Mathematical models of Leukaemia and its treatment: A review

TL;DR

This review summarizes current mathematical models of leukemia growth and treatment response, highlighting methodologies, biological factors, and key conclusions to aid future research in mathematical oncology.

Contribution

It compiles and analyzes the state-of-the-art mathematical models of leukemia, providing a comprehensive background for advancing mathematical biology in oncology.

Findings

Various mathematical approaches are used to model leukemia dynamics.

Models incorporate biological factors like cell proliferation and treatment effects.

The review identifies gaps and future directions in leukemia modeling.

Abstract

Leukaemia accounts for around 3% of all cancer types diagnosed in adults, and is the most common type of cancer in children of paediatric age. There is increasing interest in the use of mathematical models in oncology to draw inferences and make predictions, providing a complementary picture to experimental biomedical models. In this paper we recapitulate the state of the art of mathematical modelling of leukaemia growth dynamics, in time and response to treatment. We intend to describe the mathematical methodologies, the biological aspects taken into account in the modelling, and the conclusions of each study. This review is intended to provide researchers in the field with solid background material, in order to achieve further breakthroughs in the promising field of mathematical biology.