Core 1: Mathematical Core

核心 1：数学核心

基本信息

批准号：
10730408
负责人：
Alexander Robertson Allan Anderson
金额：
$ 40.61万
依托单位：
H. LEE MOFFITT CANCER CTR & RES INST
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-09-15 至 2028-08-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10730408
关键词：
Animals Basic Science Blood Blood Vessels Bone Tissue Breast Calibration Cancer Center Clinical Clinical Data Clinical Trials Complex Computer Models Connective Tissue Data Data Collection Development Differential Equation Disease Ecology Evolution Faculty Goals Heterogeneity Histology Human Hybrids Immune In Vitro Link Logic Lung Malignant Neoplasms Malignant neoplasm of lung Maps Mathematics Metabolism Methods Modeling Mus Non-Small-Cell Lung Carcinoma Oncology Pathway interactions Patients Phenotype Play Preclinical Testing Process Prostate Regimen Resolution Science Services Skin Stromal Neoplasm Testing Tissues Tumor Burden Uncertainty Work body system brain tissue cancer cell cancer therapy cancer type cell type clinical investigation cohort data integration dynamic system flexibility in vivo innovation insight mathematical model member molecular dynamics molecular scale multidisciplinary novel phase I trial pre-clinical programs sarcoma theories tool treatment optimization treatment response treatment strategy tumor tumor growth tumor initiation tumor microenvironment virtual virtual patient

项目摘要

Summary – Mathematical Modeling Core Understanding the changes in tumor ecology (“∆-Ecology”) that occur during tumor initiation, progression, and therapy requires careful study of a complex dynamical system involving multiple scales – from molecular to cellular to tissue to systemic. An important tool in this study is the use of mathematical models, which can bridge temporal gaps in clinical and experimental data. Ecological histology data from patients is difficult and rare to obtain, and experimental work, while crucial for teasing apart mechanism and testing hypotheses, cannot fully reproduce the human setting of disease. Mathematical modeling serves as a link between these approaches, allowing ecological principles arising from mechanisms studied in vitro and in vivo to play out in the patient setting, calibrated to available patient data. The Mathematical Modeling Core will develop these models, using a variety of approaches. Key is the use of spatial agent-based models, which can handle the rich diversity of cell types and molecules, as well as the multiple scales involved in tumor ecology and evolution. We have built a platform for developing these models that is fast and flexible, including numerous add-ons that will serve the science in the two projects of this proposal. In addition, our expertise in non-spatial models will be applied in parallel, as these approaches can capture the broad dynamics of tumor growth and the response to treatment in ways that have significant translatable potential, as evidenced by ongoing trials in Evolutionary Therapy at Moffitt. In addition to constructing these models, we will develop tools for initializing, calibrating, and analyzing models based on clinical and pre-clinical data collected in each project. This will involve the use of virtual “Phase i” trials, where virtual patients/mice are generated from a model, taking parameter uncertainty into account. In summary, the Core models will provide insight into the ecological processes that occur during tumor growth and treatment.

摘要 - 数学建模核心了解在肿瘤开始，进展和治疗需要仔细研究一个复杂的动态系统，该系统涉及多个尺度 - 从分子到细胞到组织到全身。这项研究的一个重要工具是使用数学模型，可以桥梁临床和实验数据中的临时缝隙。来自患者的生态组织学数据很困难，并且很少能获得和实验性工作，同时对于嘲笑机制和测试假设至关重要，但无法完全重现疾病的人类环境。数学建模是这些之间的链接方法，允许在体外研究的机制和体内发挥作用的生态原理患者设置，校准可用的患者数据。数学建模核心将开发这些模型，使用多种方法。关键是使用基于空间代理的模型，该模型可以处理细胞类型和分子的多样性以及肿瘤生态学涉及的多个尺度和进化。我们已经建立了一个平台，用于开发这些模型快速，灵活，包括许多将在本提案的两个项目中为科学服务的附加组件。此外，我们在非空间方面的专业知识模型将同时应用，因为这些方法可以捕获肿瘤生长的广泛动态和以具有巨大转换潜力的方式对治疗的反应，如正在进行的试验中所证明的莫菲特的进化疗法。除了构建这些模型外，我们还将开发用于初始化的工具根据每个项目中收集的临床和临床前数据进行校准和分析模型。这会涉及使用虚拟“ I期”试验，该试验是通过模型产生的虚拟患者/小鼠的使用参数不确定性。总而言之，核心模型将为生态学提供洞察力肿瘤生长和治疗过程中发生的过程。