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EMET - Evaluation et modélisation des effets thérapeutiques

Disciplines Medicine - Health
Research fields Immunology, Infectiology, Clinical pharmacology, Physiology, Clinical research, Public health
Supporting organisms UCBL, CNRS
Geographical location Domaine de la Buire - UCBL
Team leader Christophe Lega


The “Evaluation and Modeling of the Therapeutic Effects” (EMET) team joined UMR5558 in 2007, to conduct ambitious projects in pharmacology modeling, coupled with innovative disease modeling. The main domains of expertise include cardiovascular prevention (statins, blood pressure lowering drugs, stroke), cancer (angiogenesis, PK of chemotherapy encapsulated in red cells), infectious disease (modeling of antiHPV vaccine impact, of immune disorders in septic shock, of tuberculosis and its treatment, translation of PK-PD antibiotic adult models into children applications, identification of new viruses and immune phenomena involved in cardiovascular diseases). The aims in building PK-PD and disease models, and running them in individuals of virtual populations, are to simulate different therapeutic strategies, to optimize their public health impact, but also to discover and test in silico new potential drug targets, or to understand complex multifactorial mechanisms such as antibiotic resistance. This new paradigm represents a high potential for biotechnology SMEs as well as big pharmaceutical companies. Our EMET team contributes to the CNRS GDR STIC Santé, has set up a research network (the Institute for Theoretical Medicine), originated the startup NovaDiscovery, owner of one licence and in charge of WP4 of IRT BioAster (Institut de Recherche Technologique). The EMET team is a member of IXXI (Institute of Complex Systems) and EIBSM (European Institute for Systemic Biology and Medicine). EMET is in charge of a European platform for simulating clinical trials in rare disease, to help in choosing the optimal experimental design (CRESIM, FP7). EMET organizes two master curricula, one in pharmacology and therapeutics modeling, and one at the European level linked with Innovative Medicine Initiative of pharmaceutical medicine.

KEY-WORDS : Pharmacological models, Disease models, Public health impact models, Systems biology, Realistic virtual populations, Meta-analysis