Objetivo
Obesity is one of the most serious and fast-growing health problem in the European Union, and a leading cause of diabetes. The main barrier for approval of an anti-obesity drug is the safety requirements. We propose to overcome this barrier by discovering phenotypes and biomarkers that identify subsets of patients with safe and efficacious responses to drugs, and by identifying new indications of existing drugs with proven safety profiles. To be approved, anti-obesity drugs need to show a decrease in abdominal fat. We focus on approaches targeting directly abdominal fat cells. In the last years only the cannabinoid CB1 receptor antagonist Rimonabant has been approved as a therapeutic agent to combat complicated obesity. Research performed with this drug has clearly revealed a role for the endogenous cannabinoid system in controlling energy homeostasis. However, its utility is limited to a restricted set of patients. A new phenotype and/or biomarker may identify responsive patients with good safety profiles. This proposal aims to discover novel or improved treatments in the shortest possible timeframe through three synergistic Specific Aims: 1) Clinical phenotyping of obese patients to identify those that would benefit from existing therapies such as Rimonabant. 2) Discover biomarkers for subsets of obese patients that may correlate with therapeutical outcomes. These biomarkers will be discovered by a novel approach called Combinatorial Cytomic Biomarkers developed by OrphaMed, applied to cells from two physiologically interlinked sources: blood and abdominal-fat samples, extracted from the above phenotyped patients. 3) Identify new indications of existing drugs, alone or in combination, with potential anti-obesity efficacy by lowering the fat content and the glucose uptake of abdominal fat cells, which would be expected to improve carbohydrate/lipid metabolism and lower body weight, extracted from the above phenotyped patients. This will be accomplished by screening approximately 2.000 known drugs against these fat cells using the novel technology platform “ExviTech” from OrphaMed. Candidates would be evaluated in animal models of obesity.
Ámbito científico (EuroSciVoc)
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural. Véase: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS clasifica los proyectos con EuroSciVoc, una taxonomía plurilingüe de ámbitos científicos, mediante un proceso semiautomático basado en técnicas de procesamiento del lenguaje natural. Véase: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- ciencias médicas y de la saludmedicina clínicaendocrinologíadiabetes
- ciencias naturalesciencias biológicasbioquímicabiomoléculaslípidos
- ciencias médicas y de la saludmedicina básicafisiologíahomeostasis
- ciencias médicas y de la saludciencias de la saludnutriciónobesidad
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Tema(s)
Convocatoria de propuestas
FP7-HEALTH-2007-B
Consulte otros proyectos de esta convocatoria
Régimen de financiación
CP-TP - Collaborative Project targeted to a special group (such as SMEs)Coordinador
29590 MALAGA
España