Pharmacometrics: The Science of Quantitative Pharmacology / Edition 1by Ene I. Ette, Paul J. Williams
Pub. Date: 02/16/2007
Pharmacometrics is the science of interpreting and describing pharmacology in a quantitative fashion. The pharmaceutical industry is integrating pharmacometrics into its drug development program, but there is a lack of and need for experienced pharmacometricians since fewer and fewer academic programs exist to train them. Pharmacometrics: The Science of
Pharmacometrics is the science of interpreting and describing pharmacology in a quantitative fashion. The pharmaceutical industry is integrating pharmacometrics into its drug development program, but there is a lack of and need for experienced pharmacometricians since fewer and fewer academic programs exist to train them. Pharmacometrics: The Science of Quantitative Pharmacology lays out the science of pharmacometrics and its application to drug development, evaluation, and patient pharmacotherapy, providing a comprehensive set of tools for the training and development of pharmacometricians.
Edited and written by key leaders in the field, this flagship text on pharmacometrics:
- Integrates theory and practice to let the reader apply principles and concepts.
- Provides a comprehensive set of tools for training and developing expertise in the pharmacometric field.
- Is unique in including computer code information with the examples.
This volume is an invaluable resource for all pharmacometricians, statisticians, teachers, graduate and undergraduate students in academia, industry, and regulatory agencies.
- Publication date:
- Product dimensions:
- 7.34(w) x 10.04(h) x 2.74(d)
Table of Contents
Chapter 1. Pharmacometrics: Impacting Drug Development and Pharmacotherpay.
I: GENERAL PRINCIPLES.
Chapter 2. General Principles of Programming (Computer and Statistical).
Chapter 3. Validation of Software for Pharmacometric Analyses.
Chapter 4. Linear, Generalized Linear, and Nonlinear Mixed-Effects Models.
Chapter 5. Bayesian Hierarchical Modeling with Markov Chain Monte Carlo Methods.
Chapter 6. Estimating the Dynamics of Drug Regimen Compliance.
Chapter 7. Graphical Display for Modeling Population Data.
Chapter 8. The Epistemology of Pharmacometrics.
Chapter 9. Data Imputation.
II: POPULATION PHARMACOKINETIC BASIS OF PHARMACOMETRICS.
Chapter 10. Population Pharmacokinetic Estimation Methods.
Chapter 11. Timing and Efficiency in Population Pharmacokinetic / Pharmacodynamic Data Analysis.
Chapter 12. Designing Population Pharmacokinetic Studies for Efficient Parameter Estimation.
Chapter 13. Population Models for Drug Absorption and Entero-hepatic Recycling.
Chapter 14. Pharmacometric Knowledge Discovery from Clinical trial Data Sets.
Chapter 15. Resampling Techniques and Their Application to Pharmacometrics.
Chapter 16. The Population Approach to Bioequivalence.
III: PHARMACOKINETICS / PHARMACODYNAMICS RELATIONSHIP BIOMARKERS AND PHARMACOGENOMICS.
Chapter 17. Biomarkers in Drug Development and Pharmacometric Modeling.
Chapter 18. Analysis of Gene Expression Data.
Chapter 19. Pharmacogenomics and Pharmacokinetic/Pharmacodynamic Modeling.
Chapter 20. Empirical Pharmacokinetic/Pharmacodynamic Models.
Chapter 21. Developing Models of Disease Progression.
Chapter 22. Mechanistic Pharmacokinetic/Pharmacodynamic (PK/PD) Models.
Chapter 23. Mechanistic Pharmacokinetic/Pharmacodynamic Models II.
Chapter 24. PK/PD Analysis of Binary (Logistic) Outcome Data.
Chapter 25. Population Pharmacokinetic / Pharmacodynamic Modeling of Ordered Categorical Longitudinal Data.
Chapter 26. Transition Models in Pharmacodynamics.
Chapter 27. Mixed Effects Modeling of Count Data.
Chapter 28. Mixture Modeling with NONMEM.
IV. CLINICAL TRIAL DESIGNS.
Chapter 29. Designs for First Time-in-Man Studies in Non-Oncology Indications.
Chapter 30. Design for Phase I Studies in Oncology.
Chapter 31. Design and Analysis of Clinical Exposure - Response Trials.
V. PHARMACOMETRIC KNOWLEDGE CREATION.
Chapter 32. Pharmacometric Knowledge Creation: Towards Characterizing an Unexplored Region of the Response Surface.
Chapter 33. Clinical Trial Simulation: Theory.
Chapter 34. Modeling and Simulation: Planning and Execution.
Chapter 35. Clinical Trial Simulation: Efficacy Trials.
VI: PHARMACOMETRIC SERVICE AND COMMUNICATION.
Chapter 36. Engineering a Pharmacometrics Enterprise.
Chapter 37. Communication of Pharmacometric Analysis Outcome.
VII: SPECIFIC APPLICATIONS EXAMPLES.
Chapter 38. Pharmacometrics Applications in Population Exposure-Response Data for New Drug Development and Evaluation.
Chapter 39. Pharmacometrics in Pharmacotherapy and Drug Development: Pediatric Application.
Chapter 40. Pharmacometric Methods for Assessing Drug-Induced QT and QTc Prolongations for Non-Antiarrhythmic Drugs.
Chapter 41. Using Pharmacometrics in the Development of Biologic Therapeutic Agents.
Chapter 42. Analysis of Quantic Pharmacokinetic Study: Robust Estimation of Tissue-to-Plasma Ratio.
Chapter 43. Physiologically Based Pharmacokinetic Modeling: Inhalation, Ingestion and Dermal Absorption.
Chapter 44. Modeling of Metablite Pharmacokinetics in a Large Pharmacokinetic Data Set: An Application.
Chapter 45. Characterizing Nonlinear Pharmacokinetics: An Example Scenario for a Therapeutic Protein.
Chapter 46. Development, Evaluation and Applications of In Vitro/ In Vivo Correlations: A Regulatory Perspective.
Chapter 47. The Confluence of Pharmacometric Knowledge Discovery and Creation in the Characterization of Drug Safety.
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An excellent book who wants to learn quantitative pharmacology. it is a book to keep for a lifetime.