Optimal Control of Immune Checkpoint Inhibitor Therapy in a Heart-Tumour Model

Autoimmune myocarditis, or cardiac muscle inflammation, is a rare but frequently fatal side-effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite the dangers that side-effects such as these pose to patients, they are rarely, if ever, included explicitly when mechanistic mathematical modelling of cancer therapy is used for optimization of treatment. In this paper, we develop a two-compartment mathematical model which incorporates the impact of ICIs on both the heart and the tumour. Such a model can be used to inform the conditions under which autoimmune myocarditis may develop as a consequence of treatment. We use this model in an optimal control framework to design optimized dosing schedules for three types of ICI therapy that balance the positive and negative effects of treatment. We show that including the negative side-effects of ICI treatment explicitly within the mathematical framework significantly impacts the predictions for the optimized dosing schedule, thus stressing the importance of a holistic approach to optimizing cancer therapy regimens.

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Publication Details

Journal
Bulletin of Mathematical Biology
Published
2025-08-11
DOI
https://doi.org/10.1007/s11538-025-01468-4
Citations
1
Primary Topic
Cancer Immunotherapy and Biomarkers
Type
article
Field-Weighted Citation Impact
1.05

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article

Optimal Control of Immune Checkpoint Inhibitor Therapy in a Heart-Tumour Model

Sarah L. Waters, Solveig A. van der Vegt, Ruth E. Baker
1 citations
Bulletin of Mathematical Biology
Cancer Immunotherapy and Biomarkers
1.05
article

Optimal Control of Immune Checkpoint Inhibitor Therapy in a Heart-Tumour Model

Sarah L. Waters, Solveig A. van der Vegt, Ruth E. Baker
article en
1 citations

Abstract

Autoimmune myocarditis, or cardiac muscle inflammation, is a rare but frequently fatal side-effect of immune checkpoint inhibitors (ICIs), a class of cancer therapies. Despite the dangers that side-effects such as these pose to patients, they are rarely, if ever, included explicitly when mechanistic mathematical modelling of cancer therapy is used for optimization of treatment. In this paper, we develop a two-compartment mathematical model which incorporates the impact of ICIs on both the heart and the tumour. Such a model can be used to inform the conditions under which autoimmune myocarditis may develop as a consequence of treatment. We use this model in an optimal control framework to design optimized dosing schedules for three types of ICI therapy that balance the positive and negative effects of treatment. We show that including the negative side-effects of ICI treatment explicitly within the mathematical framework significantly impacts the predictions for the optimized dosing schedule, thus stressing the importance of a holistic approach to optimizing cancer therapy regimens.

Bulletin of Mathematical BiologyVol. 87(9)
University of Oxford (GB), Mathematical Institute of the Slovak Academy of Sciences (SK)
Simons Foundation, Engineering and Physical Sciences Research Council
Good health and well-being
Openalex Percentile: Top 19%
Cancer Immunotherapy and Biomarkers
1.05
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