近年來對於癌症的治療，無非是手術治療、放射性治療及藥物治療。而就藥物治療來說，當癌症發展至遠端轉移期，通常只能以藥物控制來延長患者的生命。一個新療程的發展，常伴隨曠日廢時的臨床實驗。我們提出一種賽局的模型，可以模擬藥物及癌細胞間的拮抗關係，藉由解決最佳化控制問題得到癌細胞的變化趨勢。導入藥物基因敏感度資料庫及癌症基因的網路，模擬癌細胞的抗藥機制，使該模型能體現臨床的化療報告。由單一藥物固定療程的報告及模型調整參數及權重，並以此為基礎構築雙藥物療程之模型，最後比較固定投藥策略及動態投藥的療效及差別。本實驗將著重在遠端轉移期的乳癌上，且以藥物Gemcitabine (健擇) 及 Paclitaxel (太平洋紫杉醇) 的單一及組合療程作為對象。

Now a day, we have surgery, radiation therapy and chemical drug therapy for cancer treatment. For metastatic cancer, we only have chemical therapy to prolong the life of patients. Trials for new drug therapies often take lots of time. We introduce a game model, that simulate the reaction between drug and tumor cell. We can get the trend of the tumor cell and the best strategy of drug dosage by solving this optimal problem. We also simulate the resistance mechanism of the tumor cell by introducing drug sensitivity database and cancer genes interaction network. With available trial reports, we can verify our model and make a comparison of static and dynamic dual drug strategies.
In this thesis, we focus our experiment on Gemcitabine Paclitaxel combination therapy.

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