Pharmacokinetic & Pharmacodynamic Data Analysis

Transcription

1 Pharmacokinetic & Pharmacodynamic Data Analysis CONCEPTS AND APPLICATIONS 4TH EDITION REVISED AND EXPANDED

2 Table of Contents Chapter 1 - General Principles Introduction Basic Concepts Why Model the Data The Art of Successful Modeling How to Use This Book Chapter 2 - Pharmacokinetic Concepts Background One Compartment Models Intravenous bolus administration Constant rate infusion Integration of clearance and volume Extravascular administration Estimation of absorption parameters from first-order input Estimation of absorption parameters from zero-order input What lies behind the apparent absorption rate constant? Estimation of bioavailability How does input to the plasma compartment vary? Multiple dosing Absorption from multiple sites Conclusions for extravascular dosing Plasma and Urine Data Basic renal physiology Derivation of equations Analysis of urinary excretion data Estimation of bioavailability from urinary data Multi-Compartment Models Catenary and mammillary models Intravenous bolus administration Reparameterization of the two-compartment model Constant rate infusion Extravascular administration Plasma and urine data Clearance Concepts Derivation of clearance Extraction Impact of route of administration In vitro/in vivo comparisons of clearance Hepatic clearance models Additional reading Turnover Background

3 PK/PD Data Analysis: Concepts and Applications Introduction to turnover of proteins, peptides and antibodies Turnover of immunoglobulins Turnover of hormones - Estradiol Comparison of models Turnover of body temperature Feedback Nonlinear Systems - Capacity, Time, Flow and Binding What causes nonlinearity and how is it assessed? Nonlinear kinetics - Capacity Bolus input - Capacity limited elimination Constant rate input - Capacity limited elimination First order input - Capacity limited elimination Conclusions on capacity limited elimination Nonlinear kinetics - Time Background Turnover of induction Heteroinduction - Pentobarbital induction of nortriptyline Autoinduction Nonlinear kinetics - Flow Nonlinear kinetics - Binding Nonlinear drug metabolite models Ethanol combines capacity, time and flow dependencies Non-Compartmental Analysis Non-compartmental versus regression analysis Computational methods Linear trapezoidal rule Computational methods Log-linear trapezoidal rule Strategies for estimation of \ Pertinent pharmacokinetic estimates Issues related to steady state Metabolite kinetics When half-life is short relative to input time How to Assess Exposure What do we mean by exposure? The case(s) for abandoning dose Exposure based on total concentrations Exposure based on unbound concentrations Conclusions on exposure Inter-Species Scaling When and why do we extrapolate data across species? What is allometry? Allometric equations Time scales differ between different species Estimation of parameters The elementary Dedrick plot The complex Dedrick plot Integration of concepts 215

4 Physiological variables of 11 animal species and man Allometric scaling of turnover parameters General conclusions about exposure and scaling Additional Reading Chapter 3 Pharmacodynamic Concepts Background Definitions Law of Mass Action Receptor Binding Models Saturation studies Displacement studies Pharmacodynamic Models Background Linear effect-concentration model Log-linear effect-concentration model Ordinary E^ model Sigmoid E max model Composite E nax model Multiple binding site model Interaction Models Competitive antagonism Noncompetitive antagonism General empirical dynamic model for two drugs Enantiomer interaction models Additional sigmoidal models Kinetics of pharmacological responses Area under the response-time curve Turnover Models - Reversible Drug Effects Background Model taxonomy Model characteristics Initial parameter estimates Model behavior Model extensions Turnover Models - Irreversible Drug Effects Simple irreversible action - Cell killing Cell growth coupled with cell killing Minimum inhibitory concentration Effect Compartment (Link) Models Background One-compartment models Two-compartment models Integration of time into the Hill equation Alternative parameterizations Some literature examples and simulations Problems and pitfalls 299

5 PK/PD Data Analysis: Concepts and Applications 3.10 Dose-Response-Time Models Background Mioticdata Acetycholinesterase turnover Antinociception Body temperature Turnover of antipsychotic effects - Disease modeling Conclusions about dose-response-time data modeling Tolerance and Rebound Models Background Systems analysis Time dependent attenuation of parameters Antagonistic metabolite model Tolerance compartment model Counteracting mechanisms Feedback and rebound Simple negative feedback on turnover rate Negative feedback via a moderator Negative feedback via a moderator and level of response Simulation of feedback via a moderator Pool model - Unidirectional flow Pool model - Bidirectional flow Comparisons with other models Modeling of cocaine response-time data Some thoughts about tolerance and dependence models Baseline Models Constant versus variable baseline models Oscillating turnover rates Transduction Models Synergistic Effects Modeled by Turnover Functions Synergistic Effects Modeled by Hyperbolic Functions Logistic Response Models Additional Reading Chapter 4 - Parameter Estimation Background Linear and Nonlinear Models Criteria for Best Fit - Minimization Methods Ordinary, weighted and extended least squares methods Generalized least squares method Considerations in the Choice of Weights Why weight? Constant absolute error Poisson error Constant relative error - Proportional error 370 Jj^^ ^^ _ 5Z^-

6 4.5 Application of Least Squares to Linear Models MA 4.6 Application of Least Squares to Nonlinear Models Background M^ Random search methods Stripping or peeling methods Linearization methods Simplex methods Constraints on the Parameter Space Estimating Functions of Parameters Validation of Software What do we mean by software validation? Computer systems validation Testing of user models Chapter 5 - Modeling Strategies Background Plot and Explore Data Understand your experimental data better Pooling of data Transformation for exploration Transformation for fitting Normalizing data How Complicated a Model? How many parameters? How do we specify the model? Combining several sources of data for modeling Parameter identifiability Ability to estimate parameters Obtaining Initial F^stimates Graphical methods and linear regression Kinetic data Dynamic steady state data Dynamic non-steady state data Dynamic repeated dose data Convolution and deconvolution analysis Background Theory Oral solution versus tablet Transdermal input Drug and metabolite data Bidirectional drug flux When all else fails Selection of the Minimization Algorithm Iterations Assessing the Goodness-of-Fit Analyzing the residuals Graphical presentation of residuals 441

7 PK/PD Data Analysis: Concepts and Applications Pure error versus lack of fit Parameter estimates - Accuracy Parameter estimates - Precision Correlation between observed and predicted values Correlation between parameters Condition number 5.8 Discrimination Between Rival Models Ftest Background The ordinary E rmx versus the sigmoid E mn model The ordinary E max versus the linear response model The hepatic distributed versus parallel tube model Akaike and Schwarz criteria 5.9 Outliers 5.10 A Checklist for Assessing Goodness-of-Fit 5.11 Additional Reading 6. Chapter 6 - Design Elements 6.1 Background 6.2 Tools for Experimental Design Delta function Variance inflation factor Partial derivatives Sensitivity analysis 6.3 General Design Issues of Kinetic/Dynamic Studies Bolus, infusion and first-order input Nonlinear kinetics Design of toxicokinetic studies Dynamic studies - Baseline Acute versus chronic dosing Pharmacokinetic and Pharmacodynamic Applications PK1 PK2 PK3 PK4 PK5 PK6 PK7 PK8 PK9 PK10 PK11 PK12 PK13 PK14 PK15 Pharmacokinetic Applications One-compartment iv bolus dosing One-compartment oral dosing One-compartment 1" and 0-order input One-compartment oral dosing One-compartment iv plasma/urine I One-compartment iv plasma/urine II Two-compartment iv bolus dosing Two-compartment distribution models Two-compartment model testing Simultaneous fitting of iv/po data Two-compartment repeated po dosing Intravenous and oral dosing Bolus plus constant rate infusion Multi-compartment model oral dosing Toxicokinetics I

8 PK16 Two-compartment iv plasma/urine 622 PK17 Nonlinear kinetics - Capacity I 628 PK18 Ethanol kinetics-capacity II 634 PK19 Metabolite kinetics-capacity III 650 PK20 Nonlinear kinetics - Capacity IV 666 PK21 Nonlinear kinetics Heteroinduction 676 PK22 Nonlinear kinetics - Autoinduction 684 PK23 Nonlinear kinetics - Flow I 691 PK24 Nonlinear kinetics - Flow II 698 PK25 Two-compartment plasma and urine analysis with rate and ARE plots 708 PK26 Toxicokinetics II - Multiple dose data 713 PK27 Toxicokinetics III - Repeated dose safety study 718 PK28 Allometry - Elementary Dedrick plot 723 PK29 Allometry - Complex Dedrick plot 729 PK30 Turnover I - Sc dosing of hormone 739 PK31 Turnover II Iv dosing of hormone 743 PK32 Turnover III - Nonlinear disposition 750 PK33 Transdermal input and kinetics 759 PK34 Reversible metabolism 764 PK35 Bayesian model - Digoxin 772 PK36 Time controlled drug delivery 777 PK37 In vitro/in vivo extrapolation I 780 PK38 In vitro/in vivo extrapolation II 788 PK39 Two-compartment plasma data Experimental design issues 796 PK40 Enterohepatic recirculation 803 PK41 Multiple intravenous infusions - NCA versus regression 808 PK42 Saturable absorption via transporters 814 PK43 Multiple absorption routes 823 PK44 Estimation of inhibitory constant K by means of SNLR 828 PK45 Toxicokinetics IV - Study Simulation 837 PK46 Long infusion and short half-life 839 PK47 Plasma protein binding modeling 844 PK48 One-compartment Michaelis-Menten kinetics-drug&metabolite in urine 851 PK49 In vitro enzyme kinetics Reaction product measurement 857 PK50 Analysis of multiple subject profiles Two-compartment plasma data 862 PK51 Multi-compartment drug/metabolite 865 PK52 Impact of disease on r-hsod kinetics 873 PK53 Kinetics of a large molecule 883 Pharmacodynamic applications 888 PD1 Receptor binding models. Part I - One-and two-site models 888 Part II Specific and non-specific binding PD2 One and two-site receptor binding 895 PD3 Inhibitory / m model 902 PD4 Turnover model I - Bolus dosing 917 PD5 Turnover model 2 Iv infusions 933 PD6 Turnover model 3 Turnover versus link modeling 941 PD7 Turnover model 4 - Iv infusions 954 PD8 Turnover models 2 and PD9 Turnover model 1 - Repeated dosing I 970 PD10 Turnover models 1 and 4 - Iv infusions 980 JPDJJ Sigmoidal models 989_

9 PK/PD Data Analysis: Concepts and Applications PD12 PD13 PD14 PD15 PD16 PD17 PD 18 PD19 PD20 PD21 PD22 PD23 PD24 PD25 PD26 PD27 PD28 PD29 PD30 PD31 PD32 PD33 PD34 PD35 PD36 PD37 PD38 PD39 PD40 PD41 PD42 Tolerance I - Single iv dosing Tolerance II - Repeated if infusions Feedback modeling - Cortisol/ACTH Oscillating response Turnover model Irreversible action Composite model I 7 mi Composite model II - E mix I I ma Enantiomer interaction Effect compartment I Iv bolus Effect compartment II Oral dosing Effect compartment III Iv infusion Logistic regression I - Single stimulus Logistic regression II - Multiple stimulii Dose-response-time analysis I Dose-response-time analysis II - Irreversible response Dose-response-time analysis III Dose-response-time analysis IV Synergy via hyperbolic functions Incomplete response data Consecutive escalating infusions Safety data Scaling PD and PK data - Efficacy Turnover of anti-psychotic response Agonist/antagonist interaction model Transduction modeling Turnover of asymmetric baseline Multiple binding site model Turnover model 1 - Repeated dosing II Turnover model of synergistic effects Operational model of agonism Receptor on/off rate model Pool model of antilipolytic effect References Symbols and Definitions Index ,