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MAGnetic In-silico CAncer Treatment (MAGICAT): Advanced models of magnetic hyperthermia

Objective

Magnetic nanoparticles show promising perspectives for an increasing number of biomedical applications, in particular magnetic hyperthermia, which is proposed as a non-invasive method for cancer therapy. The advances are limited by the complex behaviour of nanoparticles inside biological environments and the lack of sophisticated theoretical tools to tackle the problem.
The project goal is to develop an advanced theoretical and computational model to investigate the basis of magnetic hyperthermia and provide tools for personalised therapy optimisation. The model will use state of the art techniques in theoretical magnetism and thermodynamics to describe, in a self-consistent way, the heat generation and transport inside and around the tumour. The new theoretical framework will
allow quantifying the heat generated by each individual particle at nanosecond resolution.
This will include the case of large particle assembles, where inter-particle interaction play a crucial role. The short time scale (nanoseconds) required by the fundamental aspect of the problem will be coupled with the large time scale (minutes/hours) required for the treatments by using a multiscale approach. To mimic the physical conditions of magnetic nanopaticles inside real tumour tissues, particles/tumour spatial configuration and properties will be based on experimental data.
The model will be validated through an extensive collaboration with leading experimental groups.
The final goal is to develop a publicly available documented software which can be used by the research community for basic theoretical studies, understanding of experiments, and as a tool for hyperthermia optimisation.

Coordinator

AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
Net EU contribution
€ 181 152,96
Address
Calle Serrano 117
28006 Madrid
Spain

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Region
Comunidad de Madrid Comunidad de Madrid Madrid
Activity type
Research Organisations
Non-EU contribution
No data