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Author: Valerii V. Fedorov
Publisher: CRC Press
ISBN: 1439821518
Category : Mathematics
Languages : en
Pages : 404
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Book Description
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors’ many years of experience in academia and the pharmaceutical industry. 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. The common goals of experimental design—such as reducing costs, supporting efficient decision making, and gaining maximum information under various constraints—are often the same across diverse applied areas. Ethical and regulatory aspects play a much more prominent role in biological, medical, and pharmaceutical research. The authors address all of these issues through many examples in the book.
Author: Valerii V. Fedorov
Publisher: CRC Press
ISBN: 1439821518
Category : Mathematics
Languages : en
Pages : 404
Get Book Here
Book Description
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors’ many years of experience in academia and the pharmaceutical industry. 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. The common goals of experimental design—such as reducing costs, supporting efficient decision making, and gaining maximum information under various constraints—are often the same across diverse applied areas. Ethical and regulatory aspects play a much more prominent role in biological, medical, and pharmaceutical research. The authors address all of these issues through many examples in the book.
Author: Valerii V. Fedorov
Publisher: CRC Press
ISBN: 1439821526
Category : Mathematics
Languages : en
Pages : 398
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Book Description
Optimal Design for Nonlinear Response Models discusses the theory and applications of model-based experimental design with a strong emphasis on biopharmaceutical studies. The book draws on the authors' many years of experience in academia and the pharmaceutical industry. While the focus is on nonlinear models, the book begins with an explanation of
Author: Peter Goos
Publisher: John Wiley & Sons
ISBN: 1119976162
Category : Science
Languages : en
Pages : 249
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Book Description
"This is an engaging and informative book on the modern practice of experimental design. The authors' writing style is entertaining, the consulting dialogs are extremely enjoyable, and the technical material is presented brilliantly but not overwhelmingly. The book is a joy to read. Everyone who practices or teaches DOE should read this book." - Douglas C. Montgomery, Regents Professor, Department of Industrial Engineering, Arizona State University "It's been said: 'Design for the experiment, don't experiment for the design.' This book ably demonstrates this notion by showing how tailor-made, optimal designs can be effectively employed to meet a client's actual needs. It should be required reading for anyone interested in using the design of experiments in industrial settings." —Christopher J. Nachtsheim, Frank A Donaldson Chair in Operations Management, Carlson School of Management, University of Minnesota This book demonstrates the utility of the computer-aided optimal design approach using real industrial examples. These examples address questions such as the following: How can I do screening inexpensively if I have dozens of factors to investigate? What can I do if I have day-to-day variability and I can only perform 3 runs a day? How can I do RSM cost effectively if I have categorical factors? How can I design and analyze experiments when there is a factor that can only be changed a few times over the study? How can I include both ingredients in a mixture and processing factors in the same study? How can I design an experiment if there are many factor combinations that are impossible to run? How can I make sure that a time trend due to warming up of equipment does not affect the conclusions from a study? How can I take into account batch information in when designing experiments involving multiple batches? How can I add runs to a botched experiment to resolve ambiguities? While answering these questions the book also shows how to evaluate and compare designs. This allows researchers to make sensible trade-offs between the cost of experimentation and the amount of information they obtain.
Author: Friedrich Pukelsheim
Publisher: SIAM
ISBN: 0898716047
Category : Mathematics
Languages : en
Pages : 527
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Book Description
Optimal Design of Experiments offers a rare blend of linear algebra, convex analysis, and statistics. The optimal design for statistical experiments is first formulated as a concave matrix optimization problem. Using tools from convex analysis, the problem is solved generally for a wide class of optimality criteria such as D-, A-, or E-optimality. The book then offers a complementary approach that calls for the study of the symmetry properties of the design problem, exploiting such notions as matrix majorization and the Kiefer matrix ordering. The results are illustrated with optimal designs for polynomial fit models, Bayes designs, balanced incomplete block designs, exchangeable designs on the cube, rotatable designs on the sphere, and many other examples.
Author: John O'Quigley
Publisher: CRC Press
ISBN: 1351648020
Category : Mathematics
Languages : en
Pages : 390
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Book Description
Handbook of Methods for Designing, Monitoring, and Analyzing Dose-Finding Trials gives a thorough presentation of state-of-the-art methods for early phase clinical trials. The methodology of clinical trials has advanced greatly over the last 20 years and, arguably, nowhere greater than that of early phase studies. The need to accelerate drug development in a rapidly evolving context of targeted therapies, immunotherapy, combination treatments and complex group structures has provided the stimulus to these advances. Typically, we deal with very small samples, sequential methods that need to be efficient, while, at the same time adhering to ethical principles due to the involvement of human subjects. Statistical inference is difficult since the standard techniques of maximum likelihood do not usually apply as a result of model misspecification and parameter estimates lying on the boundary of the parameter space. Bayesian methods play an important part in overcoming these difficulties, but nonetheless, require special consideration in this particular context. The purpose of this handbook is to provide an expanded summary of the field as it stands and also, through discussion, provide insights into the thinking of leaders in the field as to the potential developments of the years ahead. With this goal in mind we present: An introduction to the field for graduate students and novices A basis for more established researchers from which to build A collection of material for an advanced course in early phase clinical trials A comprehensive guide to available methodology for practicing statisticians on the design and analysis of dose-finding experiments An extensive guide for the multiple comparison and modeling (MCP-Mod) dose-finding approach, adaptive two-stage designs for dose finding, as well as dose–time–response models and multiple testing in the context of confirmatory dose-finding studies. John O’Quigley is a professor of mathematics and research director at the French National Institute for Health and Medical Research based at the Faculty of Mathematics, University Pierre and Marie Curie in Paris, France. He is author of Proportional Hazards Regression and has published extensively in the field of dose finding. Alexia Iasonos is an associate attending biostatistician at the Memorial Sloan Kettering Cancer Center in New York. She has over one hundred publications in the leading statistical and clinical journals on the methodology and design of early phase clinical trials. Dr. Iasonos has wide experience in the actual implementation of model based early phase trials and has given courses in scientific meetings internationally. Björn Bornkamp is a statistical methodologist at Novartis in Basel, Switzerland, researching and implementing dose-finding designs in Phase II clinical trials. He is one of the co-developers of the MCP-Mod methodology for dose finding and main author of the DoseFinding R package. He has published numerous papers on dose finding, nonlinear models and Bayesian statistics, and in 2013 won the Royal Statistical Society award for statistical excellence in the pharmaceutical industry.
Author: Jürgen Franke
Publisher: Springer Nature
ISBN: 3031662539
Category :
Languages : en
Pages : 393
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Book Description
Author: Alex Dmitrienko
Publisher: SAS Institute
ISBN: 1599943573
Category : Computers
Languages : en
Pages : 464
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Book Description
Introduces a range of data analysis problems encountered in drug development and illustrates them using case studies from actual pre-clinical experiments and clinical studies. Includes a discussion of methodological issues, practical advice from subject matter experts, and review of relevant regulatory guidelines.
Author: L.W. Ratner
Publisher: Elsevier
ISBN: 008053760X
Category : Science
Languages : en
Pages : 281
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Book Description
In order to select an optimal structure among possible similar structures, one needs to compare the elastic behavior of the structures. A new criterion that describes elastic behavior is the rate of change of deformation. Using this criterion, the safe dimensions of a structure that are required by the stress distributed in a structure can be calculated. The new non-linear theory of elasticity allows one to determine the actual individual limit of elasticity/failure of a structure using a simple non-destructive method of measurement of deformation on the model of a structure while presently it can be done only with a destructive test for each structure. For building and explaining the theory, a new logical structure was introduced as the basis of the theory. One of the important physical implications of this logic is that it describes mathematically the universal domain of the possible stable physical relations.
Author: Joachim Kunert
Publisher: Springer
ISBN: 3319312669
Category : Mathematics
Languages : en
Pages : 256
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Book Description
This volume contains pioneering contributions to both the theory and practice of optimal experimental design. Topics include the optimality of designs in linear and nonlinear models, as well as designs for correlated observations and for sequential experimentation. There is an emphasis on applications to medicine, in particular, to the design of clinical trials. Scientists from Europe, the US, Asia, Australia and Africa contributed to this volume of papers from the 11th Workshop on Model Oriented Design and Analysis.
Author: Oleksandr Sverdlov
Publisher: CRC Press
ISBN: 1000799239
Category : Mathematics
Languages : en
Pages : 462
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Book Description
One of the hallmarks of the 21st century medicine is the emergence of digital therapeutics (DTx)—evidence-based, clinically validated digital technologies to prevent, diagnose, treat, and manage various diseases and medical conditions. DTx solutions have been gaining interest from patients, investors, healthcare providers, health authorities, and other stakeholders because of the potential of DTx to deliver equitable, massively scalable, personalized and transformative treatments for different unmet medical needs. Digital Therapeutics: Scientific, Statistical, Clinical, and Regulatory Aspects is an unparalleled summary of the current scientific, statistical, developmental, and regulatory aspects of DTx which is poised to become the fastest growing area of the biopharmaceutical and digital medicine product development. This edited volume intends to provide a systematic exposition to digital therapeutics through 19 peer-reviewed chapters written by subject matter experts in this emerging field. This edited volume is an invaluable resource for business leaders and researchers working in public health, healthcare, digital health, information technology, and biopharmaceutical industries. It will be also useful for regulatory scientists involved in the review of DTx products, and for faculty and students involved in an interdisciplinary research on digital health and digital medicine. Key Features: Provides the taxonomy of the concepts and a navigation tool for the field of DTx. Covers important strategic aspects of the DTx industry, thereby helping investors, developers, and regulators gain a better appreciation of the potential value of DTx. Expounds on many existing and emerging state-of-the art scientific and technological tools, as well as data privacy, ethical and regulatory considerations for DTx product development. Presents several case studies of successful development of some of the most remarkable DTx products. Provides some perspectives and forward-looking statements on the future of digital medicine.
