This book focuses on novel approaches that provide a reliable basis for identifying which patients are likely to benefit from each treatment. Aimed at both clinical investigators and statisticians, it covers the development and validation of prognostic and predictive biomarkers and their integration into clinical trials.

Design and Analysis of Clinical Trials for Predictive Medicine provides statistical guidance on conducting clinical trials for predictive medicine. It covers statistical topics relevant to the main clinical research phases for developing molecular diagnostics and therapeutics-from identifying molecular biomarkers using DNA microarrays to confirming

Pharmacogenomics supports personalized medicine by translating genome-based knowledge into clinical practice, offering enhanced benefit for patients and health-care systems at large. Current routine practice for diagnosing and treating patients is conducted by correlating parameters such as age, gender and weight with risks and expected treatment outcomes. In the new era of personalized medicine the healthcare provider is equipped with improved ability to prevent, diagnose, treat and predict outcomes on the basis of complex information sources, including genetic and genomic data. Targeted therapy and reliable prediction of expected outcomes offer patients access to better healthcare management, by way of identifying the therapies effective for the relevant patient group, avoiding prescription of unnecessary treatment and reducing the likelihood of developing adverse drug reactions.

Ten years after the sequencing of the human genome, scientists have developed genetic tests that can predict a person's response to certain drugs, estimate the risk of developing Alzheimer's disease, and make other predictions based on known links between genes and diseases. However, genetic tests have yet to become a routine part of medical care, in part because there is not enough evidence to show they help improve patients' health. The Institute of Medicine (IOM) held a workshop to explore how researchers can gather better evidence more efficiently on the clinical utility of genetic tests. Generating Evidence for Genomic Diagnostic Test Development compares the evidence that is required for decisions regarding clearance, use, and reimbursement, to the evidence that is currently generated. The report also addresses innovative and efficient ways to generate high-quality evidence, as well as barriers to generating this evidence. Generating Evidence for Genomic Diagnostic Test Development contains information that will be of great value to regulators and policymakers, payers, health-care providers, researchers, funders, and evidence-based review groups.

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

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

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.