Drawing on the authors' many years of experience in academia and the pharmaceutical industry, this book discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. While the focus is on nonlinear models, the book begins with an explanation of the key ideas, using linear models as examples. Applying the linearization in the parameter space, it then covers nonlinear models and locally optimal designs as well as minimax, optimal on average, and Bayesian designs. The authors also discuss adaptive designs, focusing on procedures with non-informative stopping.
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