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Principles of Translational Science in Medicine: From Bench to Bedside, Second Edition, provides an update on major achievements in the translation of research into medically relevant results and therapeutics.
The book presents a thorough discussion of biomarkers, early human trials, and networking models, and includes institutional and industrial support systems. It also covers algorithms that have influenced all major areas of biomedical research in recent years, resulting in an increasing numbers of new chemical/biological entities (NCEs or NBEs) as shown in FDA statistics.
The book is ideal for use as a guide for biomedical scientists to establish a systematic approach to translational medicine.
Contains contributions from world leaders in translational medicine, including the former NIH director and authorities from various European regulatory institutions
Principles of Translational Science in Medicine: From Bench to Bedside, Second Edition, provides an update on major achievements in the translation of research into medically relevant results and therapeutics.
The book presents a thorough discussion of biomarkers, early human trials, and networking models, and includes institutional and industrial support systems. It also covers algorithms that have influenced all major areas of biomedical research in recent years, resulting in an increasing numbers of new chemical/biological entities (NCEs or NBEs) as shown in FDA statistics.
The book is ideal for use as a guide for biomedical scientists to establish a systematic approach to translational medicine.
Échantillon de lecture
Chapter 2.1.1 "Omics" Translation
A Challenge for Laboratory Medicine
Mario Plebani, Martina Zaninotto, and Giuseppe Lippi Introduction
The rapid advances in medical research that have occurred over the past few years have allowed us to dissect molecular signatures and functional pathways that underlie disease initiation and progression, as well as to identify molecular profiles related to disease subtypes in order to determine their natural course, prognosis, and responsiveness to therapies (Dammann and Weber, 2012). The "omics" revolution of the past 15 years has represented the most compelling stimulus in personalized medicine that, in turn, should be simply defined as "getting the right treatment to the right patient at the right dose and schedule at the right time" (Schilsky, 2009). As a matter of fact, among the 20 most-cited papers in molecular biology and genetics that have been published in the past decade, 13 entail omics methods or applications (Ioannidis, 2010). "Omics": What does it mean?
Omics is an English-language neologism that refers to a field of study in biology focusing on large-scale and holistic data, as derived from its root of Greek origin which refers to wholeness or to completion. Initially, the suffix omics had been used in the word genome, a popular word for the complete genetic makeup of an organism, and later, in the term proteome. Genomics and proteomics succinctly describe a new way of holistic analysis of complete genomes and proteomes, and the success of these terms led to more emphasis in the trend of using omics as a convenient term to describe holistic ways of looking at complex systems, particularly in biology. Fields with names like genomics (genetic complement), transcriptomics (gene expression), proteomics (protein synthesis and signaling), metabolomics (concentration and fluxes of cellular metabolites), metabonomics (systemic profiling through the analysis of biological fluids), and cytomics (the study of cell systems-cytomes-at a single cell level) have been introduced in medicine with increasing emphasis (Plebani, 2005). However, beyond these terms, multiple "omics" fields, with names like epigenomics, ribonomics, epigenomics, oncopeptidomics, lipidomics, glycomics, spliceomics, and interactomics, have been similarly explored regarding molecular biomarkers for the diagnosis and prognosis of human diseases. Each of these emerging disciplines grouped under the umbrella of the term omics shares the simultaneous characterization of dozens, hundreds, or thousands of genes (genomics), gene transcripts (transcriptomics), or proteins (proteomics) and other molecules, that in aggregate and in parallel should be coupled with sophisticated bioinformatics to reveal aspects of biological function that cannot be culled from traditional linear methods of discovery (Finn, 2007). While an increasing body of literature has been produced to prove that "omics" will irrevocably modify the practice of medicine, that change has yet to occur and its precise details are still unclear. The reasonable assumption that the application of "omics" research will be riddled with difficulties has led to a much better appreciation of concepts of knowledge translation, translational research, and translational medicine. Proteomics as a Paradigm of Problems in Translational Medicine
The paradigm of obstacles in translating new "omics" insights into clinical practice is a study reporting that a blood test, based on pattern-recognition proteomics analysis of serum, was nearly 100% sensitive and specific for detecting ovarian cancer and was possibly useful fo
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