Kim Munju, Gillies Robert J, Rejniak Katarzyna A
Integrated Mathematical Oncology, H. Lee Moffitt Cancer Center and Research Institute , Tampa, FL , USA.
Front Oncol. 2013 Nov 18;3:278. doi: 10.3389/fonc.2013.00278.
Delivery of anti-cancer drugs to tumor tissues, including their interstitial transport and cellular uptake, is a complex process involving various biochemical, mechanical, and biophysical factors. Mathematical modeling provides a means through which to understand this complexity better, as well as to examine interactions between contributing components in a systematic way via computational simulations and quantitative analyses. In this review, we present the current state of mathematical modeling approaches that address phenomena related to drug delivery. We describe how various types of models were used to predict spatio-temporal distributions of drugs within the tumor tissue, to simulate different ways to overcome barriers to drug transport, or to optimize treatment schedules. Finally, we discuss how integration of mathematical modeling with experimental or clinical data can provide better tools to understand the drug delivery process, in particular to examine the specific tissue- or compound-related factors that limit drug penetration through tumors. Such tools will be important in designing new chemotherapy targets and optimal treatment strategies, as well as in developing non-invasive diagnosis to monitor treatment response and detect tumor recurrence.
将抗癌药物递送至肿瘤组织,包括其在间质中的转运和细胞摄取,是一个复杂的过程,涉及多种生化、机械和生物物理因素。数学建模提供了一种方法,通过该方法可以更好地理解这种复杂性,并通过计算模拟和定量分析系统地研究各促成因素之间的相互作用。在本综述中,我们介绍了用于解决与药物递送相关现象的数学建模方法的现状。我们描述了如何使用各种类型的模型来预测肿瘤组织内药物的时空分布,模拟克服药物转运障碍的不同方法,或优化治疗方案。最后,我们讨论了数学建模与实验或临床数据的整合如何能够提供更好的工具来理解药物递送过程,特别是研究限制药物穿透肿瘤的特定组织或化合物相关因素。此类工具对于设计新的化疗靶点和优化治疗策略,以及开发用于监测治疗反应和检测肿瘤复发的非侵入性诊断方法都将非常重要。