Project description
An adaptive approach to cancer drug dosing
Cancer treatment often follows a one-size-fits-all strategy, pushing drugs to the limit until resistance or toxicity forces a change. However, tumours are usually quick to evolve. Supported by the Marie Skłodowska-Curie Actions programme, the B-REDiTx project explores a smarter approach. Specifically, it will combine mathematical models with patient data, such as tumour volume and blood biomarkers. The project’s goal is to personalise treatment timing and dosages to delay resistance. The project will test these adaptive strategies in an ovarian cancer trial, using Bayesian inference and deep reinforcement learning to guide decisions under uncertainty. Ultimately, B-REDiTx aims to turn cancer therapy into a dynamic process in order to improve outcomes and quality of life for patients.
Objective
Cancers are complex, continuously evolving diseases unique to each individual patient. Yet, most drugs are administered according to fixed, “one-size-fits-all” strategies that always aim to deliver the maximum tolerated dose until it fails due to toxicity or resistance. “Adaptive Cancer Therapy” (AT) is a novel approach which seeks to delay drug resistance by personalising when and how much drug is given, based on the tumour’s response dynamics. After initial success in prostate cancer, there are now important questions about which patients would benefit from AT, and how should we optimally adapt therapy? In this 2-year fellowship, I will develop a computational framework to: i) understand and track resistance evolution from a patient’s tumour burden data (volume, blood biomarkers, ctDNA), and ii) translate this knowledge into personalised dosing strategies to slow resistance evolution and improve quality-of-life. To predict whether a patient will benefit from AT we need a firm, quantitative understanding of the dynamics of resistance evolution. Under supervision of Prof Trevor Graham at the ICR, I will develop a software package (B-REDi) which integrates a family of mathematical models and Bayesian inference to learn about the evolutionary route to resistance in a patient. Subsequently, I will deploy this package to investigate how AT is altering resistance evolution in a clinical trial in ovarian cancer (ACTOv). Finally, I will use deep reinforcement learning to explore how our calibrated models can guide treatment decisions even under uncertainty about resistance mechanisms. In the future, I plan to establish my own lab to develop computational tools to mitigate resistance and toxicity through schedule personalisation. This project will serve me as a steppingstone towards this goal, and it will contribute novel tools and insights towards a future in which mathematical models are used akin to weather forecasts to inform clinical decision-making.
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 computer and information sciences software
- medical and health sciences clinical medicine oncology
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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-2024-PF-01
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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.
SW7 3RP London
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.