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Will genome-based precision medicine fix the problem of race/ethnicity-based medicine? To answer this question, Sun and Ong propose the concept of racialization of precision medicine, defined as the social processes by which racial/ethnic categories are incorporated (or not) into the development, interpretation, and implementation of precision medicine research and practice. Drawing on interview data with physicians and scientists in the field of cancer care, this book addresses the following questions: Who are the racializers in precision medicine, how and why do they do it? Under what conditions do clinicians personalize medical treatments in the context of cancer therapies? The chapters elucidate different ways in which racialization occurs and reveal that there exists an inherent contradiction in the usage of race/ethnicity as precision medicine moves from bench to bedside. The relative resources theory is proposed to explain that whether race/ethnicity-based medicine will be replaced by genomic medicine depends on the resources available at the individual and systemic levels. Furthermore, this book expands on how racialization happens not only in pharmacogenomic drug efficacy studies, but also in drug toxicity studies and cost-effectiveness studies. An important resource for clinicians, researchers, public health policymakers, health economists, and journalists on how to deracialize precision medicine.
"Will genome-based precision medicine fix the problem of race/ethnicity-based medicine? To answer this question, Sun and Ong propose the concept of racialization of precision medicine, defined as the social processes by which racial/ethnic categories are incorporated (or not) into the development, interpretation and implementation of precision medicine research and practice. Drawing on interview data with physicians and scientists in the field of cancer care, this book addresses the following questions: Who are the racializers in precision medicine, how and why do they do it? Under what conditions do clinicians personalize medical treatments in the context of cancer therapies? The chapters elucidate different ways in which racialization occurs, and reveal that there exists an inherent contradiction in the usage of race/ethnicity as genomic medicine moves from bench to bedside. The relative resources theory is proposed to explain that whether race/ethnicity-based medicine will be replaced by genomic medicine depends on the resources available at the individual and systemic levels. Furthermore, this book expands on how racialization happens not only in pharmacogenomic drug efficacy studies, but also in drug toxicity studies and cost effectiveness studies. An important resource for clinicians, researchers, public health policy makers, health economists and journalists on how to deracialize precision medicine"--
The enormous advances in nanomedicine and precision medicine in the past two decades necessitated this comprehensive reference, which can be relied upon by researchers, clinicians, pharmaceutical scientists, regulators, policymakers, and lawyers alike. This standalone, full-color resource broadly surveys innovative technologies and advances pertaining to nanomedicine and precision medicine. In addition, it addresses often-neglected yet crucial areas such as translational medicine, intellectual property law, ethics, policy, FDA regulatory issues, nano-nomenclature, and artificial nano-machines—all accomplished in a user-friendly, broad yet interconnected format. The book is essential reading for the novice and the expert alike in diverse fields such as medicine, law, pharmacy, genomics, biomedical sciences, ethics, and regulatory science. The book’s multidisciplinary approach will attract a global audience and serve as a valuable reference resource for industry, academia, and government.
Derived from the comprehensive two-volume set, Genomic and Personalized Medicine also edited by Drs. Willard and Ginsburg, this work serves the needs of the evolving population of scientists, researchers, practitioners and students that are embracing one of the most promising avenues for advances in diagnosis, prevention and treatment of human disease. From principles, methodology and translational approaches to genome discoveries and clinical applications, Essentials of Genomic and Personalized Medicine will be a valuable resource for various professionals and students across medical disciplines, including human genetics and genomics, oncology, neuroscience, gene therapy, molecular medicine, pharmacology, and biomedical sciences. Updates with regard to diagnostic testing, pharmacogenetics, predicting disease susceptibility, and other important research components as well as chapters dedicated to cardiovascular disease, oncology, inflammatory disease, metabolic disease, neuropsychiatric disease, and infectious disease, present this book as an essential tool for a variety of professionals and students who are endeavouring into the developing the diverse and practical field of genomic and personalized medicine. Full color throughout Includes contributions on genetic counselling, ethical, legal/regulatory, and social issues related to the practice of genomic medicine from leaders in the field Introductory chapter highlights differences between personalized and traditional medicine, promising areas of current research, and challenges to incorporate the latest research discoveries and practic Ancillary material includes case studies and lab questions which highlight the collaborative approach to the science
Bayesian Precision Medicine presents modern Bayesian statistical models and methods for identifying treatments tailored to individual patients using their prognostic variables and predictive biomarkers. The process of evaluating and comparing treatments is explained and illustrated by practical examples, followed by a discussion of causal analysis and its relationship to statistical inference. A wide array of modern Bayesian clinical trial designs are presented, including applications to many oncology trials. The later chapters describe Bayesian nonparametric regression analyses of datasets arising from multistage chemotherapy for acute leukemia, allogeneic stem cell transplantation, and targeted agents for treating advanced breast cancer. Features: Describes the connection between causal analysis and statistical inference Reviews modern personalized Bayesian clinical trial designs for dose-finding, treatment screening, basket trials, enrichment, incorporating historical data, and confirmatory treatment comparison, illustrated by real-world applications Presents adaptive methods for clustering similar patient subgroups to improve efficiency Describes Bayesian nonparametric regression analyses of real-world datasets from oncology Provides pointers to software for implementation Bayesian Precision Medicine is primarily aimed at biostatisticians and medical researchers who desire to apply modern Bayesian methods to their own clinical trials and data analyses. It also might be used to teach a special topics course on precision medicine using a Bayesian approach to postgraduate biostatistics students. The main goal of the book is to show how Bayesian thinking can provide a practical scientific basis for tailoring treatments to individual patients.
Artificial Intelligence for Drug Development, Precision Medicine, and Healthcare covers exciting developments at the intersection of computer science and statistics. While much of machine-learning is statistics-based, achievements in deep learning for image and language processing rely on computer science’s use of big data. Aimed at those with a statistical background who want to use their strengths in pursuing AI research, the book: · Covers broad AI topics in drug development, precision medicine, and healthcare. · Elaborates on supervised, unsupervised, reinforcement, and evolutionary learning methods. · Introduces the similarity principle and related AI methods for both big and small data problems. · Offers a balance of statistical and algorithm-based approaches to AI. · Provides examples and real-world applications with hands-on R code. · Suggests the path forward for AI in medicine and artificial general intelligence. As well as covering the history of AI and the innovative ideas, methodologies and software implementation of the field, the book offers a comprehensive review of AI applications in medical sciences. In addition, readers will benefit from hands on exercises, with included R code.
Precision Medicine, Volume 190 in the Progress in Molecular Biology and Translational Science series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of topics, including Evolution of Biomarkers and Strategies for Integrating the Precision Philosophy to Guide Monitoring of Individualized Autoimmunity Conditions and to Implement the Philosophy into Clinical Practice, Precision Medicine in Epilepsy, The use of ASOs for personized medicine, Adult medicine, EGFR, NF-KB signal and regulatory noncoding RNAs in cancer, Precision medicine with multi-omics strategies, deep phenotyping, and predictive analysis, The Paradox of Personalized Medicine, and more. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Progress in Molecular Biology and Translational Science series Updated release includes the latest information on the precision medicine
Clinical and Statistical Considerations in Personalized Medicine explores recent advances related to biomarkers and their translation into clinical development. Leading clinicians, biostatisticians, regulators, commercial professionals, and researchers address the opportunities and challenges in successfully applying biomarkers in drug discovery and preclinical and clinical development. Robust Biomarkers for Drug Development and Disease Treatment The first four chapters discuss biomarker development from a clinical perspective. Coverage ranges from an introduction to biomarkers to advances in RNAi screens, epigenetics, and rare diseases as targets for personalized medicine approaches. Subsequent chapters examine the statistical considerations in applying a personalized medicine approach, including multiplicity in pharmacogenomics. The last chapter assesses the regulatory issues involved in using biomarkers. Improve Patient Care and Reduce Costs and Side Effects Despite the vast amount of literature on biomarkers, there is no comprehensive book that integrates the clinical and statistical components. This book is one of the first to incorporate both the clinical and statistical aspects of biomarkers in the personalized medicine paradigm. Covering a wide spectrum of personalized medicine-related topics, it presents state-of-the-art techniques for advancing the application of biomarkers in drug discovery and development.
Computational techniques to analyze genetic data for identifying biomarkers. These biomarkers are crucial for diagnosing diseases, predicting outcomes, and personalizing treatments. The book covers various machine learning algorithms, such as deep learning, support vector machines, and random forests, explaining how they can be applied to genomic datasets. It discusses feature selection methods, data pre-processing, and the challenges of dealing with high-dimensional data. Case studies and real-world applications illustrate the practical aspects. Additionally, the book addresses ethical considerations and data privacy issues. It is an invaluable resource for bioinformaticians, computational biologists, and healthcare professionals seeking to harness machine learning for genomic
Precision medicine is an approach that proposes customized medical care based on the individual characteristics of each patient. The rapidly emerging field not only holds great promise for diagnosis of disease and prediction of risk of developing diseases, but also offers the possibility of remarkably fine-tuned remedies to improve patient health while minimizing the risk of harmful side effects. Many technologies including genetics, informatics, and medical imaging, are rapidly expanding the scope of precision medicine. Among these technologies, imaging is poised to play a major role in the age of precision medicine. By characterizing anatomy, physiology and metabolism of the patient, medical imaging enables precise, personalized procedures and predictive, patient-specific therapy selection. In recent years, image-guided treatment procedures are becoming more and more common in hospitals, replacing conventional surgery or allowing faster recoveries with fewer post-procedure complications. As the most widely used modality, ultrasound is playing an increasingly important role towards moving precision medicine into clinical practice. It is a safe, inexpensive diagnostic tool and capable of producing real-time and non-invasive images without significant biological effects. To date, lots of ultrasound imaging technology, such as gray-scale, color Doppler flow imaging (CDFI), contrast enhanced ultrasound (CEUS), elastography have been developed, which have greatly improved disease diagnosis, treatment and prognosis. Thanks to these progress, ultrasound imaging has also been used in fields that were not previously involved, such as the lungs and musculoskeletal tissues. With the rapid development of ultrasound contrast agents, ultrasound molecular imaging is moving from animal study into clinical practice. First-in-human results of ultrasound molecular imaging with BR55 (a kinase insert domain receptor [KDR]–targeted contrast microbubble) in patients with breast and ovarian lesions have been reported in 2017. Taking advantage of microbubble cavitation effect, ultrasound-assisted drug delivery technology also makes great progress. The clinical trial of blood-brain barrier disruption for chemotherapy delivery in the brain had been conducted and confirmed its safety and well toleration in patients with recurrent glioblastoma (GBM). Moreover, ultrasound provides an advantageous tool for image-guided therapy due to its capability of real-time imaging for deep tissues, contributing to greatly improved localization and targeting of diseased tissues. More interestingly, by imaging these drug-loaded contrast agents, ultrasound-mediated drug delivery can be visualized. All of the above examples help demonstrate the promising potential of ultrasound in precision medicine, not only for disease diagnosis, but also for treatment selection and prognosis evaluation. The present Research Topic here in Frontiers in Pharmacology aims to bring a collection of research describing ultrasound used for precision medicine in diagnosis, drug delivery and image-guided therapy.