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Optimizing treatment of cancer patients infected with COVID-19 and other preconditions using mathematical modelling

Project description

A model to predict optimal therapy for cancer patients with COVID-19

Patients with cancer are at increased risk of contracting SARS-CoV-2 and becoming severely ill. To avoid discontinuity of their clinical care, there is an imminent need to identify the right combination of drugs. The EU-funded CancerCOtreat project proposes to develop an in silico system to model COVID-19 progression in the context of cancer. The system combines the biology of SARS-CoV-2 infection, the action of approved drugs and the pathophysiology of cancer patients. It will help explore the efficacy of various treatments and identify synergistic combinations that provide optimal therapy for cancer patients infected with SARS-CoV-2.

Objective

Cancer patients are of high risk to develop severe COVID-19, which has a negative impact on their clinical management. Cancer therapy and COVID-19 severity can be also affected negatively by preconditions, including obesity, diabetes, hypertension and advanced age, as well as by the gender. To help cancer patients suffering from COVID-19 and the other preconditions as soon as possible, it will be necessary to repurpose existing and well tolerated drugs - alone or in combination. To accelerate this process, we propose to develop an in silico systems biology approach to model the known biology of SARS-CoV-2 infection and the action of approved drugs overlaid on the underlying pathophysiology of cancer patients with different disease states, preconditions and gender. The proposed mathematical framework will mechanistically model the COVID-19 progression in the context of cancer. We will also simulate the effect of COVID-19 in this patient population and explore the efficacy of various treatment regimens to identify synergistic combinations as well as optimal schedules for therapy. Robust model validation will be performed using data from the Massachusetts General Hospital patient database (host of outgoing phase). This is a very timely research because the proposed mechanism-based model will reveal novel strategies to optimally combine current and emerging treatments for COVID-19 in cancer. Importantly, the proposed model will not be limited to COVID-19 but it will set a mathematical framework for the optimal treatment of cancer patients contracted by any infectious diseases. The fellowship will allow the applicant to substantially built upon his previous experience and strengthen his overall scientific abilities. In particular, he will expand his knowledge in tumor/virus biology, cancer research and clinical translation, will enrich his mathematical modelling capabilities and the analysis of complex biological systems that involve more than one medical conditions.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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MSCA-IF - Marie Skłodowska-Curie Individual Fellowships (IF)

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) H2020-MSCA-IF-2020

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Coordinator

UNIVERSITY OF CYPRUS
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.

€ 256 236,48
Address
AVENUE PANEPISTIMIOU 2109 AGLANTZI
1678 Nicosia
Cyprus

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Region
Κύπρος Κύπρος Κύπρος
Activity type
Higher or Secondary Education Establishments
Links
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.

€ 256 236,48

Partners (1)

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