Modeling of drug delivery by modifying tumor microenvironment
| dc.contributor | Ph.D. Program in Physics. | |
| dc.contributor.advisor | Ünlü, Mehmet Burçin. | |
| dc.contributor.author | Yılmaz, Defne. | |
| dc.date.accessioned | 2025-04-14T12:52:09Z | |
| dc.date.available | 2025-04-14T12:52:09Z | |
| dc.date.issued | 2023 | |
| dc.description.abstract | The tumor microenvironment is a critical aspect in the formation and progression of tumors. Its complex nature is commonly distinguished by abnormal vascular structure and tumor-induced states, including hypoxia, elevated interstitial pressure, and acidity. The tumor microenvironment has a significant impact on the effectiveness of anticancer treatments, so it is crucial to adopt strategies in cancer research that target tumor microenvironment features. In this regard, to study the therapeutic strategies targeting the tumor microenvironment, a mathematical modeling approach is utilized here to incorporate vascular tumor growth and response to treatments. The spatiotemporal model captures the tumor cell growth, vasculature, and oxygenation, along with drug treatments. The effects of drugs targeting hypoxia, an important feature of the tumor microenvironment, are investigated when given in combination with chemotherapy drugs. Different scheduling and sequencing are applied, and the tumor response to these various cases is examined. In addition, to examine the response of the tumor to chemotherapy treatment, a deep learning approach is employed, and a response prediction model is presented. The model includes tumor growth and drug response behaviors. The goal of the presented model is to represent the tumor response behavior according to the ongoing treatment schedule. The model predicts future tumor microenvironment maps using drug scalars and tumor microenvironment channels as inputs, which might aid in determining the optimum schedule and dosages of combination therapy for patients. | |
| dc.format.pages | xiv, 108 leaves | |
| dc.identifier.other | Ph.D. Program in Physics. TKL 2023 U68 PhD (Thes TR 2023 L43 | |
| dc.identifier.uri | https://digitalarchive.library.bogazici.edu.tr/handle/123456789/21566 | |
| dc.publisher | Thesis (Ph.D.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2023. | |
| dc.subject.lcsh | Tumors -- Molecular aspects. | |
| dc.subject.lcsh | Drug delivery systems. | |
| dc.title | Modeling of drug delivery by modifying tumor microenvironment |
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