Integrated Mathematical Oncology Department, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Department of Oncologic Sciences, Morsani College of Medicine, University of South Florida, Tampa, FL, USA.
Bull Math Biol. 2019 Sep;81(9):3623-3641. doi: 10.1007/s11538-018-0402-x. Epub 2018 Feb 8.
Systemic chemotherapy is one of the main anticancer treatments used for most kinds of clinically diagnosed tumors. However, the efficacy of these drugs can be hampered by the physical attributes of the tumor tissue, such as tortuous vasculature, dense and fibrous extracellular matrix, irregular cellular architecture, tumor metabolic gradients, and non-uniform expression of the cell membrane receptors. This can impede the transport of therapeutic agents to tumor cells in sufficient quantities. In addition, tumor microenvironments undergo dynamic spatio-temporal changes during tumor progression and treatment, which can also obstruct drug efficacy. To examine ways to improve drug delivery on a cell-to-tissue scale (single-cell pharmacology), we developed the microscale pharmacokinetics/pharmacodynamics (microPKPD) modeling framework. Our model is modular and can be adjusted to include only the mathematical equations that are crucial for a biological problem under consideration. This modularity makes the model applicable to a broad range of pharmacological cases. As an illustration, we present two specific applications of the microPKPD methodology that help to identify optimal drug properties. The hypoxia-activated drugs example uses continuous drug concentrations, diffusive-advective transport through the tumor interstitium, and passive transmembrane drug uptake. The targeted therapy example represents drug molecules as discrete particles that move by diffusion and actively bind to cell receptors. The proposed modeling approach takes into account the explicit tumor tissue morphology, its metabolic landscape and/or specific receptor distribution. All these tumor attributes can be assessed from patients' diagnostic biopsies; thus, the proposed methodology can be developed into a tool suitable for personalized medicine, such as neoadjuvant chemotherapy.
系统化疗是用于大多数临床诊断肿瘤的主要抗癌治疗方法之一。然而,这些药物的疗效可能会受到肿瘤组织的物理特性的阻碍,例如曲折的脉管系统、密集的纤维细胞外基质、不规则的细胞结构、肿瘤代谢梯度和细胞膜受体的不均匀表达。这会阻碍治疗剂以足够的数量输送到肿瘤细胞。此外,肿瘤微环境在肿瘤进展和治疗过程中会发生动态时空变化,这也会阻碍药物疗效。为了研究如何在细胞到组织的尺度上提高药物输送(单细胞药理学),我们开发了微尺度药代动力学/药效学(microPKPD)建模框架。我们的模型是模块化的,可以调整为仅包含考虑的生物学问题的关键数学方程。这种模块化使模型适用于广泛的药理学情况。作为说明,我们提出了 microPKPD 方法的两个具体应用,以帮助确定最佳药物特性。缺氧激活药物的例子使用连续的药物浓度、通过肿瘤间质的扩散和对流运输以及被动的跨膜药物摄取。靶向治疗的例子将药物分子表示为离散的粒子,通过扩散移动并主动与细胞受体结合。所提出的建模方法考虑了明确的肿瘤组织形态、其代谢景观和/或特定受体分布。所有这些肿瘤属性都可以从患者的诊断活检中评估;因此,所提出的方法可以发展成为适合个性化医疗的工具,例如新辅助化疗。