Objective
This project aims to improve the treatment of metastasized colorectal carcinoma (mCRC), as treatment options after first line chemotherapy are desperately needed. The key to improvement of cancer therapy resides in optimal combination of drugs. Optimally combining drugs is non-trivial due to the large number of possibilities, especially when more than two drugs are combined at various doses. In the current research program I propose to use a differential evolution guided stochastic search algorithm to guide the way in finding optimal combination therapies. In previous research I have applied this feedback system control (FSC) technique to navigate through the enormous parametric space of nine angiostatic drugs at four doses. The straightforward iterative approach of in vitro cell viability testing and algorithm-based analysis identified optimal synergistic low-dose drug combinations. In vivo translation by maintaining the drug dose ratio led to effective anti-cancer activity, without evidence of side-effects.
A new screen for optimal targeted combination treatment of advanced CRC will be performed. A series of 7 genetically different human CRC cell lines will be used in this screen, thus simulating personalized treatment. The optimized combinations will be ‘ratiometrically’ translated into orthotopic and metastasizing preclinical CRC mouse models and tested in parallel to standard chemotherapy regimens. Development of a method for a personalized screen using freshly isolated tumor cells will prepare the technology for application in the clinic.
Using an innovative strategy I previously identified a series of novel markers of the tumor endothelium. After validation of these targets, this project aims for the design of new drugs to be used in a screen for optimal combination therapy for mCRC. The translational and multidisciplinary nature of the current proposal aims for preparing an improved therapeutic combination regimen for testing in cancer patients.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- medical and health sciences clinical medicine oncology
- medical and health sciences basic medicine pathology
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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.1.1. - EXCELLENT SCIENCE - European Research Council (ERC)
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.
ERC-STG - Starting Grant
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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-2015-STG
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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.
1211 Geneve
Switzerland
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.