Chang Monte Carlo Simulation for the Pharmaceutical Industry

Concepts, Algorithms, and Case Studies
1. Auflage 2010
ISBN: 978-1-4398-3593-7
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 564 Seiten

Reihe: Chapman & Hall/CRC Biostatistics Series

Helping you become a creative, logical thinker and skillful "simulator," Monte Carlo Simulation for the Pharmaceutical Industry: Concepts, Algorithms, and Case Studies provides broad coverage of the entire drug development process, from drug discovery to preclinical and clinical trial aspects to commercialization. It presents the theories and methods needed to carry out computer simulations efficiently, covers both descriptive and pseudocode algorithms that provide the basis for implementation of the simulation methods, and illustrates real-world problems through case studies.

The text first emphasizes the importance of analogy and simulation using examples from a variety of areas, before introducing general sampling methods and the different stages of drug development. It then focuses on simulation approaches based on game theory and the Markov decision process, simulations in classical and adaptive trials, and various challenges in clinical trial management and execution. The author goes on to cover prescription drug marketing strategies and brand planning, molecular design and simulation, computational systems biology and biological pathway simulation with Petri nets, and physiologically based pharmacokinetic modeling and pharmacodynamic models. The final chapter explores Monte Carlo computing techniques for statistical inference.

This book offers a systematic treatment of computer simulation in drug development. It not only deals with the principles and methods of Monte Carlo simulation, but also the applications in drug development, such as statistical trial monitoring, prescription drug marketing, and molecular docking.

Zielgruppe

Statisticians and practitioners in the pharmaceutical and healthcare industries, biostatisticians, informaticians, specialists in pharmacokinetics and pharmacodynamics, computer/software engineers and programmers, clinical trial project managers, and prescription drug planners.

Autoren/Hrsg.

Chang, Mark

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Numerische Mathematik

Inhaltsverzeichnis

Simulation, Simulation Everywhere
Modeling and Simulation
Introductory Monte Carlo Examples
Simulations in Drug Development

Virtual Sampling Techniques
Uniform Random Number Generation
General Sampling Methods
Efficiency Improvement in Virtual Sampling
Sampling Algorithms for Specific Distributions

Overview of Drug Development
Introduction
Drug Discovery
Preclinical Development
Clinical Development

Meta-Simulation for Pharmaceutical Industry
Introduction
Game Theory Basics
Pharmaceutical Games
Prescription Drug Global Pricing

Macro-Simulation for Pharmaceutical R & D
Sequential Decision-Making
Markov Decision Process
Pharmaceutical Decision Process
Extension of Markov Decision Process

Clinical Trial Simulation (CTS)
Classical Trial Simulation
Adaptive Trial Simulation

Clinical Trial Management and Execution
Introduction
Clinical Trial Management
Patient Recruitment and Projection
Randomization
Dynamic and Adaptive Drug Supply
Statistical Trial Monitoring

Prescription Drug Commercialization
Dynamics of Prescription Drug Marketing
Stock-Flow Dynamic Model for Brand Planning
Competitive Drug Marketing Strategy
Compulsory Licensing and Parallel Importation

Molecular Design and Simulation
Why Molecular Design and Simulation
Molecular Similarity Search
Overview of Molecular Docking
Small Molecule Confirmation Analysis
Ligand-Receptor Interaction
Docking Algorithms
Scoring Functions

Disease Modeling and Biological Pathway Simulation
Computational System Biology
Petri Nets
Biological Pathway Simulation

Pharmacokinetic Simulation
Overview of ADME
Absorption Modeling
Distribution
Metabolism Modeling
Excretion Modeling
Physiologically Based PK Model
Pharmacodynamic Simulation
Way to Pharmacodynamics
Enzyme Kinetics
Pharmacodynamic Models
Drug-Drug Interaction
Application of Pharmacodynamic Modeling
Monte Carlo for Inference and Beyond
Sorting Algorithm
Resampling Methods
Genetic Programming
Appendix A: JavaScript Programs
Appendix B: K-Stage Adaptive Design Stopping Boundaries
Afterword
Bibliography
A Summary and Exercises appear at the end of each chapter.

Über Autor(innen)

Mark Chang is the executive director of biostatistics and data management at AMAG Pharmaceuticals in Lexington, Massachusetts. Dr. Chang is an elected fellow of the American Statistical Association. He is the author of the best-selling Adaptive Design Theory and Implementation Using SAS and R and co-author of the best-selling Adaptive Design Methods in Clinical Trials.