Project description
Connecting research and collaborative filtering for drug screening
Drug development pipelines incur high expenses, possess short lifespans and exhibit elevated failure rates. As such, drug repurposing, involving the systematic screening of existing compounds to uncover novel therapeutic uses, is a solution. Collaborative filtering leverages established drug-disease associations to formulate fresh recommendations. However, prior investigations lack emphasis on human supervision and exhibit resistance to biological data incorporation. With this in mind, the MSCA-funded RECeSS project aims to bridge the gap between drug research and collaborative filtering through the use of a classifier. This classifier addresses the issue of class imbalance within drug-disease pairings and the presence of incomplete drug/disease features using a semi-supervised learning approach. It establishes connections between projected matches and perturbed biological pathways via enrichment analyses.
Objective
In 2021, drug development pipelines last 10 years in average, and cost around $2 billion, while facing high failure rates, as only around 10% of Phase 0 drug candidates reach the commercialization stage. These issues can be mitigated through drug repurposing, where existent compounds are systematically screened for new therapeutic indications. Collaborative filtering is a semi-supervised learning framework that leverages known drug-disease matchings to make novel recommendations. However, prior works cannot be leveraged because of their lack of focus on human oversight and robustness to biological data.
This project aims at bridging the gap between drug research and collaborative filtering by implementing a RECeSS classifier, that is
(1) Robust: deals with class imbalance in drug-disease matchings, and missing drug/disease features, by semi-supervised learning;
(2) Explainable: connects predicted matchings to perturbed biological pathways through enrichment analyses, based on the learnt importance of features in the model;
(3) Controllable: guarantees a bound on the false positive rate using an adaptive learning scheme;
(4) Standard: algorithms are trained and tested by a standardized open-source pipeline.
Predicted matchings will be independently validated by structure-based methods. This innovative interdisciplinary project relies on a solid basis of newly curated data (up to 1,386 drugs, 1,599 diseases, 12 feature types). It is primarily supervised by Pr. Olaf Wolkenhauer, at SBI Rostock, whose team has an expertise in drug repurposing, in systems biology and data imbalance in machine learning. This project will help the fellow develop new skills, and enhance her professional maturity in academia.
In the short term, this would yield the first method that fully integrates biological interpretation and risk assessment to collaborative filtering-based repurposing. Long-term outcomes might help define sustainable and transparent drug development for rare diseases.
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.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
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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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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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.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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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) HORIZON-MSCA-2022-PF-01
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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.
18055 Rostock
Germany
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.