Monte Carlo Simulation for the Pharmaceutical Industry
Concepts, Algorithms, and Case Studies
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A complete dissertation of the theory and practice of Monte Carlo simulation in the pharmaceutical and health industry, this book describes simulation methodologies including data sampling, game theory, deterministic and stochastic decision theories, the adaptive design method, Petri nets, genetic programming, resampling methods, and computer algorithms. Teaching readers how to become visionary, creative, and skillful "simulators," the book provides broad coverage of the entire drug development process from drug discovery, through preclinical and clinical development to prescription drug comme...
A complete dissertation of the theory and practice of Monte Carlo simulation in the pharmaceutical and health industry, this book describes simulation methodologies including data sampling, game theory, deterministic and stochastic decision theories, the adaptive design method, Petri nets, genetic programming, resampling methods, and computer algorithms. Teaching readers how to become visionary, creative, and skillful "simulators," the book provides broad coverage of the entire drug development process from drug discovery, through preclinical and clinical development to prescription drug commercialization.
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