Modeling Tumor Growth: A Simple Individual-Based Model and Its Analysis

Kozitsky, Yuri; Pilorz, Krzysztof

doi:10.1142/9789811216220_0005

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2021

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“…We begin by making a brief summary of the aspects of the theory presented here, understandable also for non-mathematicians, see also [8] for an extended explanations and analysis. Then, we discuss some aspects of this work, as well as outline its possible continuation.…”

Section: Summary and Concluding Remarksmentioning

confidence: 99%

Stochastic branching at the edge: individual-based modeling of tumor cell proliferation

Kozitsky

2021

J. Evol. Equ.

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An individual-based model of stochastic branching is proposed and studied, in which point particles drift in $$\bar{\mathbb {R}}_{+}:=[0,+\infty )$$ R ¯ + : = [ 0 , + ∞ ) toward the origin (edge) with unit speed, where each of them splits into two particles that instantly appear in $$\bar{\mathbb {R}}_{+}$$ R ¯ + at random positions. During their drift, the particles are subject to a random disappearance (death). The model is intended to capture the main features of the proliferation of tumor cells, in which trait $$x\in \bar{\mathbb {R}}_{+}$$ x ∈ R ¯ + of a given cell is time to its division and the death is caused by therapeutic factors. The main result of the paper is proving the existence of an honest evolution of this kind and finding a condition that involves the death rate and cell cycle distribution parameters, under which the mean size of the population remains bounded in time.

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Section: Summary and Concluding Remarksmentioning

confidence: 99%