 Bayesian Estimation 27\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 3 NONMEM Overview and Writing an NM-TRAN Control Stream 28\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 28\u003c\/p\u003e \u003cp\u003e3.2 Components of the NONMEM System 28\u003c\/p\u003e \u003cp\u003e3.3 General Rules 30\u003c\/p\u003e \u003cp\u003e3.4 Required Control Stream Components 31\u003c\/p\u003e \u003cp\u003e3.4.1 $PROBLEM Record 31\u003c\/p\u003e \u003cp\u003e3.4.2 The $DATA Record 32\u003c\/p\u003e \u003cp\u003e3.4.3 The $INPUT Record 35\u003c\/p\u003e \u003cp\u003e3.5 Specifying the Model in NM-TRAN 35\u003c\/p\u003e \u003cp\u003e3.5.1 Calling PREDPP Subroutines for Specific PK Models 35\u003c\/p\u003e \u003cp\u003e3.5.2 Specifying the Model in the $PK Block 38\u003c\/p\u003e \u003cp\u003e3.5.3 Specifying Residual Variability in the $ERROR Block 45\u003c\/p\u003e \u003cp\u003e3.5.4 Specifying Models Using the $PRED Block 49\u003c\/p\u003e \u003cp\u003e3.6 Specifying Initial Estimates with $THETA, $OMEGA, and $SIGMA 50\u003c\/p\u003e \u003cp\u003e3.7 Requesting Estimation and Related Options 56\u003c\/p\u003e \u003cp\u003e3.8 Requesting Estimates of the Precision of Parameter Estimates 62\u003c\/p\u003e \u003cp\u003e3.9 Controlling the Output 63\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 4 Datasets 66\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction 66\u003c\/p\u003e \u003cp\u003e4.2 Arrangement of the Dataset 68\u003c\/p\u003e \u003cp\u003e4.3 Variables of the Dataset 71\u003c\/p\u003e \u003cp\u003e4.3.1 TIME 71\u003c\/p\u003e \u003cp\u003e4.3.2 DATE 71\u003c\/p\u003e \u003cp\u003e4.3.3 ID 72\u003c\/p\u003e \u003cp\u003e4.3.4 DV 74\u003c\/p\u003e \u003cp\u003e4.3.5 MDV 74\u003c\/p\u003e \u003cp\u003e4.3.6 CMT 74\u003c\/p\u003e \u003cp\u003e4.3.7 EVID 75\u003c\/p\u003e \u003cp\u003e4.3.8 AMT 76\u003c\/p\u003e \u003cp\u003e4.3.9 RATE 77\u003c\/p\u003e \u003cp\u003e4.3.10 ADDL 78\u003c\/p\u003e \u003cp\u003e4.3.11 II 79\u003c\/p\u003e \u003cp\u003e4.3.12 SS 80\u003c\/p\u003e \u003cp\u003e4.4 Constructing Datasets with Flexibility to Apply Alternate Models 80\u003c\/p\u003e \u003cp\u003e4.5 Examples of Event Records 81\u003c\/p\u003e \u003cp\u003e4.5.1 Alternatives for Specifying Time 81\u003c\/p\u003e \u003cp\u003e4.5.2 Infusions and Zero-Order Input 81\u003c\/p\u003e \u003cp\u003e4.5.3 Using ADDL 82\u003c\/p\u003e \u003cp\u003e4.5.4 Steady-State Approach 83\u003c\/p\u003e \u003cp\u003e4.5.5 Samples Before and After Achieving Steady State 83\u003c\/p\u003e \u003cp\u003e4.5.6 Unscheduled Doses in a Steady-State Regimen 84\u003c\/p\u003e \u003cp\u003e4.5.7 Steady-State Dosing with an Irregular Dosing Interval 84\u003c\/p\u003e \u003cp\u003e4.5.8 Multiple Routes of Administration 85\u003c\/p\u003e \u003cp\u003e4.5.9 Modeling Multiple Dependent Variable Data Types 86\u003c\/p\u003e \u003cp\u003e4.5.10 Dataset for $PRED 86\u003c\/p\u003e \u003cp\u003e4.6 Beyond Doses and Observations 87\u003c\/p\u003e \u003cp\u003e4.6.1 Other Data Items 87\u003c\/p\u003e \u003cp\u003e4.6.2 Covariate Changes over Time 88\u003c\/p\u003e \u003cp\u003e4.6.3 Inclusion of a Header Row 89\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 5 Model Building: Typical Process 90\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 90\u003c\/p\u003e \u003cp\u003e5.2 Analysis Planning 90\u003c\/p\u003e \u003cp\u003e5.3 Analysis Dataset Creation 92\u003c\/p\u003e \u003cp\u003e5.4 Dataset Quality Control 93\u003c\/p\u003e \u003cp\u003e5.5 Exploratory Data Analysis 94\u003c\/p\u003e \u003cp\u003e5.5.1 EDA: Population Description 95\u003c\/p\u003e \u003cp\u003e5.5.2 EDA: Dose-Related Data 99\u003c\/p\u003e \u003cp\u003e5.5.3 EDA: Concentration-Related Data 99\u003c\/p\u003e \u003cp\u003e5.5.4 EDA: Considerations with Large Datasets 111\u003c\/p\u003e \u003cp\u003e5.5.5 EDA: Summary 115\u003c\/p\u003e \u003cp\u003e5.6 Base Model Development 116\u003c\/p\u003e \u003cp\u003e5.6.1 Standard Model Diagnostic Plots and Interpretation 116\u003c\/p\u003e \u003cp\u003e5.6.2 Estimation of Random Effects 130\u003c\/p\u003e \u003cp\u003e5.6.3 Precision of Parameter Estimates (Based on $COV Step) 137\u003c\/p\u003e \u003cp\u003e5.7 Covariate Evaluation 138\u003c\/p\u003e \u003cp\u003e5.7.1 Covariate Evaluation Methodologies 140\u003c\/p\u003e \u003cp\u003e5.7.2 Statistical Basis for Covariate Selection 141\u003c\/p\u003e \u003cp\u003e5.7.3 Diagnostic Plots to Illustrate Parameter-Covariate Relationships 143\u003c\/p\u003e \u003cp\u003e5.7.4 Typical Functional Forms for Covariate-Parameter Relationships 148\u003c\/p\u003e \u003cp\u003e5.7.5 Centering Covariate Effects 156\u003c\/p\u003e \u003cp\u003e5.7.6 Forward Selection Process 160\u003c\/p\u003e \u003cp\u003e5.7.7 Evaluation of the Full Multivariable Model 167\u003c\/p\u003e \u003cp\u003e5.7.8 Backward Elimination Process 169\u003c\/p\u003e \u003cp\u003e5.7.9 Other Covariate Evaluation Approaches 171\u003c\/p\u003e \u003cp\u003e5.8 Model Refinement 172\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 6 Interpreting the NONMEM Output 178\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 178\u003c\/p\u003e \u003cp\u003e6.2 Description of the Output Files 178\u003c\/p\u003e \u003cp\u003e6.3 The NONMEM Report File 179\u003c\/p\u003e \u003cp\u003e6.3.1 NONMEM-Related Output 179\u003c\/p\u003e \u003cp\u003e6.3.2 PREDPP-Related Output 180\u003c\/p\u003e \u003cp\u003e6.3.3 Output from Monitoring of the Search 180\u003c\/p\u003e \u003cp\u003e6.3.4 Minimum Value of the Objective Function and Final Parameter Estimates 182\u003c\/p\u003e \u003cp\u003e6.3.5 Covariance Step Output 186\u003c\/p\u003e \u003cp\u003e6.3.6 Additional Output 187\u003c\/p\u003e \u003cp\u003e6.4 Error Messages: Interpretation and Resolution 188\u003c\/p\u003e \u003cp\u003e6.4.1 NM-TRAN Errors 188\u003c\/p\u003e \u003cp\u003e6.4.2 $ESTIMATION Step Failures 189\u003c\/p\u003e \u003cp\u003e6.4.3 $COVARIANCE Step Failures 190\u003c\/p\u003e \u003cp\u003e6.4.4 PREDPP Errors 191\u003c\/p\u003e \u003cp\u003e6.4.5 Other Types of NONMEM Errors 192\u003c\/p\u003e \u003cp\u003e6.4.6 FORTRAN Compiler or Other Run-Time Errors 193\u003c\/p\u003e \u003cp\u003e6.5 General Suggestions for Diagnosing Problems 193\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 7 App lications Using Parameter Estimates from the Individual 198\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 198\u003c\/p\u003e \u003cp\u003e7.2 Bayes Theorem and Individual Parameter Estimates 200\u003c\/p\u003e \u003cp\u003e7.3 Obtaining Individual Parameter Estimates 202\u003c\/p\u003e \u003cp\u003e7.4 Applications of Individual Parameter Estimates 204\u003c\/p\u003e \u003cp\u003e7.4.1 Generating Subject-Specific Exposure Estimates 204\u003c\/p\u003e \u003cp\u003e7.4.2 Individual Exposure Estimates for Group Comparisons 210\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 8 Introduction to Model Evaluation 212\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 212\u003c\/p\u003e \u003cp\u003e8.2 Internal Validation 212\u003c\/p\u003e \u003cp\u003e8.3 External Validation 213\u003c\/p\u003e \u003cp\u003e8.4 Predictive Performance Assessment 214\u003c\/p\u003e \u003cp\u003e8.5 Objective Function Mapping 217\u003c\/p\u003e \u003cp\u003e8.6 Leverage Analysis 220\u003c\/p\u003e \u003cp\u003e8.7 Bootstrap Procedures 222\u003c\/p\u003e \u003cp\u003e8.8 Visual and Numerical Predictive Check Procedures 223\u003c\/p\u003e \u003cp\u003e8.8.1 The VPC Procedure 223\u003c\/p\u003e \u003cp\u003e8.8.2 Presentation of VPC Results 225\u003c\/p\u003e \u003cp\u003e8.8.3 The Numerical Predictive Check (NPC) Procedure 229\u003c\/p\u003e \u003cp\u003e8.9 Posterior Predictive Check Procedures 229\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 9 User-Written Models 232\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 232\u003c\/p\u003e \u003cp\u003e9.2 $MODEL 235\u003c\/p\u003e \u003cp\u003e9.3 $SUBROUTINES 236\u003c\/p\u003e \u003cp\u003e9.3.1 General Linear Models (ADVAN5 and ADVAN7) 236\u003c\/p\u003e \u003cp\u003e9.3.2 General Nonlinear Models (ADVAN6, ADVAN8, ADVAN9, and ADVAN13) 238\u003c\/p\u003e \u003cp\u003e9.3.3 $DES 238\u003c\/p\u003e \u003cp\u003e9.4 A Series of Examples 240\u003c\/p\u003e \u003cp\u003e9.4.1 Defined Fractions Absorbed by Zero- and First-Order Processes 240\u003c\/p\u003e \u003cp\u003e9.4.2 Sequential Absorption with First-Order Rates, without Defined Fractions 242\u003c\/p\u003e \u003cp\u003e9.4.3 Parallel Zero-Order and First-Order Absorption, without Defined Fractions 243\u003c\/p\u003e \u003cp\u003e9.4.4 Parallel First-Order Absorption Processes, without Defined Fractions 245\u003c\/p\u003e \u003cp\u003e9.4.5 Zero-Order Input into the Depot Compartment 246\u003c\/p\u003e \u003cp\u003e9.4.6 Parent and Metabolite Model: Differential Equations 247\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 10 PK\/PD Models 250\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 250\u003c\/p\u003e \u003cp\u003e10.2 Implementation of PD Models in NONMEM 251\u003c\/p\u003e \u003cp\u003e10.3 $PRED 252\u003c\/p\u003e \u003cp\u003e10.3.1 Direct-Effect PK\/PD Examples: PK Concentrations in the Dataset 253\u003c\/p\u003e \u003cp\u003e10.3.2 Direct-Effect PK\/PD Example: PK from Computed Concentrations 255\u003c\/p\u003e \u003cp\u003e10.4 $PK 256\u003c\/p\u003e \u003cp\u003e10.4.1 Specific ADVANs (ADVAN1–ADVAN4 and ADVAN10–ADVAN12) 256\u003c\/p\u003e \u003cp\u003e10.4.2 General ADVANs (ADVAN5–ADVAN9 and ADVAN13) 257\u003c\/p\u003e \u003cp\u003e10.4.3 PREDPP: Effect Compartment Link Model Example (PD in $ERROR) 257\u003c\/p\u003e \u003cp\u003e10.4.4 PREDPP: Indirect Response Model Example: PD in $DES 259\u003c\/p\u003e \u003cp\u003e10.5 Odd-Type Data: Analysis of Noncontinuous Data 261\u003c\/p\u003e \u003cp\u003e10.6 PD Model Complexity 262\u003c\/p\u003e \u003cp\u003e10.7 Communication of Results 263\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 11 Simulation Basics 265\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 265\u003c\/p\u003e \u003cp\u003e11.2 The Simulation Plan 265\u003c\/p\u003e \u003cp\u003e11.2.1 Simulation Components 266\u003c\/p\u003e \u003cp\u003e11.2.2 The Input–Output Model 266\u003c\/p\u003e \u003cp\u003e11.2.3 The Covariate Distribution Model 270\u003c\/p\u003e \u003cp\u003e11.2.4 The Trial Execution Model 273\u003c\/p\u003e \u003cp\u003e11.2.5 Replication of the Study 274\u003c\/p\u003e \u003cp\u003e11.2.6 Analysis of the Simulated Data 275\u003c\/p\u003e \u003cp\u003e11.2.7 Decision Making Using Simulations 275\u003c\/p\u003e \u003cp\u003e11.3 Miscellaneous Other Simulation-Related Considerations 276\u003c\/p\u003e \u003cp\u003e11.3.1 The Seed Value 276\u003c\/p\u003e \u003cp\u003e11.3.2 Consideration of Parameter Uncertainty 277\u003c\/p\u003e \u003cp\u003e11.3.3 Constraining Random Effects or Responses 278\u003c\/p\u003e \u003cp\u003e\u003cb\u003eCHAPTER 12 Quality Control 285\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 285\u003c\/p\u003e \u003cp\u003e12.2 QC of the Data Analysis Plan 285\u003c\/p\u003e \u003cp\u003e12.3 Analysis Dataset Creation 286\u003c\/p\u003e \u003cp\u003e12.3.1 Exploratory Data Analysis and Its Role in Dataset QC 287\u003c\/p\u003e \u003cp\u003e12.3.2 QC in Data Collection 287\u003c\/p\u003e \u003cp\u003e12.4 QC of Model Development 288\u003c\/p\u003e \u003cp\u003e12.4.1 QC of NM-TRAN Control Streams 289\u003c\/p\u003e \u003cp\u003e12.4.2 Model Diagnostic Plots and Model Evaluation Steps as QC 290\u003c\/p\u003e \u003cp\u003e12.5 Documentation of QC Efforts 290\u003c\/p\u003e \u003cp\u003e12.6 Summary 291\u003c\/p\u003e \u003cp\u003eReferences 292\u003c\/p\u003e \u003cp\u003eIndex 293\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Chemistry [\u003ca title=\"See our other books on Chemistry\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Chemistry%20%5BPN%5D%22\"\u003ePN\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley","offers":[{"title":"Brand New","offer_id":52475003339032,"sku":"9780470582299","price":76.79,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9780470582299.jpg?v=1785803202","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/introduction-to-population-pharmacokinetic-pharmacodynamic-analysis-with-nonlinear-mixed-effects-models-hardback-9780470582299","provider":"Freshly Printed Books","version":"1.0","type":"link"}