Objective
The translational paradigm of testing stroke treatments in animal models before proceeding to clinical trial has resulted in little success. A number of scientific practices likely contribute to this translational failure: Low study quality and bias in animal studies can cause overly or falsely positive results. Failure to publish outcomes contributes to an inaccurate body of knowledge and the wasteful duplication of experiments. Limited analysis of previous literature leads to weakly justified studies that may not investigate the most promising treatments. I aim to address these issues by developing new approaches to systematic review. Systematic review and meta-analysis are transparent, reproducible methods to objectively synthesise and interpret scientific evidence. They are routinely used in clinical research to support evidence-based healthcare decisions but remain underdeveloped and underutilised in preclinical research. Current systematic review methods provide a summary effect of treatments but do not adjust for the quality of evidence from different studies or the range of conditions where an intervention is effective. Additionally, while they are used to summarise data from different studies, they cannot present the comparative effectiveness of different treatments. I will develop sophisticated statistical techniques to address these drawbacks and analyse published literature describing animal models of stroke. I will be one of the first to adapt the powerful new method, network meta-analysis, to assess preclinical data. My results will inform drug selection for preclinical multicentre stroke trials and identify aspects of experimental design that contribute to biased research outcomes. Gaps in current knowledge will be identified, focussing animal experiments and reducing unjustified animal use and the duplication of studies into low potential areas. My new approach can be used for prioritising research in a broad range of biomedical fields.
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 knowledge engineering ontology
- medical and health sciences basic medicine neurology stroke
- medical and health sciences clinical medicine anaesthesiology
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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-EF-ST - Standard EF
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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-2015
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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.
EH8 9YL Edinburgh
United Kingdom
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.