Current evolutions in medical practices induce a change of paradigm with the convergence of diagnosis and therapy, going to personalized medicine and “theranostics”. One can observe the new role of biomarkers in biomedical and therapeutic applications, for instance in the development of molecular multiplex biosensors (nucleic acid, proteins, and metabolites). In addition this is supported by the explosion of point-of-care (POC) technologies and of home monitoring/testing devoted to probe patient parameters in his direct environment. In this context, synthetic biology provides new opportunities to develop a novel generation of biological biosensors able to perform multiplex biomarker detection, simple computation and return of a useful result. However, in order to design robust circuits and to be reliable in a clinical context, synthetic biological biosensor systems must progress in their biochemical implementation of logical tasks and simple operations.
While for the biologist, as well as for the mathematician, the sizes of the biological networks and the number of elementary
interactions constitute a complexity barrier, for the computer scientist the difficulty is not that much in the size of the
networks than in the unconventional nature of biochemical computation. Unlike most programs, biochemical computation
involve transitions that are stochastic rather than deterministic, continuous-time rather than discrete-time, poorly insulated
in compartments instead of well-structured in modules, and created by evolution instead of by rational design. Although
designing biochemical systems is in several ways similar to designing electronic systems, there are fundamental
differences that require novel solutions. For example, an asynchronous design approach (in contrast to the standard
synchronous approach to electronic system design) is more natural for biochemical reactions, which may vary in a wide
spectrum of time scales. Signal integrity and modularity have to be carefully considered since molecules without confining
to local compartments may have undesirable global interference. Moreover, available molecular species can be very
limited and should be reused whenever possible. These difficulties await new design automation and robustness analysis
tools for engineering biochemical systems.
The scientific challenge proposed in this project is to master the complexity of biochemical computation and biochemical
programming, by working on four fronts:
• development of a compiler of behaviour specifications into biochemical reactions,
• use of chemical reaction networks (CRNs) as a programming language suitable for mapping into biochemical system design,
• implementation of biochemical biosensor programs in microfluidic reactors,
• formal verification methods to assess what a circuit can and cannot do.
Monsieur Franck Molina (Modélisation et ingénierie des systèmes complexes biologiques pour le diagnostic (Sys2Diag))
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
Inria Saclay - Ile-de-France - équipe LI Inria - Centre de recherche Saclay - Ile-de-France - Equipe projet LIFEWARE
NTU National Taiwan University
CNRS-SYS2DIAG Modélisation et ingénierie des systèmes complexes biologiques pour le diagnostic (Sys2Diag)
Help of the ANR 333,490 euros
Beginning and duration of the scientific project: February 2017 - 36 Months