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The initial sequencing of the human genome, carried out by an international group of experts, took 13 years and $2.7 billion to complete. In the decade since that achievement, sequencing technology has evolved at such a rapid pace that today a consumer can have his or her entire genome sequenced by a single company in a matter of days for less than $10,000, though the addition of interpretation may extend this timeframe. Given the rapid technological advances, the potential effect on the lives of patients, and the increasing use of genomic information in clinical care, it is important to address how genomics data can be integrated into the clinical setting. Genetic tests are already used to assess the risk of breast and ovarian cancers, to diagnose recessive diseases such as cystic fibrosis, to determine drug dosages based on individual patient metabolism, and to identify therapeutic options for treating lung and breast tumors, melanoma, and leukemia. With these issues in mind and considering the potential impact that genomics information can have on the prevention, diagnosis, and treatment of disease, the Roundtable on Translating Genomic-Based Research for Health hosted a workshop on July 19, 2011, to highlight and identify the challenges and opportunities in integrating large-scale genomic information into clinical practice. Integrating Large-Scale Genomic Information into Clinical Practice summarizes the speaker presentations and the discussions that followed them. This report focuses on several key topics, including the analysis, interpretation, and delivery of genomic information plus workforce, ethical, and legal issues.
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.
Genomic and Precision Medicine: Primary Care, Third Edition is an invaluable resource on the state-of-the-art tools, technologies and policy issues that are required to fully realize personalized health care in the area of primary care. One of the major areas where genomic and personalized medicine is most active is the realm of the primary care practitioner. Risk, family history, personal genomics and pharmacogenomics are becoming increasingly important to the PCP and their patients, and this book discusses the implications as they relate to primary care practitioners. - Presents a comprehensive volume for primary care providers - Provides succinct commentary and key learning points that will assist providers with their local needs for the implementation of genomic and personalized medicine - Includes a current overview on major opportunities for genomic and personalized medicine in practice - Highlights case studies that illustrate the practical use of genomics in the management in patients
Technologies collectively called omics enable simultaneous measurement of an enormous number of biomolecules; for example, genomics investigates thousands of DNA sequences, and proteomics examines large numbers of proteins. Scientists are using these technologies to develop innovative tests to detect disease and to predict a patient's likelihood of responding to specific drugs. Following a recent case involving premature use of omics-based tests in cancer clinical trials at Duke University, the NCI requested that the IOM establish a committee to recommend ways to strengthen omics-based test development and evaluation. This report identifies best practices to enhance development, evaluation, and translation of omics-based tests while simultaneously reinforcing steps to ensure that these tests are appropriately assessed for scientific validity before they are used to guide patient treatment in clinical trials.
"Describes and delineates the thirty eight essential genetic and genomic competencies that inform the practice of all nurses functioning at the graduate level in nursing, summarizes the key documents and processes used to identify these competencies, and identifies the members of the Steering, Advisory and Consensus Panel committees involved"--Provided by publisher.
Computational Genomics with R provides a starting point for beginners in genomic data analysis and also guides more advanced practitioners to sophisticated data analysis techniques in genomics. The book covers topics from R programming, to machine learning and statistics, to the latest genomic data analysis techniques. The text provides accessible information and explanations, always with the genomics context in the background. This also contains practical and well-documented examples in R so readers can analyze their data by simply reusing the code presented. As the field of computational genomics is interdisciplinary, it requires different starting points for people with different backgrounds. For example, a biologist might skip sections on basic genome biology and start with R programming, whereas a computer scientist might want to start with genome biology. After reading: You will have the basics of R and be able to dive right into specialized uses of R for computational genomics such as using Bioconductor packages. You will be familiar with statistics, supervised and unsupervised learning techniques that are important in data modeling, and exploratory analysis of high-dimensional data. You will understand genomic intervals and operations on them that are used for tasks such as aligned read counting and genomic feature annotation. You will know the basics of processing and quality checking high-throughput sequencing data. You will be able to do sequence analysis, such as calculating GC content for parts of a genome or finding transcription factor binding sites. You will know about visualization techniques used in genomics, such as heatmaps, meta-gene plots, and genomic track visualization. You will be familiar with analysis of different high-throughput sequencing data sets, such as RNA-seq, ChIP-seq, and BS-seq. You will know basic techniques for integrating and interpreting multi-omics datasets. Altuna Akalin is a group leader and head of the Bioinformatics and Omics Data Science Platform at the Berlin Institute of Medical Systems Biology, Max Delbrück Center, Berlin. He has been developing computational methods for analyzing and integrating large-scale genomics data sets since 2002. He has published an extensive body of work in this area. The framework for this book grew out of the yearly computational genomics courses he has been organizing and teaching since 2015.
Following on from 2015’s Healthcare Reform, Quality and Safety: Perspectives, Participants, Partnerships and Prospects in 30 Countries, this book encompasses a global perspective on healthcare while shifting the focus from reform to showcasing success stories of healthcare systems worldwide. It provides explanations of why various facets of healthcare systems work well in different contexts and offers the reader alternative models for consideration. The book features contributions from 60 countries, going much further than the common practice of focusing on affluent Western nations, to provide a comprehensive exploration of the success of healthcare systems globally. The majority of literature on health-sector improvement attempts to address the problems within systems, relating the errors that can and do occur, for example, and offering solutions and preventative strategies. This book of country case studies will approach the enhancement of health systems, patient safety and the quality of care in a new and innovative way, comprehensively surveying and synthesizing the success stories of healthcare systems around the world, utilizing Hollnagel’s Safety-II approach to acknowledge the importance of exploring what goes right, what works well, and why it works. These success stories may include reference to macro, meso or micro levels of healthcare systems, various sectors (e.g., aged care, acute care or primary care), or specific programs or projects. Health System Improvement Across the Globe: Success Stories from 60 Countries is unprecedented in terms of both reach and positive emphasis, and as such will be instrumental in changing ways of thinking about and guiding health-sector improvement.
This open access book presents thirteen outstanding doctoral dissertations in Information Technology from the Department of Electronics, Information and Bioengineering, Politecnico di Milano, Italy. Information Technology has always been highly interdisciplinary, as many aspects have to be considered in IT systems. The doctoral studies program in IT at Politecnico di Milano emphasizes this interdisciplinary nature, which is becoming more and more important in recent technological advances, in collaborative projects, and in the education of young researchers. Accordingly, the focus of advanced research is on pursuing a rigorous approach to specific research topics starting from a broad background in various areas of Information Technology, especially Computer Science and Engineering, Electronics, Systems and Control, and Telecommunications. Each year, more than 50 PhDs graduate from the program. This book gathers the outcomes of the thirteen best theses defended in 2020-21 and selected for the IT PhD Award. Each of the authors provides a chapter summarizing his/her findings, including an introduction, description of methods, main achievements and future work on the topic. Hence, the book provides a cutting-edge overview of the latest research trends in Information Technology at Politecnico di Milano, presented in an easy-to-read format that will also appeal to non-specialists.
Genomic and Precision Medicine: Oncology, Third Edition focuses on the applications of genome discovery as research points to personalized cancer therapies. Each chapter is organized to cover the application of genomics and personalized medicine tools and technologies to a) Risk Assessment and Susceptibility, b) Diagnosis and Prognosis, c) Pharmacogenomics and Precision Therapeutics, and d) Emerging and Future Opportunities in the field. - Provides a comprehensive volume written and edited by oncology genomic specialists for oncology health providers - Includes succinct commentary and key learning points that will assist providers with their local needs for implementation of genomic and personalized medicine into practice - Presents an up-to-date overview on major opportunities for genomic and personalized medicine in practice - Covers case studies that highlight the practical use of genomics in the management of patients
Advances in genetics and genomics are transforming medical practice, resulting in a dramatic growth of genetic testing in the health care system. The rapid development of new technologies, however, has also brought challenges, including the need for rigorous evaluation of the validity and utility of genetic tests, questions regarding the best ways to incorporate them into medical practice, and how to weigh their cost against potential short- and long-term benefits. As the availability of genetic tests increases so do concerns about the achievement of meaningful improvements in clinical outcomes, costs of testing, and the potential for accentuating medical care inequality. Given the rapid pace in the development of genetic tests and new testing technologies, An Evidence Framework for Genetic Testing seeks to advance the development of an adequate evidence base for genetic tests to improve patient care and treatment. Additionally, this report recommends a framework for decision-making regarding the use of genetic tests in clinical care.