Analysis Of Biomarker Data
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Analysis Of Biomarker Data
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Author : Stephen W. Looney
language : en
Publisher: John Wiley & Sons
Release Date : 2015-01-23
Analysis Of Biomarker Data written by Stephen W. Looney and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-01-23 with Medical categories.
A “how to” guide for applying statistical methods to biomarker data analysis Presenting a solid foundation for the statistical methods that are used to analyze biomarker data, Analysis of Biomarker Data: A Practical Guide features preferred techniques for biomarker validation. The authors provide descriptions of select elementary statistical methods that are traditionally used to analyze biomarker data with a focus on the proper application of each method, including necessary assumptions, software recommendations, and proper interpretation of computer output. In addition, the book discusses frequently encountered challenges in analyzing biomarker data and how to deal with them, methods for the quality assessment of biomarkers, and biomarker study designs. Covering a broad range of statistical methods that have been used to analyze biomarker data in published research studies, Analysis of Biomarker Data: A Practical Guide also features: A greater emphasis on the application of methods as opposed to the underlying statistical and mathematical theory The use of SAS®, R, and other software throughout to illustrate the presented calculations for each example Numerous exercises based on real-world data as well as solutions to the problems to aid in reader comprehension The principles of good research study design and the methods for assessing the quality of a newly proposed biomarker A companion website that includes a software appendix with multiple types of software and complete data sets from the book’s examples Analysis of Biomarker Data: A Practical Guide is an ideal upper-undergraduate and graduate-level textbook for courses in the biological or environmental sciences. An excellent reference for statisticians who routinely analyze and interpret biomarker data, the book is also useful for researchers who wish to perform their own analyses of biomarker data, such as toxicologists, pharmacologists, epidemiologists, environmental and clinical laboratory scientists, and other professionals in the health and environmental sciences.
Biomarker Analysis In Clinical Trials With R
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Author : Nusrat Rabbee
language : en
Publisher: CRC Press
Release Date : 2020-03-11
Biomarker Analysis In Clinical Trials With R written by Nusrat Rabbee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-11 with Mathematics categories.
The world is awash in data. This volume of data will continue to increase. In the pharmaceutical industry, much of this data explosion has happened around biomarker data. Great statisticians are needed to derive understanding from these data. This book will guide you as you begin the journey into communicating, understanding and synthesizing biomarker data. -From the Foreword, Jared Christensen, Vice President, Biostatistics Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the pharmaceutical industry on how to incorporate biomarker data analysis in clinical trial studies. The book discusses the appropriate statistical methods for evaluating pharmacodynamic, predictive and surrogate biomarkers for delivering increased value in the drug development process. The topic of combining multiple biomarkers to predict drug response using machine learning is covered. Featuring copious reproducible code and examples in R, the book helps students, researchers and biostatisticians get started in tackling the hard problems of designing and analyzing trials with biomarkers. Features: Analysis of pharmacodynamic biomarkers for lending evidence target modulation. Design and analysis of trials with a predictive biomarker. Framework for analyzing surrogate biomarkers. Methods for combining multiple biomarkers to predict treatment response. Offers a biomarker statistical analysis plan. R code, data and models are given for each part: including regression models for survival and longitudinal data, as well as statistical learning models, such as graphical models and penalized regression models.
Bioinformatics And Biomarker Discovery
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Author : Francisco Azuaje
language : en
Publisher: John Wiley & Sons
Release Date : 2011-08-24
Bioinformatics And Biomarker Discovery written by Francisco Azuaje and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-08-24 with Science categories.
This book is designed to introduce biologists, clinicians and computational researchers to fundamental data analysis principles, techniques and tools for supporting the discovery of biomarkers and the implementation of diagnostic/prognostic systems. The focus of the book is on how fundamental statistical and data mining approaches can support biomarker discovery and evaluation, emphasising applications based on different types of "omic" data. The book also discusses design factors, requirements and techniques for disease screening, diagnostic and prognostic applications. Readers are provided with the knowledge needed to assess the requirements, computational approaches and outputs in disease biomarker research. Commentaries from guest experts are also included, containing detailed discussions of methodologies and applications based on specific types of "omic" data, as well as their integration. Covers the main range of data sources currently used for biomarker discovery Covers the main range of data sources currently used for biomarker discovery Puts emphasis on concepts, design principles and methodologies that can be extended or tailored to more specific applications Offers principles and methods for assessing the bioinformatic/biostatistic limitations, strengths and challenges in biomarker discovery studies Discusses systems biology approaches and applications Includes expert chapter commentaries to further discuss relevance of techniques, summarize biological/clinical implications and provide alternative interpretations
Statistical Methods In Biomarker And Early Clinical Development
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Author : Liang Fang
language : en
Publisher: Springer Nature
Release Date : 2019-12-26
Statistical Methods In Biomarker And Early Clinical Development written by Liang Fang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-12-26 with Medical categories.
This contributed volume offers a much-needed overview of the statistical methods in early clinical drug and biomarker development. Chapters are written by expert statisticians with extensive experience in the pharmaceutical industry and regulatory agencies. Because of this, the data presented is often accompanied by real world case studies, which will help make examples more tangible for readers. The many applications of statistics in drug development are covered in detail, making this volume a must-have reference. Biomarker development and early clinical development are the two critical areas on which the book focuses. By having the two sections of the book dedicated to each of these topics, readers will have a more complete understanding of how applying statistical methods to early drug development can help identify the right drug for the right patient at the right dose. Also presented are exciting applications of machine learning and statistical modeling, along with innovative methods and state-of-the-art advances, making this a timely and practical resource. This volume is ideal for statisticians, researchers, and professionals interested in pharmaceutical research and development. Readers should be familiar with the fundamentals of statistics and clinical trials.
Proteomic And Metabolomic Approaches To Biomarker Discovery
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Author : Haleem J. Issaq
language : en
Publisher: Academic Press
Release Date : 2019-10-24
Proteomic And Metabolomic Approaches To Biomarker Discovery written by Haleem J. Issaq and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-24 with Science categories.
Proteomic and Metabolomic Approaches to Biomarker Discovery, Second Edition covers techniques from both proteomics and metabolomics and includes all steps involved in biomarker discovery, from study design to study execution. The book describes methods and presents a standard operating procedure for sample selection, preparation and storage, as well as data analysis and modeling. This new standard effectively eliminates the differing methodologies used in studies and creates a unified approach. Readers will learn the advantages and disadvantages of the various techniques discussed, as well as potential difficulties inherent to all steps in the biomarker discovery process. This second edition has been fully updated and revised to address recent advances in MS and NMR instrumentation, high-field NMR, proteomics and metabolomics for biomarker validation, clinical assays of biomarkers and clinical MS and NMR, identifying microRNAs and autoantibodies as biomarkers, MRM-MS assay development, top-down MS, glycosylation-based serum biomarkers, cell surface proteins in biomarker discovery, lipodomics for cancer biomarker discovery, and strategies to design studies to identify predictive biomarkers in cancer research. - Addresses the full range of proteomic and metabolomic methods and technologies used for biomarker discovery and validation - Covers all steps involved in biomarker discovery, from study design to study execution - Serves as a vital resource for biochemists, biologists, analytical chemists, bioanalytical chemists, clinical and medical technicians, researchers in pharmaceuticals and graduate students
The Detection Of Biomarkers
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Author : Sibel A. Ozkan
language : en
Publisher: Academic Press
Release Date : 2021-12-05
The Detection Of Biomarkers written by Sibel A. Ozkan and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-05 with Medical categories.
Reliable, precise and accurate detection and analysis of biomarkers remains a significant challenge for clinical researchers. Methods for the detection of biomarkers are rather complex, requiring pre-treatment steps before analysis can take place. Moreover, comparing various biomarker assays and tracing research progress in this area systematically is a challenge for researchers. The Detection of Biomarkers presents developments in biomarker detection, including methods tools and strategies, biosensor design, materials, and applications. The book presents methods, materials and procedures that are simple, precise, sensitive, selective, fast and economical, and therefore highly practical for use in clinical research scenarios. This volume situates biomarker detection in its research context and sets out future prospects for the area. Its 20 chapters offer a comprehensive coverage of biomarkers, including progress on nanotechnology, biosensor types, synthesis, immobilization, and applications in various fields. The book also demonstrates, for students, how to synthesize and immobilize biosensors for biomarker assay. It offers researchers real alternative and innovative ways to think about the field of biomarker detection, increasing the reliability, precision and accuracy of biomarker detection. - Locates biomarker detection in its research context, setting out present and future prospects - Allows clinical researchers to compare various biomarker assays systematically - Presents new methods, materials and procedures that are simple, precise, sensitive, selective, fast and economical - Gives innovative biomarker assays that are viable alternatives to current complex methods - Helps clinical researchers who need reliable, precise and accurate biomarker detection methods
Metabolic Profiling Its Role In Biomarker Discovery And Gene Function Analysis
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Author : George G. Harrigan
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Metabolic Profiling Its Role In Biomarker Discovery And Gene Function Analysis written by George G. Harrigan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Science categories.
It is evident that biochemical control is not strictly hierarchical and that intermediary metabolism can contribute to control of regulatory pathways. Metabolic studies are therefore increasingly important in gene function analyses, and an increased interest in metabolites as biomarkers for disease progression or response to therapeutic intervention is also evident in the pharmaceutical industry. This book offers guidelines to currently available technology and bioinformatics and database strategies now being developed. Evidence is presented that metabolic profiling is a valuable addition to genomics and proteomics strategies devoted to drug discovery and development, and that metabolic profiling offers numerous advantages.
Evaluation Of Biomarkers And Surrogate Endpoints In Chronic Disease
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Author : Institute of Medicine
language : en
Publisher: National Academies Press
Release Date : 2010-07-25
Evaluation Of Biomarkers And Surrogate Endpoints In Chronic Disease written by Institute of Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-07-25 with Medical categories.
Many people naturally assume that the claims made for foods and nutritional supplements have the same degree of scientific grounding as those for medication, but that is not always the case. The IOM recommends that the FDA adopt a consistent scientific framework for biomarker evaluation in order to achieve a rigorous and transparent process.
Biomarkers In Drug Development
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Author : Michael R. Bleavins
language : en
Publisher: John Wiley & Sons
Release Date : 2011-09-20
Biomarkers In Drug Development written by Michael R. Bleavins and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-20 with Medical categories.
Discover how biomarkers can boost the success rate of drug development efforts As pharmaceutical companies struggle to improve the success rate and cost-effectiveness of the drug development process, biomarkers have emerged as a valuable tool. This book synthesizes and reviews the latest efforts to identify, develop, and integrate biomarkers as a key strategy in translational medicine and the drug development process. Filled with case studies, the book demonstrates how biomarkers can improve drug development timelines, lower costs, facilitate better compound selection, reduce late-stage attrition, and open the door to personalized medicine. Biomarkers in Drug Development is divided into eight parts: Part One offers an overview of biomarkers and their role in drug development. Part Two highlights important technologies to help researchers identify new biomarkers. Part Three examines the characterization and validation process for both drugs and diagnostics, and provides practical advice on appropriate statistical methods to ensure that biomarkers fulfill their intended purpose. Parts Four through Six examine the application of biomarkers in discovery, preclinical safety assessment, clinical trials, and translational medicine. Part Seven focuses on lessons learned and the practical aspects of implementing biomarkers in drug development programs. Part Eight explores future trends and issues, including data integration, personalized medicine, and ethical concerns. Each of the thirty-eight chapters was contributed by one or more leading experts, including scientists from biotechnology and pharmaceutical firms, academia, and the U.S. Food and Drug Administration. Their contributions offer pharmaceutical and clinical researchers the most up-to-date understanding of the strategies used for and applications of biomarkers in drug development.
Biomarker Analysis In Clinical Trials With R
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Author : Nusrat Rabbee
language : en
Publisher: CRC Press
Release Date : 2020-03-11
Biomarker Analysis In Clinical Trials With R written by Nusrat Rabbee and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-11 with Mathematics categories.
The world is awash in data. This volume of data will continue to increase. In the pharmaceutical industry, much of this data explosion has happened around biomarker data. Great statisticians are needed to derive understanding from these data. This book will guide you as you begin the journey into communicating, understanding and synthesizing biomarker data. -From the Foreword, Jared Christensen, Vice President, Biostatistics Early Clinical Development, Pfizer, Inc. Biomarker Analysis in Clinical Trials with R offers practical guidance to statisticians in the pharmaceutical industry on how to incorporate biomarker data analysis in clinical trial studies. The book discusses the appropriate statistical methods for evaluating pharmacodynamic, predictive and surrogate biomarkers for delivering increased value in the drug development process. The topic of combining multiple biomarkers to predict drug response using machine learning is covered. Featuring copious reproducible code and examples in R, the book helps students, researchers and biostatisticians get started in tackling the hard problems of designing and analyzing trials with biomarkers. Features: Analysis of pharmacodynamic biomarkers for lending evidence target modulation. Design and analysis of trials with a predictive biomarker. Framework for analyzing surrogate biomarkers. Methods for combining multiple biomarkers to predict treatment response. Offers a biomarker statistical analysis plan. R code, data and models are given for each part: including regression models for survival and longitudinal data, as well as statistical learning models, such as graphical models and penalized regression models.