In the realm of oncology, the development of innovative cancer treatments, such as immunotherapy, gene therapies, targeted therapies, nanomedicine, and oncolytic virotherapy, heralds a promising frontier for enhancing patient outcomes. These treatments focus on selectively targeting not only the cancer cells but also the neighboring cells in the tumor microenvironment, thus potentially increasing the efficacy of cancer care. Utilizing mathematical modeling, oncologists and researchers gain tools to dissect the complicated interactions between these novel therapies and tumor responses. This method allows for the simulation and optimization of treatment strategies while highlighting potential delivery challenges—key steps toward more effective cancer interventions.

This Research Topic aims to deepen the understanding of how mathematical modeling can serve as a pivotal tool in the evolution of cancer treatment. Specific goals include optimizing existing treatment strategies, closely examining the dynamics of emerging therapies, elucidating the impact of these treatments on tumor growth, and predicting responses to different treatment modalities. Through various modeling techniques, such as Ordinary Differential Equations (ODEs) and agent-based modeling, this topic seeks to illuminate the intricate mechanisms of action of these therapies and facilitate the development of more refined treatment protocols.

The scope of this topic is broad yet clearly defined, aimed at extending the boundaries of current cancer treatment models. Specifically, we invite contributions that:

- Develop and simulate mathematical models to predict treatment efficacy.
- Explore inter-treatment interactions within a mathematical framework.
- Analyze the influence of the tumor microenvironment on treatment outcomes.
- Optimize treatment schedules and dosage plans.
- Construct and validate models that predict outcomes of combination therapies.

Moreover, we encourage submissions focusing on:

- Robust model validation methods and precise parameter estimation.
- Utilization of models in clinical or virtual trials.
- Strategies for integrating various treatment modalities.

By delving into these areas, the research aims to foster interdisciplinary collaborative efforts, driving forward the translation of cutting-edge treatments from theoretical models to clinical application, ultimately enhancing patient care in oncology.

Are you interested in contributing a manuscript to this Research Topic?

Quantitative Insights into New Cancer Therapies: A Mathematical Modeling Approach