"From Alzheimer's and diabetes to cancer, schizophrenia and even baldness, the list of ailments that elude cure marches on. The crisis in "translational science," or turning basic discoveries into therapies, has been brewing for years, but it hit a depressing nadir in 2005, when just 20 new drugs won approval from the Food and Drug Administration.
"Basic scientists and clinical investigators haven't had enough to do with each other," says endocrinologist William Crowley, director of clinical research at Massachusetts General Hospital. The resulting "bench-to-bedside block has been of great concern throughout academic medicine. But now we're starting to see things that hopefully will overcome it.""
Genomeweb New Breed of Genomics Centers Works Disease-Down, Not Genes-Up
""The concept can work if it's a really integrated center," says Michael Liebman, director of computational biology at the Abramson Family Cancer Research Institute at the University of Pennsylvania. He likes the disease focus because it makes more sense from a clinical standpoint - starting from the disease and its effect in patients and stripping that down, layer by layer, to understanding "how genomics and proteomics can help differentiate between subtypes of disease" - than starting with genomics and working up from genes."redux [05.17.02]
British Medical Journal Science, medicine, and the future: Bioinformatics
"An unprecedented wealth of biological data has been generated by the human genome project and sequencing projects in other organisms. The huge demand for analysis and interpretation of these data is being managed by the evolving science of bioinformatics. Bioinformatics is defined as the application of tools of computation and analysis to the capture and interpretation of biological data. It is an interdisciplinary field, which harnesses computer science, mathematics, physics, and biology. Bioinformatics is essential for management of data in modern biology and medicine. This paper describes the main tools of the bioinformatician and discusses how they are being used to interpret biological data and to further understanding of disease. The potential clinical applications of these data in drug discovery and development are also discussed."STKE Opening Pandora's Box: Clinical Data and the Study of Complex Diseases
"Complex diseases have complex phenotypes, and proper diagnosis requires that the analysis take into account the patient's history and exposure to environmental factors, as well as genetic information. Signaling information is one aspect of a grander "biomedical informatics" approach advocated for a better understanding of a patient's medically relevant disease phenotype."redux [04.17.02]
BBC Gene knowledge gap
"Research into human genetics is being limited by a lack of knowledge in other areas of science, say delegates at the Seventh International Human Genome Meeting (HUGO) in China.
Professor Lap-Chee Tsui, HUGO's outgoing president, says that our poor understanding of even basic human anatomy means that the human genome project is not delivering cures for genetic diseases as was hoped."redux [12.08.01]
HBS Working Knowledge Healthcare Conference Looks At Ailing Industry
"The goal now is to redefine disease based on the underlying biological mechanisms, Lander said. By that token, diseases are going to surprise us. Reclassifying them means that some diseases will get split in half and other diseases will get lumped together because they have the same mechanism, although they may look different to us, he said.
What this portends commercially is up to smart companies to figure out, he said. Companies will need the ability to integrate scale and informatics; they'll need what he called a "fleetness" with technologies—not just one favored technology, but many kinds. They shouldn't worry too much about hoarding intellectual property rights nor depend on one technology platform. It is more important to understand the big picture in the first place in order to choose the right target, Lander said."redux [08.01.01]
Stanford Medical Informatics Preprint Archive Challenges for Biomedical Informatics and Pharmacogenomics
"Pharmacogenomics requires the integration and analysis of genomic, molecular, cellular, and clinical data, and thus offers a remarkable set of challenges to biomedical informatics. These include infrastructural challenges such as the creation of data models and data bases for storing this data, the integration of these data with external databases, the extraction of information from natural language text, and the protection of databases with sensitive information. There are also scientific challenge in creating tools to support gene expression analysis, three-dimensional structural analysis, and comparative genomic analysis. In this review, we summarize the current uses of informatics within pharmacogenomics, and show how the technical challenges that remain for biomedical informatics are typical of those that will be confronted in the post-genomic era."redux [11.16.00]
The New England Journal Of Medicine: Correspondence Will Genetics Revolutionize Medicine?
"Neither we nor our critics defined a revolution in medicine. We mean a paradigm shift in theory or practice. Sotos and Rienhoff's plea for "precise diagnosis" epitomizes the current paradigm. In most of those who will have common disorders, the interaction of genetic, environmental, and behavioral factors makes the quest for precise diagnosis illusive."
"The revolution in medicine will come with the recognition, based in part on genetic research, that the quest for single causes for common diseases will seldom be fruitful and that a new paradigm of a causal web must be adopted. Interventions must be directed at the most vulnerable points in the web. Sometimes this will involve biomedical interventions. At other times, it will involve modifying aspects of our social structure, lifestyle, or environment that increase the risk of disease."redux [08.06.01]
Science Defining Disease in the Genomics Era
[ summary can be viewed for free once registered ]
"The human genome sequence will dramatically alter how we define, prevent, and treat disease. As more and more genetic variations among individuals are discovered, there will be a rush to label many of these variations as disease-associated. We need to define the term disease so that it incorporates our expanding genetic knowledge, taking into account the possible risks and adverse consequences associated with certain genetic variations, while acknowledging that a definition of disease cannot be based solely on one genetic abnormality."
"In thinking about how clinicians use the term disease, we think that three elements should be considered: disease is a state that places individuals at increased risk of adverse consequences . Treatment is given to those with a disease to prevent or ameliorate adverse consequences. The key element in this definition is risk: deviations from normal that are not associated with risk should not be considered synonymous with disease. Our definition has three definable elements and should serve clinicians well. Of course, its success will depend on whether it becomes clinically useful."redux [07.11.00]
Biospace.Com Big Picture Biology
"For most of us, formal biology education begins with complex systems--the traditional dissection of a frog in high school biology class is virtually a rite of passage in the U.S.
But the way many people learn about and invest in biotechnology is at the smallest end of the spectrum--the genome, now often described as the "periodic table" of biology. Genomics and all its related buzzwords have been responsible for much of the media attention, government grants, and investment capital heaped on the biotech industry over the past decade.
But just as there is a whole lot of chemistry that happens in between the periodic table and a birthday cake, there is a lot of biology in between the genome and a living organism. With the completion of biology's periodic table within sight, academics and industry players alike are pondering the best way to apply our hard won knowledge.
The only problem is, the path from genome to system seems to get harder the more we learn."
“Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.”BIOINFORMATICS IN THE 21st CENTURY
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