Objective
Alcohol addiction ranks among the primary global causes of preventable death and disabilities in human population, but treatment options are very limited. Rational strategies for design and development of novel, evidence based therapies for alcohol addiction are still missing. Within this project, we will utilize a translational approach based on clinical studies and animal experiments to fill this gap. We will provide a novel discovery strategy based on systems biology concepts that uses mathematical and network theoretical models to identify brain sites and functional networks that can be targeted specifically by therapeutic interventions. To build predictive models of the ‘relapse-prone’ state of brain networks we will use magnetic resonance imaging and neurochemical data from patients and laboratory animals. The mathematical models will be rigorously tested through experimental procedures aimed to guide network dynamics towards increased resilience. We expect to identify hubs that promote ‘relapse-proneness’ and to predict how aberrant network states could be normalized. Proof of concept experiments in animal will need to demonstrate this possibility by showing directed remodeling of functional brain networks by targeted interventions prescribed by the theoretical framework. Thus, our translational goal will be achieved by a theoretical and experimental framework for making predictions based on fMRI and mathematical modeling, which is verified in animals, and which can be transferred to humans. To achieve this goal we have assembled an interdisciplinary consortium (eight European countries) of world-class expertise in all complementary skills required for the project. If successful this project will positively impact on the development of new therapies for a disorder with largely unmet clinical needs, and thus help to address a serious and widespread health problem in our societies.
Fields of science
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- medical and health sciencesbasic medicinepharmacology and pharmacypharmaceutical drugs
- medical and health sciencesclinical medicinecardiologycardiovascular diseases
- medical and health scienceshealth sciencespersonalized medicine
- natural scienceschemical sciencesorganic chemistryalcohols
- engineering and technologymedical engineeringdiagnostic imagingmagnetic resonance imaging
Programme(s)
Funding Scheme
RIA - Research and Innovation actionCoordinator
68159 Mannheim
Germany
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Participants (15)
BN1 9RH Brighton
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581 83 Linkoping
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84105 Beer Sheva
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Participation ended
39106 Magdeburg
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Participation ended
400504 Cluj-Napoca
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CB2 1TN Cambridge
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16163 Genova
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28006 Madrid
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00014 HELSINGIN YLIOPISTO
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Participation ended
10589 Berlin
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Legal entity other than a subcontractor which is affiliated or legally linked to a participant. The entity carries out work under the conditions laid down in the Grant Agreement, supplies goods or provides services for the action, but did not sign the Grant Agreement. A third party abides by the rules applicable to its related participant under the Grant Agreement with regard to eligibility of costs and control of expenditure.
Participation ended
10589 Berlin
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9777518 JERUSALEM
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80539 Munchen
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2311 EZ Leiden
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400191 Cluj Napoca
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