Recently, a growing interest in reproducing biological phenomena by in silico models has been registered. In this framework, the present work is inspired by new advancements in Organs-on-chip technology and, in particular, in Cancer-on-chip experiment, where tumor cells are treated with chemotherapy drugs and secrete chemical signals in the environment thus stimulating immune response. Here we present a scenario-based study realized by a simulation algorithm based on a hybrid model consisting of a coupled PDE–ODE system describing the concentration of chemicals as well as immune cells migration in the Cancer-on-chip environment. The main goal of this work is to investigate numerically the qualitative effects on the overall dynamics of immune cells given by coefficients regulating cell alignment, growth rate and inflow of chemicals. To this aim, some simulated scenarios obtained by varying the values of corresponding model parameters are presented.

A Scenario-Based Study on Hybrid PDE-ODE Model for Cancer-on-Chip Experiment

Menci M.;
2024-01-01

Abstract

Recently, a growing interest in reproducing biological phenomena by in silico models has been registered. In this framework, the present work is inspired by new advancements in Organs-on-chip technology and, in particular, in Cancer-on-chip experiment, where tumor cells are treated with chemotherapy drugs and secrete chemical signals in the environment thus stimulating immune response. Here we present a scenario-based study realized by a simulation algorithm based on a hybrid model consisting of a coupled PDE–ODE system describing the concentration of chemicals as well as immune cells migration in the Cancer-on-chip environment. The main goal of this work is to investigate numerically the qualitative effects on the overall dynamics of immune cells given by coefficients regulating cell alignment, growth rate and inflow of chemicals. To this aim, some simulated scenarios obtained by varying the values of corresponding model parameters are presented.
2024
9783031607721
9783031607738
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12610/83044
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