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CancerCOtreat

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Optimizing treatment of cancer patients infected with COVID 19 and other precond...

Optimizing treatment of cancer patients infected with COVID 19 and other preconditions using mathematical modelling 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, diabe... ver más

30/04/2024

UCY

256K€

Presupuesto del proyecto: 256K€

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Fecha límite participación Sin fecha límite de participación.

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Financiación concedida El organismo H2020 notifico la concesión del proyecto el día 2024-04-30

MSCA-IF-2020: Individual Fellowships Objective:The goal of the Individual Fellowships is to enhance the creative and innovative potential...

I+D

Cerrada hace 4 años

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Este proyecto no cuenta con búsquedas de partenariado abiertas en este momento.

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No hay información privada compartida para este proyecto. Habla con el coordinador.

3 Participantes

UCY

256.24K€ | Lider

THE GENERAL HOSPITAL CORPORA...

177.27K€ | Participante

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Duración del proyecto: 36 meses Fecha Inicio: 2021-04-13
Fecha Fin: 2024-04-30

Líder del proyecto

UNIVERSITY OF CYPRUS No se ha especificado una descripción o un objeto social para esta compañía.

TRL 4-5

Presupuesto del proyecto 256K€

Fecha límite de participación Sin fecha límite de participación.

Descripción del proyecto 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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