Predictive cell models

The aim of this transversal axis relies on the skills and knowledge shared by the 3 teams, and includes the development of cellular and animal models for:

– Screening and identifying new biological processes involved in the diseases by limiting the use of animal models (according to the 3R EU-directive);

– Identifying therapeutic methods and routes of administration to limit adverse effects;

– Developing easy-to-use diagnostic methods for prevention and patient monitoring.

The strategy for the identification of physiopathological processes is based on a long history of knowledge and skills in liver and digestive cell models, including primary cultures and differentiated cell models (2D, 3D, organoids), which are shared between the teams. They allow the analysis of the role of specific genes that represent potential targets by using in particular: a) the CRISPR / CAS9 technology for the prediction of the role of genes and their variants; b) the impact of biological molecules, including nutrients, drugs, chemicals present in the environment and other xenobiotics; and c) the relationships between the microbiota and enterocytes (human and porcine) and the differentiation processes of liver cells. The integration of microfluidic devices linking different tissue types will enable the modelling of exchange systems between cells. The interest of such a predictive strategy is highlighted by the national PREVITOX network, headed by NuMeCan and supported by ANSM and Inserm, that brings together 35 national laboratories and infrastructures dedicated to the evaluation of drug toxicity using in vitro and in silico approaches.

The therapeutic methods include : (i) the characterization and prediction of the behavior and impact of new drugs, coupled or not with new candidate vectors and nano-vectors targeting liver, for example in drug delivery and/or internal metabolic radiotherapy of liver cancer, with the support of the Synanovect platform; (ii) the evaluation of processes aiming at correcting nutritional and metabolic disorders through the use of specific nutrients, probiotics, and/or by using neurobehavioral therapeutics. The evaluation of minimally invasive predictive diagnostic methods, in particular those based on decisional algorithms or on the determination of global metabolic signatures, (e.g. mass spectrometry, infrared or Raman spectroscopies) is carried out in strong interactions with the Institute for Research in Mathematics of Rennes (IRMAR).

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