BioBanking as the central tool for translational medicine CTM issue 2013
Clinical Protein Science & Imaging, Biomedical Center, Department of Measurement Technology and Industrial Electrical Engineering, Lund University, BMC C13, Lund, 221 84, Sweden
First Department of Surgery, Tokyo Medical University, 6-7-1 Nishishinjiku Shinjiku-ku, Tokyo, 160-0023, Japan
Clinical and Translational Medicine 2013, 2:4 doi:10.1186/2001-1326-2-4Published: 6 February 2013
The impact of mapping the human proteome
Globally, the health care organizations are under resource and cost constrains due to the increasing number of patients that are due to a fast increase of the 65+ age group requiring extensive medical hospitalization and treatments. Hospitals worldwide strive to seek the best cure for patients, suffering from various diseases. A consequence of these global changes, of healthy populations in relation to patients forms the basis for the build of large and centralized biobank facilities, with strategies where the search for an understanding of diseases at a molecular level is at heart. The efforts made lies within large governmental resource allocations where patient centers are collecting samples from clinical study participants in order to try to discover universal expression patterns and molecular signatures of disease and disease stages. Most developments in this area are aimed towards the discovery, and understanding diagnosis implementations. By providing the right treatment alternatives for patients care, at the right time point i.e., at a given disease stage development becomes a major goal where pharmaceutical industry, academia and the health care sector joins forces in large clinical epidemiological, population-, and disease based studies. This becomes a clear strategic link to the enhancement and prospects for personalized medicines and target directed diagnosis developments (Companion Diagnostics), which require coordinated efforts across a wide range of disciplines. Currently, companion diagnostics is at the core of the personalized medicine paradigm shift. It will identify patients who are most likely to benefit from a particular therapeutic product, as well as identify patients likely to be at increased risk for serious adverse reactions as a result of treatment with a particular therapeutic agent. It is predicted that more than half of all new drugs will require a companion diagnostic, which opens up for an endeavor for Proteomics research implementations.