Project description
A novel in vitro model of age-related muscle loss
Age-related muscle atrophy is a condition that affects millions of individuals worldwide decreasing both quality of life and life expectancy. Existing experimental models do not account for the role of cellular ageing and senescence in muscle wasting, resulting in the design of ineffective therapies. To address this problem, the EU-funded Pept-AGE project will develop an improved in vitro model that effectively recapitulates age-related muscle loss and use it to identify the affected pathways. By integrating results from the in vitro model into Nuritas' Artificial intelligence peptide finder platform, deep learning will further contribute to the discovery of novel bioactive peptides capable of ameliorating muscle loss. The clinically relevant Pept-AGE model has the potential to advance therapeutics against disorders associated with muscle atrophy.
Objective
Loss of muscle function through advancing age, injury or disease significantly decreases both the quality of life and life expectancy of millions of individuals globally. Treatments tackling this issue have proven elusive as in vitro systems aimed at modelling age-related muscle atrophy are primarily murine based and fail to capture the complexity of this process in humans. In particular, these models neglect to accurately account for the impact of cellular-ageing and senescence on the advancement of sarcopenia-induced muscle wastage. This project aims to address these problems by firstly developing a more human aligned in vitro ageing model to elucidate key pathways associated with muscle loss. From this in vitro model, we will identify key mechanistic pathways driving age-related muscle loss at the transcriptional and translational level. Supplied with suitable data, artificial intelligence (AI) has to potential to rapidly accelerate the discovery of novel therapeutics. As such, here, informed by data derived from the human in vitro model, Nuritas’ proven artificial intelligence platform will be applied to identify novel bioactive peptides that have the potential to counter the impact of cellular aging thus ameliorating muscle loss. This innovative proposal affords the experienced researcher the opportunity to bring his knowledge at the forefront of ageing research back to Europe and combine it with the expertise of an industry leader in AI therapeutic discovery, facilitating decisive two-way intersectoral transfer of knowledge. By integrating these distinct interdisciplinary skillsets this project has the expected outcomes of discovering more clinically relevant, translational models and therapeutics for muscle wastage disorders.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences artificial intelligence
- natural sciences biological sciences biochemistry biomolecules
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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H2020-EU.1.3. - EXCELLENT SCIENCE - Marie Skłodowska-Curie Actions
MAIN PROGRAMME
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H2020-EU.1.3.2. - Nurturing excellence by means of cross-border and cross-sector mobility
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) H2020-MSCA-IF-2019
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
D02 RY95 Dublin 2
Ireland
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.