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Modern medicine is undergoing a paradigm shift from a "one-size-fits-all" strategy to a more precise patient-customized therapy and medication plan. While the success of precision medicine relies on the level of pharmacogenomic knowledge, dissecting the genetic mechanisms of drug response in a sufficient detail requires powerful computational tools. Quantitative Methods for Precision Medicine: Pharmacogenomics in Action presents the advanced statistical methods for mapping pharmacogenetic control by integrating pharmacokinetic and pharmacodynamic principles of drug-body interactions. Beyond traditional reductionist-based statistical genetic approaches, statistical formulization in this book synthesizes elements of multiple disciplines to infer, visualize, and track how pharmacogenes interact together as an intricate but well-coordinated system to mediate patient-specific drug response. Features: Functional and systems mapping models to characterize the genetic architecture of multiple medication processes Statistical methods for analyzing informative missing data in pharmacogenetic association studies Functional graph theory of inferring genetic interaction networks from association data Leveraging the concept of epistasis to capture its bidirectional, signed and weighted properties Modeling gene-induced cell-cell crosstalk and its impact on drug response A graph model of drug-drug interactions in combination therapies Critical methodological issues to improve pharmacogenomic research as the cornerstone of precision medicine This book is suitable for graduate students and researchers in the fields of biology, medicine, bioinformatics and drug design and delivery who are interested in statistical and computational modelling of biological processes and systems. It may also serve as a major reference for applied mathematicians, computer scientists, and statisticians who attempt to develop algorithmic tools for genetic mapping, systems pharmacogenomics and systems biology. It can be used as both a textbook and research reference. Professionals in pharmaceutical sectors who design drugs and clinical doctors who deliver drugs will also find it useful.
Precision Medicine: Tools and Quantitative Approaches discusses precision and personalized medicine, two relevant topics that are revolutionizing diagnostics and treatment, while also providing a shift toward prevention. The book covers the most relevant features and explanations underlying developments in the field. A timely review on prerequisites, causes and consequences is given. Unique to this book is a combined view on technical and data analysis aspects that is mandatory for obtaining and interpreting results. This book is a valuable source for researchers in medical and life sciences, physicians and students with an interest in this emerging field of precision medicine. - Provides technological aspects in precision medicine with aspects of modern statistical and bioinformatics models and methods - Brings timely reviews on status and chances in precision medicine and associated aspects of data analysis, statistics and data interpretation - Encompasses easy access to relevant approaches, interactions and original literature
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.
Progress and Challenges in Precision Medicine presents an insightful overview to the myriad factors of personalized and precision medicine. The availability of the human genome, large amounts of data on individual genetic variations, environmental interactions, influence of lifestyle, and cutting-edge tools and technologies for big-data analysis have led to the age of personalized and precision medicine. Bringing together a global range of experts on precision medicine, this book collects previously scattered information into one concise volume which covers the most important developments so far in precision medicine and also suggests the most likely avenues for future development. The book includes clinical information, informatics, public policy implications, and information on case studies. It is a useful reference and background work for students, researchers, and clinicians working in the biomedical and medical fields, as well as policymakers in the health sciences. - Provides an overview of the growing field of precision medicine - Contains chapters from geographically diverse experts in their field - Explores important aspects of precision medicine, including applications, ethics, and development
The author uses decades of experience and interviews with experts in precision medicine to explain past, present, and future of precision medicine. She reviews the full continuum of personalizing precision medicine, including diagnostics, therapeutics, big data, supportive care, regulation, and reimbursement and innovation in precision medicine worldwide. • Combines a unique cross section of history, current technologies, and future directions for how precision medicine has and will affect people worldwide • Reviews precision medicine around the world, including the US, China, Japan, the Middle East, India, Europe, and Latin America • Discusses a number of diseases areas – cancer, cardiovascular, neurodegenerative, infectious disease, pain, immunology, rare diseases • Includes information and quotes from over 100 interviews with key industry experts in biotech, pharma, informatics, diagnostics, health providers, advocacy groups, and more. • Includes stories illustrating current issues and future promises in precision medicine for a human touch
Motivated by the explosion of molecular data on humans-particularly data associated with individual patients-and the sense that there are large, as-yet-untapped opportunities to use this data to improve health outcomes, Toward Precision Medicine explores the feasibility and need for "a new taxonomy of human disease based on molecular biology" and develops a potential framework for creating one. The book says that a new data network that integrates emerging research on the molecular makeup of diseases with clinical data on individual patients could drive the development of a more accurate classification of diseases and ultimately enhance diagnosis and treatment. The "new taxonomy" that emerges would define diseases by their underlying molecular causes and other factors in addition to their traditional physical signs and symptoms. The book adds that the new data network could also improve biomedical research by enabling scientists to access patients' information during treatment while still protecting their rights. This would allow the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia. Toward Precision Medicine notes that moving toward individualized medicine requires that researchers and health care providers have access to very large sets of health- and disease-related data linked to individual patients. These data are also critical for developing the information commons, the knowledge network of disease, and ultimately the new taxonomy.
This book will be among the first to cover the detection methods for precision medicine that are set to transform health care in the future.
This book concisely describes the role of omics in precision medicine for cancer therapies. It outlines our current understanding of cancer genomics, shares insights into the process of oncogenesis, and discusses emerging technologies and clinical applications of cancer genomics in prognosis and precision-medicine treatment strategies. It then elaborates on recent advances concerning transcriptomics and translational genomics in cancer diagnosis, clinical applications, and personalized medicine in oncology. Importantly, it also explains the importance of high-performance analytics, predictive modeling, and system biology in cancer research. Lastly, the book discusses current and potential future applications of pharmacogenomics in clinical cancer therapy and cancer drug development.
The edition will cover proceedings of the second International conference on digital health Technologies (ICDHT 2019). The conference will address the topic of P4 medicine from the information technology point of view, and will be focused on the following topics: - Artificial Intelligence for health • Knowledge extraction • Decision-aid systems • Data analysis and risk prediction • Machine learning, deep learning - Health data processing • Data preprocessing, cleaning, management and mining • Computer-aided detection • Big data analysis, prediction and prevention • Cognitive algorithms for healthcare handling dynamic context management • Augmented reality, Motion detection and activity recognition - Devices, infrastructure and communication • Wearable & connected devices • Communication infrastructures, architectures and standards Blockchain for e-Health • Computing/storage infrastructures for e-Health • IoT devices & architectures for Smart Healthcare - Health information systems • Telemedicine, Teleservices • Computing/storage infrastructures for e-Health • Clinical Data Visualisation Standards - Security and privacy for e-health • Health data Analytics for Security and Privacy • E-health Software and Hardware Security • Embedded Security for e-health - Applications in P4 medicine
The high failure rate in the pharmaceutical industry has positioned biomarkers and personalized medicine in the frontline, as possible solutions. If executed right, biomarkers and companion diagnostics (CDx) can potentially help the drug industry enhance the probability of success, accelerate the time to market, and, more importantly, benefit patients by supporting accurate diagnosis and selection of the most effective and least toxic therapies. This book aims to examine the challenges and limitations in biomarkers and laboratory tests. It also offers advice on best practices to ensure proper application of biomarkers and bridges the gap between diagnostic business development claims and real-life deliverables. The book covers biomarkers for different purposes, provides examples from different technologies, which includes standard-of-care approved assays as well as for-investigational-use and for-research-use-only assays. It also includes new data for biomarkers in different therapeutic indications and offers case studies and practical examples. This book serves as a reference to drug developers, IVD providers, clinical labs, healthcare givers, academicians, and researchers for best practices to help increase the probability of success in drug development and improve patient management. - Provides the unique insight of an expert with extensive experience in diagnostics and clinical laboratory on one side and drug discovery and development on the other side - Addresses the challenges of drug development and precision medicine and suggests how to eliminate or mitigate these challenges through better utilization of biomarkers and diagnostics in drug development and patient management - Features case studies and real-life examples from different classes of biomarkers on different platforms for different therapeutic areas and includes more than 200 illustrations