Chareyron S, Alamir M
CNRS/GIPSA-Lab/University of Grenoble, BP 46, Domaine Universitaire, rue de la Houille Blanche, 38400 Saint Martin d'Hères, France.
J Theor Biol. 2009 Jun 7;258(3):444-54. doi: 10.1016/j.jtbi.2008.07.002. Epub 2008 Jul 5.
In this paper, a recently developed model governing the cancer growth on a cell population level with combination of immune and chemotherapy is used to develop a reactive (feedback) mixed treatment strategy. The feedback design proposed here is based on nonlinear constrained model predictive control together with an adaptation scheme that enables the effects of unavoidable modeling uncertainties to be compensated. The effectiveness of the proposed strategy is shown under realistic human data showing the advantage of treatment in feedback form as well as the relevance of the adaptation strategy in handling uncertainties and modeling errors. A new treatment strategy defined by an original optimal control problem formulation is also proposed. This new formulation shows particularly interesting possibilities since it may lead to tumor regression under better health indicator profile.
在本文中，一个最近开发的、在细胞群体水平上结合免疫和化疗来控制癌症生长的模型被用于制定一种反应式（反馈）混合治疗策略。这里提出的反馈设计基于非线性约束模型预测控制以及一种自适应方案，该方案能够补偿不可避免的建模不确定性的影响。在实际人体数据下展示了所提策略的有效性，显示了反馈形式治疗的优势以及自适应策略在处理不确定性和建模误差方面的相关性。还提出了一种由原始最优控制问题公式定义的新治疗策略。这种新公式显示出特别有趣的可能性，因为它可能在更好的健康指标状况下导致肿瘤消退。
