Document Type
Honors Thesis
Abstract
According to the American Cancer Society, colon cancer is the third leading cause of cancer-related deaths amongst men and women. A data-driven Quantitative and Systems Pharmacology model is used to provide treatment for each individual patient using gene expression data from primary tumor samples. Using uncertainty and sensitivity analysis, a prediction of the efficacy of a personal treatment could be obtained. A Latin hypercube sampling-partial rank correlation method, using a Normal distribution, was used to conduct the sensitivity analysis. It was found that the most sensitive parameter was the day-1 of cancer. This assists researchers to suggest an optimal treatment strategy for each colon cancer patient and predict the efficacy of the proposed treatment.
Publication Date
5-1-2021
Language
English
License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.
Recommended Citation
Villegas, Juan, "SENSITIVITY ANALYSIS AND MATHEMATICAL MODELING FOR TAILORED COLON CANCER TREATMENT" (2021). 2021 Spring Honors Capstone Projects. 60.
https://mavmatrix.uta.edu/honors_spring2021/60