# Addressing current challenges in cancer immunotherapy with mathematical and computational modeling

## TL;DR

This review discusses how mathematical and computational models are used to address key challenges in cancer immunotherapy, including tumor classification, treatment scheduling, and combination therapies, to improve therapy design.

## Contribution

It provides a comprehensive survey of modeling approaches tailored to immunotherapy challenges, highlighting recent advances and future directions.

## Key findings

- Models have become more complex with biological data integration.
- Analytical and numerical methods aid in therapy optimization.
- Modeling supports rational design of combination treatments.

## Abstract

The goal of cancer immunotherapy is to boost a patient's immune response to a tumor. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumor microenvironment, immune-modulating effects of conventional treatments, and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modeling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumor classification, optimal treatment scheduling, and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modelers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumor-immune biology. We conclude the review with recommendations for modelers both with respect to methodology and biological direction that might help keep modelers at the forefront of cancer immunotherapy development.