The landscape of cancer treatment is rapidly evolving, with the emergence of multiple, novel therapies, including immunotherapy, gene therapies, targeted therapies, nanomedicine, and oncolytic virotherapy. These innovative approaches hold great promise for improving patient outcomes by selectively targeting either cancer cells or other cells in the tumor microenvironment. Mathematical modeling offers a valuable framework to unravel the complex interplay between these emerging therapies and tumor response. By employing mathematical models and computational simulations, researchers can explore the dynamics, optimize treatment strategies, and identify potential challenges in their delivery, ultimately paving the way for enhanced cancer care. This Research Topic aims to delve into the realm of mathematical modeling to advance our understanding of emerging cancer treatments, such as oncolytic virotherapy, and their combination with other treatment modalities. By investigating how different treatments interact, we aim to identify synergistic effects, optimize treatment regimens and, in the longer term, to identify strategies for improving patient outcomes in the fight against cancer.
This Research Topic aims to explore the application of mathematical modeling in the field of emerging cancer therapies. The objective is to address challenges associated with optimizing treatment strategies, understanding the dynamics of novel therapies, elucidating their impact on tumor growth, and predicting treatment response. By employing a variety of different modeling approaches, this special issue seeks to provide insights into the complex interplay between emerging cancer therapies, contributing to the development of effective treatment strategies and improved patient outcomes. Contributions that utilize mathematical and computational modeling approaches to enhance our understanding of the dynamics and efficacy of emerging cancer therapies are encouraged.
This Research Topic invites contributions on mathematical modeling in the context of emerging cancer therapies. We seek research articles, reviews, perspectives, and computational studies utilizing diverse mathematical modeling approaches, including ODEs, PDEs, data-driven modeling, agent-based models, network models, stochastic models, and more.
The scope encompasses:
(1) Developing and simulating mathematical models to predict treatment efficacy,
(2) Investigating treatment interactions using mathematical frameworks,
(3) Analyzing the impact of the tumor microenvironment on outcomes through mathematical modeling,
(4) Optimizing treatment schedules and dosing regimens using mathematical techniques,
(5) Generating predictive models for combination therapy outcomes and understanding synergistic interactions.
Additionally, we encourage contributions on:
(6) Model validation and parameter estimation,
(7) Clinical/virtual trials assessing the utility of mathematical models, and
(8) The development and evaluation of combination cancer treatment strategies.
Our aim is to foster interdisciplinary collaboration and advance the understanding and translation of emerging cancer therapies.
Keywords:
Mathematical modeling, Emerging cancer therapies, Synergistic interactions, Treatment optimization, Combination therapies, Tumor dynamics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
The landscape of cancer treatment is rapidly evolving, with the emergence of multiple, novel therapies, including immunotherapy, gene therapies, targeted therapies, nanomedicine, and oncolytic virotherapy. These innovative approaches hold great promise for improving patient outcomes by selectively targeting either cancer cells or other cells in the tumor microenvironment. Mathematical modeling offers a valuable framework to unravel the complex interplay between these emerging therapies and tumor response. By employing mathematical models and computational simulations, researchers can explore the dynamics, optimize treatment strategies, and identify potential challenges in their delivery, ultimately paving the way for enhanced cancer care. This Research Topic aims to delve into the realm of mathematical modeling to advance our understanding of emerging cancer treatments, such as oncolytic virotherapy, and their combination with other treatment modalities. By investigating how different treatments interact, we aim to identify synergistic effects, optimize treatment regimens and, in the longer term, to identify strategies for improving patient outcomes in the fight against cancer.
This Research Topic aims to explore the application of mathematical modeling in the field of emerging cancer therapies. The objective is to address challenges associated with optimizing treatment strategies, understanding the dynamics of novel therapies, elucidating their impact on tumor growth, and predicting treatment response. By employing a variety of different modeling approaches, this special issue seeks to provide insights into the complex interplay between emerging cancer therapies, contributing to the development of effective treatment strategies and improved patient outcomes. Contributions that utilize mathematical and computational modeling approaches to enhance our understanding of the dynamics and efficacy of emerging cancer therapies are encouraged.
This Research Topic invites contributions on mathematical modeling in the context of emerging cancer therapies. We seek research articles, reviews, perspectives, and computational studies utilizing diverse mathematical modeling approaches, including ODEs, PDEs, data-driven modeling, agent-based models, network models, stochastic models, and more.
The scope encompasses:
(1) Developing and simulating mathematical models to predict treatment efficacy,
(2) Investigating treatment interactions using mathematical frameworks,
(3) Analyzing the impact of the tumor microenvironment on outcomes through mathematical modeling,
(4) Optimizing treatment schedules and dosing regimens using mathematical techniques,
(5) Generating predictive models for combination therapy outcomes and understanding synergistic interactions.
Additionally, we encourage contributions on:
(6) Model validation and parameter estimation,
(7) Clinical/virtual trials assessing the utility of mathematical models, and
(8) The development and evaluation of combination cancer treatment strategies.
Our aim is to foster interdisciplinary collaboration and advance the understanding and translation of emerging cancer therapies.
Keywords:
Mathematical modeling, Emerging cancer therapies, Synergistic interactions, Treatment optimization, Combination therapies, Tumor dynamics
Important Note:
All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.