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Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis

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The item Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
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Creator

Macheras, P., (Panos)

Contributor

Iliadis, Athanassios

Language: eng

Work

Publication

New York, Springer, ©2006

Extent: xx, 442 pages

Contents

8
51
II
Modeling in Biopharmaceutics
53
4
Drug Release
57
4.1
The Higuchi Model
58
1.3
4.2
Systems with Different Geometries
60
4.3
The Power-Law Model
63
4.3.1
Higuchi Model vs. Power-Law Model
64
4.4
Fractal Dimension
Recent Mechanistic Models
67
4.5
Monte Carlo Simulations
68
4.5.1
Verification of the Higuchi Law
69
4.5.2
Drug Release from Homogeneous Cylinders
9
70
4.5.3
Release from Fractal Matrices
75
4.6
Discernment of Drug Release Kinetics
82
4.7
Release from Bioerodible Microparticles
83
1.4
4.8
Dynamic Aspects in Drug Release
86
5
Drug Dissolution
89
5.1
The Diffusion Layer Model
90
5.1.1
Estimation of Fractal Dimension
Alternative Classical Dissolution Relationships
92
5.1.2
Fractal Considerations in Drug Dissolution
93
5.1.3
On the Use of the Weibull Function in Dissolution
94
5.1.4
Stochastic Considerations
11
97
5.2
The Interfacial Barrier Model
100
5.2.1
A Continuous Reaction-Limited Dissolution Model
100
5.2.2
A Discrete Reaction-Limited Dissolution Model
101
1.4.1
5.2.3
Modeling Supersaturated Dissolution Data
107
5.3
Modeling Random Effects
109
5.4
Homogeneity vs. Heterogeneity
110
5.5
Self-Similarity Considerations
Comparison of Dissolution Profiles
111
6
Oral Drug Absorption
113
6.1
Pseudoequilibrium Models
114
6.1.1
The pH-Partition Hypothesis
11
114
6.1.2
Absorption Potential
115
6.2
Mass Balance Approaches
117
6.2.1
Macroscopic Approach
118
1
1.4.2
6.2.2
Microscopic Approach
121
6.3
Dynamic Models
122
6.3.1
Compartmental Models
122
6.3.2
Power-Law Scaling
Convection-Dispersion Models
124
6.4
Heterogeneous Approaches
129
6.4.1
The Heterogeneous Character of GI Transit
129
6.4.2
Is in Vivo Drug Dissolution a Fractal Process?
12
130
6.4.3
Fractal-like Kinetics in Gastrointestinal Absorption
132
6.4.4
The Fractal Nature of Absorption Processes
134
6.4.5
Modeling Drug Transit in the Intestines
136
1.5
6.4.6
Probabilistic Model for Drug Absorption
142
6.5
Absorption Models Based on Structure
147
6.6
Regulatory Aspects
148
6.6.1
Self-Affine Fractals
Biopharmaceutics Classification of Drugs
148
6.6.2
The Problem with the Biowaivers
151
6.7
Randomness and Chaotic Behavior
158
III
Modeling In Pharmacokinetics
12
161
7
Empirical Models
165
7.1
Power Functions and Heterogeneity
167
7.2
Heterogeneous Processes
169
1.6
7.2.1
Distribution, Blood Vessels Network
169
7.2.2
Elimination, Liver Structure
171
7.3
Fractal Time and Fractal Processes
174
7.4
More About Dimensionality
Modeling Heterogeneity
175
7.4.1
Fractal Concepts
176
7.4.2
Empirical Concepts
177
7.5
Heterogeneity and Time Dependence
13
178
7.6
Simulation with Empirical Models
181
8
Deterministic Compartmental Models
183
8.1
Linear Compartmental Models
184
1.7
8.2
Routes of Administration
186
8.3
Time-Concentration Profiles
187
8.4
Random Fractional Flow Rates
188
8.5
The Geometry of Nature
Percolation
Nonlinear Compartmental Models
189
8.5.1
The Enzymatic Reaction
191
8.6
Complex Deterministic Models
193
8.6.1
Geometric Considerations
14
194
8.6.2
Tracer Washout Curve
195
8.6.3
Model for the Circulatory System
197
8.7
Compartmental Models and Heterogeneity
199
2
9
Stochastic Compartmental Models
205
9.1
Probabilistic Transfer Models
206
9.1.2
The Basic Steps
208
9.2
Diffusion and Kinetics
Retention-Time Distribution Models
210
9.2.1
Probabilistic vs. Retention-Time Models
210
9.2.2
Markov vs. Semi-Markov Models
212
9.2.3
Irreversible Models
17
214
9.2.4
Reversible Models
217
9.2.5
Time-Varying Hazard Rates
222
9.2.6
Pseudocompartment Techniques
225
2.1
9.2.7
A Typical Two-Compartment Model
231
9.3
Time-Concentration Profiles
235
9.3.1
Routes of Administration
236
9.3.2
Random Walks and Regular Diffusion
Some Typical Drug Administration Schemes
237
9.3.3
Time-Amount Functions
239
9.3.4
Process Uncertainty or Stochastic Error
243
9.3.5
Distribution of Particles and Process Uncertainty
18
245
9.3.6
Time Profiles of the Model
249
9.4
Random Hazard-Rate Models
251
9.4.1
Probabilistic Models with Random Hazard Rates
253
2.2
9.4.2
Retention-Time Models with Random Hazard Rates
258
9.5
The Kolmogorov or Master Equations
260
9.5.1
Master Equation and Diffusion
263
9.5.2
Anomalous Diffusion
Exact Solution in Matrix Form
265
9.5.3
Cumulant Generating Functions
265
9.5.4
Stochastic Simulation Algorithm
267
9.5.5
Simulation of Linear and Nonlinear Models
5
22
272
9.6
Fractals and Stochastic Modeling
281
9.7
Stochastic vs. Deterministic Models
285
IV
Modeling in Pharmacodynamics
289
2.3
10
Classical Pharmacodynamics
293
10.1
Occupancy Theory in Pharmacology
293
10.2
Empirical Pharmacodynamic Models
295
10.3
Fick's Laws of Diffusion
Pharmacokinetic-Dynamic Modeling
296
10.3.1
Link Models
297
10.3.2
Response Models
303
10.4
Other Pharmacodynamic Models
23
305
10.4.1
The Receptor-Transducer Model
305
10.4.2
Irreversible Models
305
10.4.3
Time-Variant Models
306
2.4
10.4.4
Dynamic Nonlinear Models
308
10.5
Unification of Pharmacodynamic Models
309
10.6
The Population Approach
310
10.6.1
Classical Kinetics
Inter- and Intraindividual Variability
310
10.6.2
Models and Software
311
10.6.3
Covariates
312
10.6.4
Applications
27
313
11
Nonclassical Pharmacodynamics
315
11.1
Nonlinear Concepts in Pharmacodynamics
316
11.1.1
Negative Feedback
316
2.4.1
11.1.2
Delayed Negative Feedback
322
11.2
Pharmacodynamic Applications
334
11.2.1
Drugs Affecting Endocrine Function
334
11.2.2
Passive Transport Processes
Central Nervous System Drugs
344
11.2.3
Cardiovascular Drugs
348
A Stability Analysis
353
B
Monte Carlo Simulations in Drug Release
355
28
C
Time-Varying Models
359
D
Probability
363
D.1
Basic Properties
363
D.2
1.1
2.4.2
Expectation, Variance, and Covariance
364
D.3
Conditional Expectation and Variance
365
D.4
Generating Functions
365
E
Convolution in Probability Theory
Reaction Processes: Diffusion- or Reaction-Limited?
367
F
Laplace Transform
369
G
Estimation
371
H
Theorem on Continuous Functions
373
29
2.4.3
Carrier-Mediated Transport
30
2.5
Fractal-like Kinetics
31
2.5.1
Geometric and Statistical Self-Similarity
Segregation of Reactants
31
2.5.2
Time-Dependent Rate Coefficients
32
2.5.3
Effective Rate Equations
34
2.5.4
Enzyme-Catalyzed Reactions
6
35
2.5.5
Importance of the Power-Law Expressions
36
2.6
Fractional Diffusion Equations
36
3
Nonlinear Dynamics
39
1.2
3.1
Dynamic Systems
41
3.2
Attractors
42
3.3
Bifurcation
43
3.4
Scaling
Sensitivity to Initial Conditions
45
3.5
Reconstruction of the Phase Space
47
3.6
Estimation and Control in Chaotic Systems
49
3.7
Physiological Systems

Isbn: 9780387281780

Instance

Label: Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches

Title: Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics

Title remainder: homogeneous and heterogeneous approaches

Statement of responsibility: Panos Macheras, Athanassios Iliadis

Creator

Macheras, P., (Panos)

Contributor

Iliadis, Athanassios

Subject

Language: eng

Member of

Interdisciplinary applied mathematics, v. 30

Cataloging source: MMU

http://library.link/vocab/creatorName: Macheras, P.

Dewey number: 615/.7

Illustrations: illustrations

Index: index present

LC call number: RM301.5

LC item number: .M33 2006

Literary form: non fiction

Nature of contents: bibliography

NLM call number

2006 C-872
QV 38

NLM item number: M149m 2006

http://library.link/vocab/relatedWorkOrContributorName: Iliadis, Athanassios

Series statement: Interdisciplinary applied mathematics

Series volume: v. 30

http://library.link/vocab/subjectName

Biopharmaceutics
Pharmacokinetics
Drugs
Biopharmaceutics
Models, Theoretical
Pharmacokinetics
Biopharmacie
Pharmacocinétique
Médicaments
Biopharmacie
Pharmacocinétique
Pharmacodynamie
Biomathematik
Biopharmazie
Pharmakodynamik
Pharmakokinetik
Pharmacodynamie - Modèles mathématiques

Label: Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis

Instantiates

Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches

Publication

New York, Springer, ©2006

Bibliography note: Includes bibliographical references (pages 383-432) and index

Carrier category: volume

Carrier category code

Carrier MARC source: rdacarrier

Content category: text

Content type code

Content type MARC source: rdacontent

Contents

8
51
II
Modeling in Biopharmaceutics
53
4
Drug Release
57
4.1
The Higuchi Model
58
1.3
4.2
Systems with Different Geometries
60
4.3
The Power-Law Model
63
4.3.1
Higuchi Model vs. Power-Law Model
64
4.4
Fractal Dimension
Recent Mechanistic Models
67
4.5
Monte Carlo Simulations
68
4.5.1
Verification of the Higuchi Law
69
4.5.2
Drug Release from Homogeneous Cylinders
9
70
4.5.3
Release from Fractal Matrices
75
4.6
Discernment of Drug Release Kinetics
82
4.7
Release from Bioerodible Microparticles
83
1.4
4.8
Dynamic Aspects in Drug Release
86
5
Drug Dissolution
89
5.1
The Diffusion Layer Model
90
5.1.1
Estimation of Fractal Dimension
Alternative Classical Dissolution Relationships
92
5.1.2
Fractal Considerations in Drug Dissolution
93
5.1.3
On the Use of the Weibull Function in Dissolution
94
5.1.4
Stochastic Considerations
11
97
5.2
The Interfacial Barrier Model
100
5.2.1
A Continuous Reaction-Limited Dissolution Model
100
5.2.2
A Discrete Reaction-Limited Dissolution Model
101
1.4.1
5.2.3
Modeling Supersaturated Dissolution Data
107
5.3
Modeling Random Effects
109
5.4
Homogeneity vs. Heterogeneity
110
5.5
Self-Similarity Considerations
Comparison of Dissolution Profiles
111
6
Oral Drug Absorption
113
6.1
Pseudoequilibrium Models
114
6.1.1
The pH-Partition Hypothesis
11
114
6.1.2
Absorption Potential
115
6.2
Mass Balance Approaches
117
6.2.1
Macroscopic Approach
118
1
1.4.2
6.2.2
Microscopic Approach
121
6.3
Dynamic Models
122
6.3.1
Compartmental Models
122
6.3.2
Power-Law Scaling
Convection-Dispersion Models
124
6.4
Heterogeneous Approaches
129
6.4.1
The Heterogeneous Character of GI Transit
129
6.4.2
Is in Vivo Drug Dissolution a Fractal Process?
12
130
6.4.3
Fractal-like Kinetics in Gastrointestinal Absorption
132
6.4.4
The Fractal Nature of Absorption Processes
134
6.4.5
Modeling Drug Transit in the Intestines
136
1.5
6.4.6
Probabilistic Model for Drug Absorption
142
6.5
Absorption Models Based on Structure
147
6.6
Regulatory Aspects
148
6.6.1
Self-Affine Fractals
Biopharmaceutics Classification of Drugs
148
6.6.2
The Problem with the Biowaivers
151
6.7
Randomness and Chaotic Behavior
158
III
Modeling In Pharmacokinetics
12
161
7
Empirical Models
165
7.1
Power Functions and Heterogeneity
167
7.2
Heterogeneous Processes
169
1.6
7.2.1
Distribution, Blood Vessels Network
169
7.2.2
Elimination, Liver Structure
171
7.3
Fractal Time and Fractal Processes
174
7.4
More About Dimensionality
Modeling Heterogeneity
175
7.4.1
Fractal Concepts
176
7.4.2
Empirical Concepts
177
7.5
Heterogeneity and Time Dependence
13
178
7.6
Simulation with Empirical Models
181
8
Deterministic Compartmental Models
183
8.1
Linear Compartmental Models
184
1.7
8.2
Routes of Administration
186
8.3
Time-Concentration Profiles
187
8.4
Random Fractional Flow Rates
188
8.5
The Geometry of Nature
Percolation
Nonlinear Compartmental Models
189
8.5.1
The Enzymatic Reaction
191
8.6
Complex Deterministic Models
193
8.6.1
Geometric Considerations
14
194
8.6.2
Tracer Washout Curve
195
8.6.3
Model for the Circulatory System
197
8.7
Compartmental Models and Heterogeneity
199
2
9
Stochastic Compartmental Models
205
9.1
Probabilistic Transfer Models
206
9.1.2
The Basic Steps
208
9.2
Diffusion and Kinetics
Retention-Time Distribution Models
210
9.2.1
Probabilistic vs. Retention-Time Models
210
9.2.2
Markov vs. Semi-Markov Models
212
9.2.3
Irreversible Models
17
214
9.2.4
Reversible Models
217
9.2.5
Time-Varying Hazard Rates
222
9.2.6
Pseudocompartment Techniques
225
2.1
9.2.7
A Typical Two-Compartment Model
231
9.3
Time-Concentration Profiles
235
9.3.1
Routes of Administration
236
9.3.2
Random Walks and Regular Diffusion
Some Typical Drug Administration Schemes
237
9.3.3
Time-Amount Functions
239
9.3.4
Process Uncertainty or Stochastic Error
243
9.3.5
Distribution of Particles and Process Uncertainty
18
245
9.3.6
Time Profiles of the Model
249
9.4
Random Hazard-Rate Models
251
9.4.1
Probabilistic Models with Random Hazard Rates
253
2.2
9.4.2
Retention-Time Models with Random Hazard Rates
258
9.5
The Kolmogorov or Master Equations
260
9.5.1
Master Equation and Diffusion
263
9.5.2
Anomalous Diffusion
Exact Solution in Matrix Form
265
9.5.3
Cumulant Generating Functions
265
9.5.4
Stochastic Simulation Algorithm
267
9.5.5
Simulation of Linear and Nonlinear Models
5
22
272
9.6
Fractals and Stochastic Modeling
281
9.7
Stochastic vs. Deterministic Models
285
IV
Modeling in Pharmacodynamics
289
2.3
10
Classical Pharmacodynamics
293
10.1
Occupancy Theory in Pharmacology
293
10.2
Empirical Pharmacodynamic Models
295
10.3
Fick's Laws of Diffusion
Pharmacokinetic-Dynamic Modeling
296
10.3.1
Link Models
297
10.3.2
Response Models
303
10.4
Other Pharmacodynamic Models
23
305
10.4.1
The Receptor-Transducer Model
305
10.4.2
Irreversible Models
305
10.4.3
Time-Variant Models
306
2.4
10.4.4
Dynamic Nonlinear Models
308
10.5
Unification of Pharmacodynamic Models
309
10.6
The Population Approach
310
10.6.1
Classical Kinetics
Inter- and Intraindividual Variability
310
10.6.2
Models and Software
311
10.6.3
Covariates
312
10.6.4
Applications
27
313
11
Nonclassical Pharmacodynamics
315
11.1
Nonlinear Concepts in Pharmacodynamics
316
11.1.1
Negative Feedback
316
2.4.1
11.1.2
Delayed Negative Feedback
322
11.2
Pharmacodynamic Applications
334
11.2.1
Drugs Affecting Endocrine Function
334
11.2.2
Passive Transport Processes
Central Nervous System Drugs
344
11.2.3
Cardiovascular Drugs
348
A Stability Analysis
353
B
Monte Carlo Simulations in Drug Release
355
28
C
Time-Varying Models
359
D
Probability
363
D.1
Basic Properties
363
D.2
1.1
2.4.2
Expectation, Variance, and Covariance
364
D.3
Conditional Expectation and Variance
365
D.4
Generating Functions
365
E
Convolution in Probability Theory
Reaction Processes: Diffusion- or Reaction-Limited?
367
F
Laplace Transform
369
G
Estimation
371
H
Theorem on Continuous Functions
373
29
2.4.3
Carrier-Mediated Transport
30
2.5
Fractal-like Kinetics
31
2.5.1
Geometric and Statistical Self-Similarity
Segregation of Reactants
31
2.5.2
Time-Dependent Rate Coefficients
32
2.5.3
Effective Rate Equations
34
2.5.4
Enzyme-Catalyzed Reactions
6
35
2.5.5
Importance of the Power-Law Expressions
36
2.6
Fractional Diffusion Equations
36
3
Nonlinear Dynamics
39
1.2
3.1
Dynamic Systems
41
3.2
Attractors
42
3.3
Bifurcation
43
3.4
Scaling
Sensitivity to Initial Conditions
45
3.5
Reconstruction of the Phase Space
47
3.6
Estimation and Control in Chaotic Systems
49
3.7
Physiological Systems

Control code: 63188951

Dimensions: 25 cm

Extent: xx, 442 pages

Isbn: 9780387281780

Lccn: 2005934524

Media category: unmediated

Media MARC source: rdamedia

Media type code

Other control number: 9780387281780

Other physical details: illustrations

System control number: (OCoLC)63188951

Label: Modeling in biopharmaceutics, pharmacokinetics, and pharmacodynamics : homogeneous and heterogeneous approaches, Panos Macheras, Athanassios Iliadis

Publication

Bibliography note: Includes bibliographical references (pages 383-432) and index

Carrier category: volume

Carrier category code

Carrier MARC source: rdacarrier

Content category: text

Content type code

Content type MARC source: rdacontent

Contents

8
51
II
Modeling in Biopharmaceutics
53
4
Drug Release
57
4.1
The Higuchi Model
58
1.3
4.2
Systems with Different Geometries
60
4.3
The Power-Law Model
63
4.3.1
Higuchi Model vs. Power-Law Model
64
4.4
Fractal Dimension
Recent Mechanistic Models
67
4.5
Monte Carlo Simulations
68
4.5.1
Verification of the Higuchi Law
69
4.5.2
Drug Release from Homogeneous Cylinders
9
70
4.5.3
Release from Fractal Matrices
75
4.6
Discernment of Drug Release Kinetics
82
4.7
Release from Bioerodible Microparticles
83
1.4
4.8
Dynamic Aspects in Drug Release
86
5
Drug Dissolution
89
5.1
The Diffusion Layer Model
90
5.1.1
Estimation of Fractal Dimension
Alternative Classical Dissolution Relationships
92
5.1.2
Fractal Considerations in Drug Dissolution
93
5.1.3
On the Use of the Weibull Function in Dissolution
94
5.1.4
Stochastic Considerations
11
97
5.2
The Interfacial Barrier Model
100
5.2.1
A Continuous Reaction-Limited Dissolution Model
100
5.2.2
A Discrete Reaction-Limited Dissolution Model
101
1.4.1
5.2.3
Modeling Supersaturated Dissolution Data
107
5.3
Modeling Random Effects
109
5.4
Homogeneity vs. Heterogeneity
110
5.5
Self-Similarity Considerations
Comparison of Dissolution Profiles
111
6
Oral Drug Absorption
113
6.1
Pseudoequilibrium Models
114
6.1.1
The pH-Partition Hypothesis
11
114
6.1.2
Absorption Potential
115
6.2
Mass Balance Approaches
117
6.2.1
Macroscopic Approach
118
1
1.4.2
6.2.2
Microscopic Approach
121
6.3
Dynamic Models
122
6.3.1
Compartmental Models
122
6.3.2
Power-Law Scaling
Convection-Dispersion Models
124
6.4
Heterogeneous Approaches
129
6.4.1
The Heterogeneous Character of GI Transit
129
6.4.2
Is in Vivo Drug Dissolution a Fractal Process?
12
130
6.4.3
Fractal-like Kinetics in Gastrointestinal Absorption
132
6.4.4
The Fractal Nature of Absorption Processes
134
6.4.5
Modeling Drug Transit in the Intestines
136
1.5
6.4.6
Probabilistic Model for Drug Absorption
142
6.5
Absorption Models Based on Structure
147
6.6
Regulatory Aspects
148
6.6.1
Self-Affine Fractals
Biopharmaceutics Classification of Drugs
148
6.6.2
The Problem with the Biowaivers
151
6.7
Randomness and Chaotic Behavior
158
III
Modeling In Pharmacokinetics
12
161
7
Empirical Models
165
7.1
Power Functions and Heterogeneity
167
7.2
Heterogeneous Processes
169
1.6
7.2.1
Distribution, Blood Vessels Network
169
7.2.2
Elimination, Liver Structure
171
7.3
Fractal Time and Fractal Processes
174
7.4
More About Dimensionality
Modeling Heterogeneity
175
7.4.1
Fractal Concepts
176
7.4.2
Empirical Concepts
177
7.5
Heterogeneity and Time Dependence
13
178
7.6
Simulation with Empirical Models
181
8
Deterministic Compartmental Models
183
8.1
Linear Compartmental Models
184
1.7
8.2
Routes of Administration
186
8.3
Time-Concentration Profiles
187
8.4
Random Fractional Flow Rates
188
8.5
The Geometry of Nature
Percolation
Nonlinear Compartmental Models
189
8.5.1
The Enzymatic Reaction
191
8.6
Complex Deterministic Models
193
8.6.1
Geometric Considerations
14
194
8.6.2
Tracer Washout Curve
195
8.6.3
Model for the Circulatory System
197
8.7
Compartmental Models and Heterogeneity
199
2
9
Stochastic Compartmental Models
205
9.1
Probabilistic Transfer Models
206
9.1.2
The Basic Steps
208
9.2
Diffusion and Kinetics
Retention-Time Distribution Models
210
9.2.1
Probabilistic vs. Retention-Time Models
210
9.2.2
Markov vs. Semi-Markov Models
212
9.2.3
Irreversible Models
17
214
9.2.4
Reversible Models
217
9.2.5
Time-Varying Hazard Rates
222
9.2.6
Pseudocompartment Techniques
225
2.1
9.2.7
A Typical Two-Compartment Model
231
9.3
Time-Concentration Profiles
235
9.3.1
Routes of Administration
236
9.3.2
Random Walks and Regular Diffusion
Some Typical Drug Administration Schemes
237
9.3.3
Time-Amount Functions
239
9.3.4
Process Uncertainty or Stochastic Error
243
9.3.5
Distribution of Particles and Process Uncertainty
18
245
9.3.6
Time Profiles of the Model
249
9.4
Random Hazard-Rate Models
251
9.4.1
Probabilistic Models with Random Hazard Rates
253
2.2
9.4.2
Retention-Time Models with Random Hazard Rates
258
9.5
The Kolmogorov or Master Equations
260
9.5.1
Master Equation and Diffusion
263
9.5.2
Anomalous Diffusion
Exact Solution in Matrix Form
265
9.5.3
Cumulant Generating Functions
265
9.5.4
Stochastic Simulation Algorithm
267
9.5.5
Simulation of Linear and Nonlinear Models
5
22
272
9.6
Fractals and Stochastic Modeling
281
9.7
Stochastic vs. Deterministic Models
285
IV
Modeling in Pharmacodynamics
289
2.3
10
Classical Pharmacodynamics
293
10.1
Occupancy Theory in Pharmacology
293
10.2
Empirical Pharmacodynamic Models
295
10.3
Fick's Laws of Diffusion
Pharmacokinetic-Dynamic Modeling
296
10.3.1
Link Models
297
10.3.2
Response Models
303
10.4
Other Pharmacodynamic Models
23
305
10.4.1
The Receptor-Transducer Model
305
10.4.2
Irreversible Models
305
10.4.3
Time-Variant Models
306
2.4
10.4.4
Dynamic Nonlinear Models
308
10.5
Unification of Pharmacodynamic Models
309
10.6
The Population Approach
310
10.6.1
Classical Kinetics
Inter- and Intraindividual Variability
310
10.6.2
Models and Software
311
10.6.3
Covariates
312
10.6.4
Applications
27
313
11
Nonclassical Pharmacodynamics
315
11.1
Nonlinear Concepts in Pharmacodynamics
316
11.1.1
Negative Feedback
316
2.4.1
11.1.2
Delayed Negative Feedback
322
11.2
Pharmacodynamic Applications
334
11.2.1
Drugs Affecting Endocrine Function
334
11.2.2
Passive Transport Processes
Central Nervous System Drugs
344
11.2.3
Cardiovascular Drugs
348
A Stability Analysis
353
B
Monte Carlo Simulations in Drug Release
355
28
C
Time-Varying Models
359
D
Probability
363
D.1
Basic Properties
363
D.2
1.1
2.4.2
Expectation, Variance, and Covariance
364
D.3
Conditional Expectation and Variance
365
D.4
Generating Functions
365
E
Convolution in Probability Theory
Reaction Processes: Diffusion- or Reaction-Limited?
367
F
Laplace Transform
369
G
Estimation
371
H
Theorem on Continuous Functions
373
29
2.4.3
Carrier-Mediated Transport
30
2.5
Fractal-like Kinetics
31
2.5.1
Geometric and Statistical Self-Similarity
Segregation of Reactants
31
2.5.2
Time-Dependent Rate Coefficients
32
2.5.3
Effective Rate Equations
34
2.5.4
Enzyme-Catalyzed Reactions
6
35
2.5.5
Importance of the Power-Law Expressions
36
2.6
Fractional Diffusion Equations
36
3
Nonlinear Dynamics
39
1.2
3.1
Dynamic Systems
41
3.2
Attractors
42
3.3
Bifurcation
43
3.4
Scaling
Sensitivity to Initial Conditions
45
3.5
Reconstruction of the Phase Space
47
3.6
Estimation and Control in Chaotic Systems
49
3.7
Physiological Systems

Control code: 63188951

Dimensions: 25 cm

Extent: xx, 442 pages

Isbn: 9780387281780

Lccn: 2005934524

Media category: unmediated

Media MARC source: rdamedia

Media type code

Other control number: 9780387281780

Other physical details: illustrations

System control number: (OCoLC)63188951

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