Objective
Detecting disease at its earliest stages depends on being able to see what is happening inside the body at the molecular level. Positron Emission Tomography (PET) is a powerful imaging technique that makes this possible by using special radioactive molecules, called tracers, to reveal biological activity in real time. New technologies, like total-body PET, are revolutionizing PET imaging by allowing earlier detection and faster diagnoses, leading to more effective treatment for complex diseases like cancer, dementia, and heart disease. To unlock the full potential of total-body PET, we need new tracers that can target a wider range of diseases and biological processes. However, progress has been hindered not by a lack of promising tracer molecules, but by the difficulty of developing efficient radiochemical reactions to reliably produce them. This research will develop open-source machine learning tools to guide and accelerate these types of reactions. These tools will be validated using real radiochemical datasets, demonstrated on the synthesis of clinically relevant [¹⁸F]-radiotracers, and applied in the discovery of new radiochemical reactions. By doing so, this research will support a broad community of chemists, medical imaging specialists, and pharmaceutical scientists in harnessing the full potential of PET for studying and diagnosing disease.
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.
- medical and health sciences clinical medicine radiology nuclear medicine
- medical and health sciences basic medicine neurology dementia
- medical and health sciences clinical medicine oncology
- engineering and technology medical engineering diagnostic imaging
- natural sciences computer and information sciences artificial intelligence machine learning
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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-2025-PF
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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.
OX1 2JD Oxford
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.