| Description |
1 online resource |
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text txt rdacontent |
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computer c rdamedia |
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online resource cr rdacarrier |
| Series |
Computer aided chemical engineering ; volume 42 |
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Computer-aided chemical engineering ; v. 42.
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| Note |
Includes index. |
| Contents |
Front Cover; Quantitative Systems Pharmacology: Models and Model-Based Systems with Applications; Copyright; Contents; Contributors; Preface; Acknowledgments; Section 1: Introduction to quantitative systems pharmacology; Chapter 1: Quantitative systems pharmacology: Extending the envelope through systems engineering; 1. Introduction; 2. The emergence of QSP modeling; 2.1. Multiscale modeling: Beyond the drug target; 2.2. Modeling the disease state; 3. Modeling drug exposure and drug response at the systemic level; 4. Modeling biological and drug interactions at the molecular level |
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4.1. Omics data4.2. Genomics; 4.3. Transcriptomics; 4.4. Proteomics; 4.5. Metabolomics; 4.6. Omics network using pathway enrichment; 4.7. Case study: Pathway enrichment for synthetic MPL; 5. Summary of the model development process; 6. QSP in context; 6.1. Case study: Cortisol regulation in the context of environmental clues: Next challenges; 7. How systems engineering can enable QSP; 8. Final comments; Acknowledgments; References; Section 2: Modeling and applications of systemic pharmacokinetics and pharmacodynamics |
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Chapter 2: An engineering oriented approach to physiologically based pharmacokinetic and pharmacodynamic modeling1. Introduction; 2. Classic compartmental pharmacokinetic models; 3. Physiologically based pharmacokinetic models; 3.1. Individualization of the pharmacokinetic prediction; 3.2. Model identification; 3.2.1. The rationale of model-assisted experiments; 3.2.2. Linearization method; 3.2.3. Monte Carlo method; 3.2.4. Bootstrap method; 3.2.5. A posteriori identifiability; 4. Introduction to pharmacodynamics; 5. Mathematical formulation of a PBPK model; 5.1. The PBPK model |
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5.1.1. Model parameters5.1.2. PK simulation; 6. Mathematical formulation of PD models; 6.1. Direct effect model: Hill equation; 6.2. Indirect response models; 6.3. Irreversible effect models; 7. Conclusions; References; Chapter 3: Advanced Techniques for the Optimal Design of Experiments in Pharmacokinetics; 1. Introduction; 2. Identifying a physiological model: The need for experimental design; 3. Design of experiments under constraints for physiological models; 3.1. Design procedure; 3.2. Design of experimental protocols under uncertainty; 4. Case study I: Identification of a PK-PD model |
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5. Case study II: Design of more effective clinical tests for the study of VWD6. Conclusions; References; Chapter 4: On the Identifiability of Physiological Models: Optimal Design of Clinical Tests; 1. Introduction; 2. The concept of identifiability; 3. Identifiability tests; 3.1. A priori tests for parametric identifiability; 3.2. A posteriori tests for parametric identifiability; 3.3. Practical identifiability of parametric models; 4. Identifiability in the development of compartmental models; 5. Optimal design of clinical tests for guaranteed identifiability |
| Note |
Online resource; title from digital title page (viewed on September 04, 2018). |
| Subject |
Pharmacology.
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Systems engineering.
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Pharmacology |
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Pharmacologie.
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Ingénierie des systèmes.
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pharmacology.
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systems engineering.
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MEDICAL -- Pharmacology.
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Pharmacology
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Systems engineering
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| Added Author |
Manca, Davide, editor.
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| Other Form: |
Print version: Quantitative systems pharmacology. Amsterdam, The Netherlands : Elsevier, [2018] 9780444639646 0444639640 (OCoLC)1002834850 |
| ISBN |
9780444639677 (electronic book) |
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0444639675 (electronic book) |
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9780444639646 (print) |
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0444639640 |
| Standard No. |
AU@ 000063796298 |
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GBVCP 1028101864 |
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UKMGB 018988946 |
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