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Revision as of 05:20, 7 January 2013
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
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.