Bayesian Precision Medicine
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Bayesian Precision Medicine
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Author : Peter F. Thall
language : en
Publisher: CRC Press
Release Date : 2024-05-07
Bayesian Precision Medicine written by Peter F. Thall and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-07 with Mathematics categories.
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer. Features: Describes the connection between causal analysis and statistical inference Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applications Presents adaptive methods for clustering similar patient subgroups to improve efficiency Describes Bayesian nonparametric regression analyses of real-world datasets from oncology Provides pointers to software for implementation Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.
Bayesian Adaptive Designs For Innovative Clinical Trials And Precision Medicine
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Author : Yuan Ji
language : en
Publisher:
Release Date : 2018
Bayesian Adaptive Designs For Innovative Clinical Trials And Precision Medicine written by Yuan Ji and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.
Statistical Remedies For Medical Researchers
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Author : Peter F. Thall
language : en
Publisher: Springer Nature
Release Date : 2020-03-12
Statistical Remedies For Medical Researchers written by Peter F. Thall and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-12 with Medical categories.
This book illustrates numerous statistical practices that are commonly used by medical researchers, but which have severe flaws that may not be obvious. For each example, it provides one or more alternative statistical methods that avoid misleading or incorrect inferences being made. The technical level is kept to a minimum to make the book accessible to non-statisticians. At the same time, since many of the examples describe methods used routinely by medical statisticians with formal statistical training, the book appeals to a broad readership in the medical research community.
Artificial Intelligence For Drug Development Precision Medicine And Healthcare
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Author : Mark Chang
language : en
Publisher: CRC Press
Release Date : 2020-05-07
Artificial Intelligence For Drug Development Precision Medicine And Healthcare written by Mark Chang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-07 with Business & Economics categories.
Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.
Bayesian Approach For Analyzing Concurrent Response Rates Data In Clinical Trials
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Author : Yilun Sun
language : en
Publisher:
Release Date : 2023
Bayesian Approach For Analyzing Concurrent Response Rates Data In Clinical Trials written by Yilun Sun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Precision medicine has emerged as a promising approach to advancing global healthcare. However, the traditional clinical trial paradigm requires novel adaptations to adjust to challenges posed by advances in precision medicine. To address this issue, master protocol designs, such as basket trials, have been created to improve flexibility and efficiency in clinical trials. These novel designs often involve multiple disease subgroups and frequently suffer from a limited number of participants. To overcome this challenge, it is necessary to borrow information across patient subgroups to estimate response rates within subgroups in clinical trials. Bayesian methods are among the most commonly recommended approaches for facilitating borrowing strategies. However, existing Bayesian methods often ignore variation in subgroup sizes and the heterogeneity between subgroups caused by multiple factors. In this dissertation, we propose a Bayesian procedure for analyzing concurrent response rates data. Our approach clusters subgroups based on outcomes, conducts flexible information borrowing based on subgroup similarities, accounts for multiple factors, and filters out the contribution of subgroups with small sizes.
Adaptive Treatment Strategies In Practice Planning Trials And Analyzing Data For Personalized Medicine
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Author : Michael R. Kosorok
language : en
Publisher: SIAM
Release Date : 2015-12-08
Adaptive Treatment Strategies In Practice Planning Trials And Analyzing Data For Personalized Medicine written by Michael R. Kosorok and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-08 with Medical categories.
Personalized medicine is a medical paradigm that emphasizes systematic use of individual patient information to optimize that patient's health care, particularly in managing chronic conditions and treating cancer. In the statistical literature, sequential decision making is known as an adaptive treatment strategy (ATS) or a dynamic treatment regime (DTR). The field of DTRs emerges at the interface of statistics, machine learning, and biomedical science to provide a data-driven framework for precision medicine. The authors provide a learning-by-seeing approach to the development of ATSs, aimed at a broad audience of health researchers. All estimation procedures used are described in sufficient heuristic and technical detail so that less quantitative readers can understand the broad principles underlying the approaches. At the same time, more quantitative readers can implement these practices. This book provides the most up-to-date summary of the current state of the statistical research in personalized medicine; contains chapters by leaders in the area from both the statistics and computer sciences fields; and also contains a range of practical advice, introductory and expository materials, and case studies.
Modern Approaches To Clinical Trials Using Sas
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Author : Sandeep Menon
language : en
Publisher: SAS Institute
Release Date : 2015-12-09
Modern Approaches To Clinical Trials Using Sas written by Sandeep Menon and has been published by SAS Institute this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-09 with Computers categories.
Get the tools you need to use SAS® in clinical trial design! Unique and multifaceted, Modern Approaches to Clinical Trials Using SAS: Classical, Adaptive, and Bayesian Methods, edited by Sandeep M. Menon and Richard C. Zink, thoroughly covers several domains of modern clinical trial design: classical, group sequential, adaptive, and Bayesian methods that are applicable to and widely used in various phases of pharmaceutical development. Written for biostatisticians, pharmacometricians, clinical developers, and statistical programmers involved in the design, analysis, and interpretation of clinical trials, as well as students in graduate and postgraduate programs in statistics or biostatistics, the book touches on a wide variety of topics, including dose-response and dose-escalation designs; sequential methods to stop trials early for overwhelming efficacy, safety, or futility; Bayesian designs that incorporate historical data; adaptive sample size re-estimation; adaptive randomization to allocate subjects to more effective treatments; and population enrichment designs. Methods are illustrated using clinical trials from diverse therapeutic areas, including dermatology, endocrinology, infectious disease, neurology, oncology, and rheumatology. Individual chapters are authored by renowned contributors, experts, and key opinion leaders from the pharmaceutical/medical device industry or academia. Numerous real-world examples and sample SAS code enable users to readily apply novel clinical trial design and analysis methodologies in practice.
Machine Learning Advanced Dynamic Omics Data Analysis For Precision Medicine
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Author : Tao Zeng
language : en
Publisher: Frontiers Media SA
Release Date : 2020-03-30
Machine Learning Advanced Dynamic Omics Data Analysis For Precision Medicine written by Tao Zeng and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-30 with categories.
Statistical Approaches In Oncology Clinical Development
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Author : Satrajit Roychoudhury
language : en
Publisher: CRC Press
Release Date : 2018-12-07
Statistical Approaches In Oncology Clinical Development written by Satrajit Roychoudhury and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Mathematics categories.
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.
Personalized Medicine In The Making
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Author : Chiara Beneduce
language : en
Publisher: Springer Nature
Release Date : 2022-03-07
Personalized Medicine In The Making written by Chiara Beneduce and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-07 with Medical categories.
This book offers a multidisciplinary look at the much-debated concept of “personalized medicine”. By combining a humanistic and a scientific approach, the book builds up a multidimensional way to understand the limits and potentialities of a personalized approach in medicine and healthcare. The book reflects on personalized medicine and complex diseases, the relationship between personalized medicine and the new bio-technologies, personalized medicine and personalized nutrition, and on some ethical, political, economic, and social implications of personalized medicine. This volume is of interest to researchers from several disciplines including philosophy, bio-medicine, and the social sciences. Chapter 16, “The Impact of Fantasy” is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.