Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 30, 24 January 2024
Open
Access | Article
Research on the application of mathematical modeling in tumor immunology in the context of chemotherapy
* Author to whom correspondence should be addressed.
Abstract
Cancer is not only a highly detrimental disease but also a particularly grave health concern. Moreover, the current incidence and mortality rates in our country are far from encouraging, making the prevention and control situation very challenging. Therefore, identifying the most scientific and effective treatment methods has become one of our primary research focuses. This paper, building upon previous models and incorporating resistance factors, categorizes tumor cells into those that are sensitive to chemotherapy drugs and those that become resistant. Using MATLAB, we have adjusted various sensitivity parameters in the model to simulate the number of tumor cells over 40 days. This simulation aims to analyze the sensitivity levels of tumor cells to different parameters upon the inclusion of resistance factors. The initial data used for the simulation were derived from the original paper. Ultimately, our findings indicate that tumor cells are most sensitive to the chemotherapy drug’s killing rate for normal tumor cells and the decay rate of the chemotherapy drug. Due to the drug resistance factor, the sensitivity of different parameters is influenced. For parameters related to chemotherapy drugs, the final results, when incorporating this factor, may deviate significantly from those of previous models without this factor. For instance, the decay rate of chemotherapy drugs might result in a larger total number of tumor cells or a steeper trend compared to previous findings.
Keywords
Tumor, Chemotherapy, Drug-resisitence
References
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 3rd International Conference on Computing Innovation and Applied Physics
- ISBN (Print)
- 978-1-83558-283-1
- ISBN (Online)
- 978-1-83558-284-8
- Published Date
- 24 January 2024
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/30/20241043
- Copyright
- 24 January 2024
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited