We focus our research on the application of systems engineering and control for synthetic biology and bio-systems, as well as the evaluation and control of bio-processes.
At the laboratory, we work on designing prototypes and the proofs of concept for our developments, ranging from genetic circuits for the regulation of metabolic routes to control algorithms and the evaluation of bioreactors.
Combining computing and experimental capacities, we use the DBTL (design, build, test and learn) circuit of bio-engineering, thanks to our vast experience in the modeling and simulation of biological processes, always taking into account the different participating scales: from biological (genetic) parts, to biological devices, strains and microorganisms and their metabolism, as well as the experimental conditions of bio-processes.
In addition, automated build and test strains come from robotic platforms and the experimental results give feedback to the design phase, using artificial intelligence, machine learning and optimization. Thus, we can learn from these experimental data and improve the model predictions and the factor-response relation in the design.
This totally automated workflow meets all the flexibility requirements for an agile design and thus it is expected to be widely adopted in future biology production systems.
