Mathematical Modeling of Leukemia Chemotherapy in Bone Marrow

TL;DR

This paper develops a mathematical model to simulate leukemia cell dynamics in bone marrow, aiming to predict relapse risk and improve treatment strategies for pediatric ALL patients.

Contribution

It introduces a novel mathematical model linking treatment response with relapse risk, providing a virtual platform for studying leukemia progression and treatment effects.

Findings

Model simulates leukemia cell behavior without treatment

Relapse risk correlates with initial treatment response

Provides a basis for future treatment optimization

Abstract

Acute Lymphoblastic Leukemia (ALL) accounts for the 80% of leukemias when coming down to pediatric ages. Survival of these patients has increased by a considerable amount in recent years. However, around 15-20% of treatments are unsuccessful. For this reason, it is definitely required to come up with new strategies to study and select which patients are at higher risk of relapse. Thus the importance to monitor the amount of leukemic cells to predict relapses in the first treatment phase. In this work we develop a mathematical model describing the behavior of ALL, examining the evolution of a leukemic clone when treatment is applied. In the study of this model it can be observed how the risk of relapse is connected with the response in the first treatment phase. This model is able to simulate cell dynamics without treatment, representing a virtual patient bone marrow behavior. Furthermore, several parameters are related to treatment dynamics, therefore proposing a basis for future works regarding childhood ALL survival improvement.