Project description
How to identify resistance to antibody-drug conjugates
Antibody-drug conjugates (ADCs) have improved survival rates in solid tumours and blood cancers, with 14 approved and over 300 in development. However, resistance to ADCs remains a critical challenge and current clinical tools and preclinical models fail to effectively identify its underlying causes. The EU-funded OASIS project aims to determine the optimal companion diagnostics for each ADC and to develop an AI-based multimodal score to predict both response and toxicity associated with ADCs. It will use a range of assays, including molecular imaging, circulating tumour cells and machine learning-enhanced digital pathology. It will also create a biobank of patient-derived organoids to reflect ADC-resistance mechanisms. These will work to identify biomarkers of ADC resistance, providing insights to inform future therapeutic strategies.
Objective
Over the past 5 years, antibody drug conjugates (ADCs) have shown impressive improvements in survival outcomes of solid tumors and hematological malignancies. With 14 ADCs already approved across different countries and more than 140 that entered the clinical development, they are intended to replace standard chemotherapies across multiple tumor types over the next decade. Although ADCs show great clinical efficacy, resistance eventually occurs, and it becomes critical to understand resistance mechanisms to guide the choice of the following lines of therapy for patients who progress on a given ADC. Given the complex nature of ADCs, immunocompromised mouse models (nude mice, NOD-SCID or NOG mice) and currently used clinical assays (standard radiology, IHC, WES etc) are not the optimal preclinical and clinical tools, to identify the multiple causes of resistance. The OASIS project aims to generate a biobank of different patient-derived organoids (PDOs), which better recapitulate ADCs resistance and integrate different assays, spanning from whole-body molecular imaging (Ab-radiolabeled PET scan or immunoPET), circulating tumor cells (CTC), plasma proteomics, to multiplex immunofluorescence (MIF) and machine-learning enhanced digital pathology (AI-digital pathology) to capture most of the parallel mechanisms of resistance to ADCs. Such tools will enable to define biomarkers of ADC resistance that can inform further therapeutic decisions.
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 biological sciences biochemistry biomolecules proteins proteomics
- medical and health sciences clinical medicine radiology
- medical and health sciences basic medicine pathology
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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.2.1 - Health
MAIN PROGRAMME
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HORIZON.2.1.5 - Tools, Technologies and Digital Solutions for Health and Care, including personalised medicine
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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-RIA - HORIZON Research and Innovation Actions
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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-HLTH-2024-TOOL-05-two-stage
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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.
94805 Villejuif
France
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.