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Integrated AI-Driven Systems For Kidney Transplant Precision Medicine (AI-Care)

Project description

AI for kidney transplant precision medicine

In the last two decades, short-term allograft and patient survival rates in kidney transplantation have significantly improved. However, long-term graft survival remains low, primarily due to rejection. Enhanced patient monitoring and rejection risk assessment are crucial for improving allograft longevity, but they require more comprehensive patient data and integrative research strategies. The ERC-funded AI CARE project aims to advance transplant precision medicine by developing a personalised, non-invasive patient monitoring system using cell-free DNA technology (liquid biopsy). It also seeks to improve rejection diagnosis beyond conventional histology through molecular technologies and digital pathology. By gaining mechanistic insights into transplant organ diseases and enhancing diagnostic accuracy, the project aims to apply this knowledge to new research areas.

Objective

Despite considerable improvements in short-term allograft and patient survival in kidney transplantation in the past two decades, long-term graft survival remains low, with 20% of transplants failing within five years. Rejection remains a leading cause of graft loss, with immediate consequences for patient morbidity and mortality, posing a major burden on healthcare systems. Increased allograft longevity requires improved patient monitoring and rejection risk stratification using mechanistically informed, non-invasive biomarker strategies and precision diagnostics. The main limitation for such an endeavor is the lack of deeply phenotyped cohorts. Given the complexity and heterogeneity of allograft rejection, patient cohorts with sufficient volume, velocity, variety and validity of data are critical in order to capture disease activity, disease stage, improve risk stratification and optimize treatment. Another limitation is the paucity of multidimensional and integrative research strategies. The goal of the ERC AI-Care project is therefore to go beyond the current state of the art by establishing a transplant precision medicine system to 1) facilitate personalized, non-invasive patient monitoring using cell-free DNA technology (Liquid biopsy) 2) improve rejection diagnosis beyond conventional histology using molecular technologies and digital pathology, and 3) gain further mechanistic insights and improve diagnostic accuracy of transplant organ diseases and apply this knowledge to new research areas.

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HORIZON-ERC - HORIZON ERC Grants

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Call for proposal

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(opens in new window) ERC-2023-COG

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Host institution

UNIVERSITE PARIS CITE
Net EU contribution

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.

€ 1 675 679,50
Address
85 BD SAINT GERMAIN
75006 PARIS
France

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Region
Ile-de-France Ile-de-France Paris
Activity type
Higher or Secondary Education Establishments
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Total cost

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.

€ 1 675 679,50

Beneficiaries (2)

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