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Clinical and Statistical Considerations in Personalized Medicine

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Release : 2014-03-27
Genre : Mathematics
Kind : eBook
Book Rating : 873/5 ( reviews)

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Book Synopsis Clinical and Statistical Considerations in Personalized Medicine by : Claudio Carini

Download or read book Clinical and Statistical Considerations in Personalized Medicine written by Claudio Carini. This book was released on 2014-03-27. Available in PDF, EPUB and Kindle. Book excerpt: Clinical and Statistical Considerations in Personalized Medicine explores recent advances related to biomarkers and their translation into clinical development. Leading clinicians, biostatisticians, regulators, commercial professionals, and researchers address the opportunities and challenges in successfully applying biomarkers in drug discovery and preclinical and clinical development. Robust Biomarkers for Drug Development and Disease Treatment The first four chapters discuss biomarker development from a clinical perspective. Coverage ranges from an introduction to biomarkers to advances in RNAi screens, epigenetics, and rare diseases as targets for personalized medicine approaches. Subsequent chapters examine the statistical considerations in applying a personalized medicine approach, including multiplicity in pharmacogenomics. The last chapter assesses the regulatory issues involved in using biomarkers. Improve Patient Care and Reduce Costs and Side Effects Despite the vast amount of literature on biomarkers, there is no comprehensive book that integrates the clinical and statistical components. This book is one of the first to incorporate both the clinical and statistical aspects of biomarkers in the personalized medicine paradigm. Covering a wide spectrum of personalized medicine-related topics, it presents state-of-the-art techniques for advancing the application of biomarkers in drug discovery and development.

Clinical and Statistical Considerations in Personalized Medicine

Download Clinical and Statistical Considerations in Personalized Medicine PDF Online Free

Author :
Release : 2014-01-01
Genre :
Kind : eBook
Book Rating : 771/5 ( reviews)

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Book Synopsis Clinical and Statistical Considerations in Personalized Medicine by : Claudio Carini

Download or read book Clinical and Statistical Considerations in Personalized Medicine written by Claudio Carini. This book was released on 2014-01-01. Available in PDF, EPUB and Kindle. Book excerpt: The Future of Clinical Research and Health Care: From Empirical to Precision Medicine Clinical and Statistical Considerations in Personalized Medicine explores recent advances related to biomarkers and their translation into clinical development. Leading clinicians, biostatisticians, regulators, commercial professionals, and researchers address the opportunities and challenges in successfully applying biomarkers in drug discovery and preclinical and clinical development. Robust Biomarkers for Drug Development and Disease Treatment The first four chapters discuss biomarker development from a clinical perspective. Coverage ranges from an introduction to biomarkers to advances in RNAi screens, epigenetics, and rare diseases as targets for personalized medicine approaches. Subsequent chapters examine the statistical considerations in applying a personalized medicine approach, including multiplicity in pharmacogenomics. The last chapter assesses the regulatory issues involved in using biomarkers. Improve Patient Care and Reduce Costs and Side Effects Despite the vast amount of literature on biomarkers, there is no comprehensive book that integrates the clinical and statistical components. This book is one of the first to incorporate both the clinical and statistical aspects of biomarkers in the personalized medicine paradigm. Covering a wide spectrum of personalized medicine-related topics, it presents state-of-the-art techniques for advancing the application of biomarkers in drug discovery and development.

Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials

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Release : 2019-03-20
Genre : Mathematics
Kind : eBook
Book Rating : 527/5 ( reviews)

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Book Synopsis Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials by : Mark Chang

Download or read book Innovative Strategies, Statistical Solutions and Simulations for Modern Clinical Trials written by Mark Chang. This book was released on 2019-03-20. Available in PDF, EPUB and Kindle. Book excerpt: "This is truly an outstanding book. [It] brings together all of the latest research in clinical trials methodology and how it can be applied to drug development.... Chang et al provide applications to industry-supported trials. This will allow statisticians in the industry community to take these methods seriously." Jay Herson, Johns Hopkins University The pharmaceutical industry's approach to drug discovery and development has rapidly transformed in the last decade from the more traditional Research and Development (R & D) approach to a more innovative approach in which strategies are employed to compress and optimize the clinical development plan and associated timelines. However, these strategies are generally being considered on an individual trial basis and not as part of a fully integrated overall development program. Such optimization at the trial level is somewhat near-sighted and does not ensure cost, time, or development efficiency of the overall program. This book seeks to address this imbalance by establishing a statistical framework for overall/global clinical development optimization and providing tactics and techniques to support such optimization, including clinical trial simulations. Provides a statistical framework for achieve global optimization in each phase of the drug development process. Describes specific techniques to support optimization including adaptive designs, precision medicine, survival-endpoints, dose finding and multiple testing. Gives practical approaches to handling missing data in clinical trials using SAS. Looks at key controversial issues from both a clinical and statistical perspective. Presents a generous number of case studies from multiple therapeutic areas that help motivate and illustrate the statistical methods introduced in the book. Puts great emphasis on software implementation of the statistical methods with multiple examples of software code (both SAS and R). It is important for statisticians to possess a deep knowledge of the drug development process beyond statistical considerations. For these reasons, this book incorporates both statistical and "clinical/medical" perspectives.

Statistical Approaches in Oncology Clinical Development

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Release : 2018-12-07
Genre : Mathematics
Kind : eBook
Book Rating : 706/5 ( reviews)

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Book Synopsis Statistical Approaches in Oncology Clinical Development by : Satrajit Roychoudhury

Download or read book Statistical Approaches in Oncology Clinical Development written by Satrajit Roychoudhury. This book was released on 2018-12-07. Available in PDF, EPUB and Kindle. Book excerpt: Statistical Approaches in Oncology Clinical Development : Current Paradigm and Methodological Advancement presents an overview of statistical considerations in oncology clinical trials, both early and late phase of development. It illustrates how novel statistical methods can enrich the design and analysis of modern oncology trials. The authors include many relevant real life examples from the pharmaceutical industry and academia based on their first-hand experience. Along with relevant references, the book highlights current regulatory views. The book covers all aspects of cancer clinical trial starting from early phase development. The early part of the book covers novel phase I dose escalation design, exposure response analysis, and innovative phase II design. This includes early development strategy for cancer immunotherapy trials. The contributors also emphasized the role of biomarker and modern era of precision medicine. The second part focuses on the late stage development. This includes the application of adaptive design, safety analysis, and quality of life (QoL) data analysis. The final part discusses current regulatory perspective and challenges. Features: Covers a wide spectrum of topics related to real-life statistical challenges in oncology clinical trials. Provides a comprehensive overview of novel statistical methods to improve trial design and statistical analysis. Detailed case studies illustrate the real life applications. Satrajit Roychoudhury is a Senior Director and a member of the Statistical Research and Innovation group in Pfizer Inc. Prior to joining; he was a member of Statistical Methodology and consulting group in Novartis. He has 11 years of extensive experience in working with different phases of clinical trial. His area of research includes early phase oncology trials, survival analysis, model informed drug development, and use of Bayesian methods in clinical trials. He is industry co-chair for the ASA Biopharmaceutical Section Regulatory-Industry Workshop and has provided statistical training in major conferences including the Joint Statistical Meetings, ASA Biopharmaceutical Section Regulatory-Industry Workshop, and ICSA Applied Statistics Symposium. Soumi Lahiri has 12 years of extensive experience in working different therapeutic areas. She is the former Director of Biostatistics in Clinical Oncology, GlaxoSmithKline. She has also worked in the oncology division of Novartis Pharmaceutical Company for two years. She is an active member of the ASA Biopharmaceutical section and former chair of the membership committee.

Dynamic Treatment Regimes

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Release : 2019-12-19
Genre : Mathematics
Kind : eBook
Book Rating : 780/5 ( reviews)

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Book Synopsis Dynamic Treatment Regimes by : Anastasios A. Tsiatis

Download or read book Dynamic Treatment Regimes written by Anastasios A. Tsiatis. This book was released on 2019-12-19. Available in PDF, EPUB and Kindle. Book excerpt: Dynamic Treatment Regimes: Statistical Methods for Precision Medicine provides a comprehensive introduction to statistical methodology for the evaluation and discovery of dynamic treatment regimes from data. Researchers and graduate students in statistics, data science, and related quantitative disciplines with a background in probability and statistical inference and popular statistical modeling techniques will be prepared for further study of this rapidly evolving field. A dynamic treatment regime is a set of sequential decision rules, each corresponding to a key decision point in a disease or disorder process, where each rule takes as input patient information and returns the treatment option he or she should receive. Thus, a treatment regime formalizes how a clinician synthesizes patient information and selects treatments in practice. Treatment regimes are of obvious relevance to precision medicine, which involves tailoring treatment selection to patient characteristics in an evidence-based way. Of critical importance to precision medicine is estimation of an optimal treatment regime, one that, if used to select treatments for the patient population, would lead to the most beneficial outcome on average. Key methods for estimation of an optimal treatment regime from data are motivated and described in detail. A dedicated companion website presents full accounts of application of the methods using a comprehensive R package developed by the authors. The authors’ website www.dtr-book.com includes updates, corrections, new papers, and links to useful websites.

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