Computational challenges of tumor spheroid modeling

TL;DR

This paper reviews a computational approach for modeling large tumor spheroids, addressing computational challenges, validating with experiments, and exploring tumor growth and treatment optimization.

Contribution

It introduces a scalable, validated numerical model for tumor spheroids, offering new insights into tumor growth and treatment strategies.

Findings

Model effectively simulates tumor growth in various environments

Validation with experimental data supports model accuracy

Provides new methods to optimize anti-tumor treatments

Abstract

The speed and the versatility of today's computers open up new opportunities to simulate complex biological systems. Here we review a computational approach recently proposed by us to model large tumor cell populations and spheroids, and we put forward general considerations that apply to any fine-grained numerical model of tumors. We discuss ways to bypass computational limitations and discuss our incremental approach, where each step is validated by experimental observations on a quantitative basis. We present a few results on the growth of tumor cells in closed and open environments and of tumor spheroids. This study suggests new ways to explore the initial growth phase of solid tumors and to optimize anti-tumor treatments.