Of the thousands of biomarkers that are currently being discovered, relatively few are being validated for further applications, and the potential of a biomarker can be quite difficult to evaluate. To aid in this imperative research, Dr. Kewal K. Jain’s Handbook of Biomarkers thoroughly describes many different types of biomarkers and their discovery using various "-omics" technologies, such as proteomics and metabolomics, along with the background information needed for the evaluation of biomarkers as well as the essential procedures for their validation and use in clinical trials. With biomarkers described first according to technologies and then according to various diseases, this detailed book features the key correlations between diseases and classifications of biomarkers, which provides the reader with a guide to sort out current and future biomarkers. Comprehensive and cutting-edge, The Handbook of Biomarkers serves as a vital guide to furthering our understanding of biomarkers, which, by facilitating the combination of therapeutics with diagnostics, promise to play an important role in the development of personalized medicine, one of the most important emerging trends in healthcare today.

In this book, expert researchers provide a tool box for those who have a general interest in biomarker research and for those currently specializing in certain technologies but desiring an understanding of other available methodologies. Its chapters include validated, mature methods as well as new, incredibly promising protocols. This book is the perfect biomarker technical guideline and reference to stimulate more exciting biomarker research and technology development.

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.

This book covers proteomics biomarker discovery and validation procedures from the clinical perspective.

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.

This book provides an introduction to the field of biomarkers, how they have been and can be used, and how different approaches can be used to identify, characterize, and monitor biomarkers. The book has chapters on topics including HIV, Cancer, Parkinson’s, vascular injury, environmental exposure. A following section discusses the technologies (diagnostics and assays) to detect biomarkers and authors have emphasized the preclinical and clinical manifestation of the injury/disease process.

This handbook covers established and advanced techniques for biomarker analysis, such as guidelines and strategies for assay validation methods; different mathematical models that are necessary in contemporary drug discovery and development; and evaluation of new cytometry methods. Expertly curated by two practicing professionals in drug development and biotherapeutics, individual chapters are selected for novel and sound research; information is chosen based on its relevance to lab applications and clinical trials, such as the topic of selecting animal models for their relevancy to humans. The book is multifaceted, discussing the ethics and issues with biospecimens and providing an in-depth analysis to the differences between pre-clinical and clinical assay development. The book is an essential read for general readers who need an introduction to the history and background of biomarkers, and it also provides critical analyses of various new validation methods for practitioners and researchers.