Difference between revisions of "Sysdiag:Research"

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Revision as of 03:20, 7 January 2013


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The Sysdiag laboratory was created in 2007 and applies synthetic biology to engineer next-generation medical diagnostics tools. Sysdiag is a joint-institute between the biotech company Bio-Rad (Hercules, USA), and the French Centre National de la Recherche Scientifique (CNRS). Sysdiag focuses on :

i) identifying new biomarkers of complex diseases(cancer, neurodegenerative diseases, diabetes and its complications) and the related pilot assays.
ii) Engineer innovative diagnostics tools based on biologically-inspired nano-objects.
iii) develop composition frameworks supporting in silico biological networks conception.

Medical diagnostics: a societal and scientific challenge
Longer life expectancy and an increasing number of risk factors lead to a global increase in infectious diseases, cancers, cardiovascular diseases and diabetes. Many of these diseases require an early diagnostics and a systematic screening of populations at risk. To be reliable, medical diagnostics must often be based on a pattern of biomarkers, increasing the complexity and the cost of the test, and therefore limiting its widespread deployment. Thus, the demand for simple, robust, and inexpensive diagnostics systems is constantly increasing. Biological systems offer an attractive alternative to perform inexpensive detection.

Applications of biological systems to medical diagnostics
Biological systems and their components can be compared to nano-machines operating independently, analyzing their internal state and their environment and computing an appropriate phenotypic response. The natural repertoire from which to retrieve useful biological functions is immense. Importantly, biological systems are able to integrate various kinds of clinically relevant physical and chemical signals (ligands, osmolarity, pH, temperature) which are not commonly detected in combination in existing diagnostics tests. Finally, because of the self-replication of biological systems, a cellular diagnostics system would have reduced production costs compatible with systematic screening and widespread deployment.