Project description
Cancer treatment with advanced modelling
Current cancer treatments rely on understanding the intricate signalling processes within cancer cells and their interactions with immune cells. However, existing models focus on limited pathways and use cell line data that poorly represent real cancer tissues. This hampers the identification of effective drug targets. In this context, the ERC-funded INTEGRATE project aims to transform this landscape. By combining mechanistic modelling with machine learning, INTEGRATE will develop scalable computational methods to analyse large-scale biomedical data. Using tools like natural language processing and signal processing, the project will link patient-derived omics and phenotypic data. This approach promises to refine clinical trial designs, advance precision medicine, and pave the way for creating digital twins in cancer research.
Objective
Modern cancer therapeutics target signalling processes within the cancer cells and the interaction of cancer and immune cells. A comprehensive understanding of these signalling processes is therefore essential to identify drug targets, plan clinical trials, and to select suitable drugs, drug combinations and drug dosages for a specific patient. Yet, most of the available mathematical models capture only a small number of molecular species and pathways, thereby ignoring important crosstalk and feedback loops. Furthermore, these models are usually based on experimental data for cell lines, which behave differently from complex cancer tissues.
In INTEGRATE, I will develop computational methods for the full process of data-driven modelling of signalling processes in cancer, ranging from model development to parameterisation all the way to uncertainty analysis. To this end, I will combine methods from the fields of mathematical modelling, machine learning, and signal processing with established approaches in systems biology. The model development will employ natural language processing and an automatic testing framework. For federated model inference, I will develop scalable mini-batch optimisation and marginalisation based uncertainty quantification. To refine models, I will exploit tools from signal processing, such as blind identification of latent variables. I will apply the developed scalable mechanistic modelling approach to integrate large-scale biomedical data for molecular phenotyping studies and clinical trials across sites. This will provide mechanistic models reconciling the available data.
The study will, for the first time, combine mechanistic modelling and machine learning for the integrated analysis of patient-derived omics and phenotypic data. By linking these data sources, INTEGRATE will deepen our understanding of biological signal processing and provide the basis for the development of digital twins.
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.1.1 - European Research Council (ERC)
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Topic(s)
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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
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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-ERC - HORIZON ERC Grants
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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) ERC-2023-COG
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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.
53113 Bonn
Germany
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