Stochastic modeling of cyclic cancer treatments under common noise
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arXiv
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866912160163037184 |
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| author | Sonith, Jason |
| author_facet | Sonith, Jason |
| contents | Path integral control is an effective method in cancer drug treatment, providing a structured approach to handle the complexities and unpredictability of tumor behavior. Utilizing mathematical principles from physics, this technique optimizes drug delivery in environments influenced by randomness. It takes into account the intricate interactions between cancer cells, healthy tissues, and the immune system, as well as factors such as patient-specific characteristics and tumor diversity. Path integral control offers tailored solutions to these issues, enabling the design of drug dosing regimens that enhance therapeutic effectiveness while minimizing side effects. Its flexibility makes it a valuable tool in creating personalized, precision-driven therapies, ultimately improving patient outcomes in cancer treatment. In this paper we give a review about the current status of path integral control in cancer research. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_13201 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Stochastic modeling of cyclic cancer treatments under common noise Sonith, Jason Tissues and Organs Optimization and Control 93E20 93E20, 91A15, 49N80 Path integral control is an effective method in cancer drug treatment, providing a structured approach to handle the complexities and unpredictability of tumor behavior. Utilizing mathematical principles from physics, this technique optimizes drug delivery in environments influenced by randomness. It takes into account the intricate interactions between cancer cells, healthy tissues, and the immune system, as well as factors such as patient-specific characteristics and tumor diversity. Path integral control offers tailored solutions to these issues, enabling the design of drug dosing regimens that enhance therapeutic effectiveness while minimizing side effects. Its flexibility makes it a valuable tool in creating personalized, precision-driven therapies, ultimately improving patient outcomes in cancer treatment. In this paper we give a review about the current status of path integral control in cancer research. |
| title | Stochastic modeling of cyclic cancer treatments under common noise |
| topic | Tissues and Organs Optimization and Control 93E20 93E20, 91A15, 49N80 |
| url | https://arxiv.org/abs/2412.13201 |