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Multi objective optimization of drug regimens in cancer chemotherapy using a PK-PD model

机译:使用PK-PD模型对癌症化疗药物方案进行多目标优化

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Mathematical modeling and methods from control theory are employed to optimize drug regimens in cancer chemotherapy. In this paper, we utilized a PK-PD model to describe the effects of drugs on the tumor cells. In chemotherapy, it is essential to prescribe the drug dosages in a way that the number of cancer cells decreases while the least side effects are imposed to the patient. So, the consideration of simultaneous drug effects on both cancer and healthy cells (in this paper white blood cells) in an optimal drug regimen is necessary. Therefore, we have considered two cost functions to minimize the area under curve of tumors as well as the side effects on the patient during chemotherapy. Using these cost functions the drug regimens are calculated with the multi objective optimization (MOO) method. Thereafter, the best drug regimen from the set of these optimal regimens can be appropriately selected by oncologists according to the specific conditions of the patient. Numerical simulations are given to illustrate the flexibility of the proposed method.
机译:采用控制理论的数学模型和方法来优化癌症化疗中的药物治疗方案。在本文中,我们利用PK-PD模型来描述药物对肿瘤细胞的作用。在化学疗法中,必须以减少癌细胞数量而对患者产生最小副作用的方式开具药物剂量。因此,有必要在最佳药物治疗方案中同时考虑药物对癌症和健康细胞(在本文中为白细胞)的影响。因此,我们考虑了两个成本函数,以最小化肿瘤曲线下的面积以及化疗期间对患者的副作用。使用这些成本函数,可以通过多目标优化(MOO)方法计算药物治疗方案。此后,肿瘤科医生可以根据患者的具体情况从这些最佳方案中选择最佳药物方案。数值仿真表明了该方法的灵活性。

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