RUI: Collaborative Research: Optimal Control of Multi-Input Mathematical Models for Tumor Dynamics under Combination Therapies

RUI：合作研究：联合治疗下肿瘤动力学多输入数学模型的优化控制

• 批准号: 1008221
• 负责人: Urszula Ledzewicz
• 金额: $ 17.51万
• 依托单位: Southern Illinois University at Edwardsville
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2014-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1008221&HistoricalAwards=false
• 关键词: RUI; Collaborative; Research; Optimal; Control

One of the directions actively pursued in current cancer research is to combine traditional treatments like chemotherapy and radiotherapy with novel approaches such as anti-angiogenic treatment or immunotherapy in the hope of achieving synergistic effects. The underlying biological mechanisms of these novel approaches are not fully understood and several important questions including how to best schedule these therapies over time still need to be answered. The scheduling aspect becomes even more difficult and complex when several therapeutic agents are involved. For these combination therapies no medical guidelines are in place yet and mathematical modeling and analysis are able to give valuable insights into establishing robust and effective treatment protocols. Mathematical models for combination therapies are quite complex and, due to the various therapies pursued, are described by multi-input control systems. In this project, geometric methods from modern optimal control will be applied and developed as needed to analyze these systems when chemotherapy or radiotherapy are combined with anti-angiogenic treatments. Starting with simplified, but biologically validated models, increasingly more realistic medical features such as the pharmacokinetics of the agents and tumor immune system interactions will be incorporated. For these models unconventional mathematical structures arise that have not been analyzed in the context of biomedical applications before and are worthwhile to be investigated on their own merit. Our analysis employs tools that go well beyond the application of standard necessary conditions for optimality and aims at a full synthesis of optimal controls, i.e., a complete solution to the problem for arbitrary initial data. These solutions will set theoretical benchmarks to which other - simpler and practically realizable - protocols can be compared. The ultimate goal is to design robust and effective realizable protocols for combination therapies. Due to its applied and interdisciplinary character, the project contains a substantial educational component of interest to students from various fields including Mathematics, Biology and Engineering. Existing efforts to attract women and minorities to the project will be continued.

目前癌症研究的一个积极方向是将化疗、放射治疗等传统治疗方法与抗血管生成治疗或免疫治疗等新方法相结合，以期达到协同作用。这些新方法的潜在生物学机制尚不完全清楚，几个重要的问题仍然需要回答，包括如何随着时间的推移最好地安排这些治疗。当涉及到几个治疗剂时，日程安排就变得更加困难和复杂。对于这些联合疗法，目前还没有医学指南，数学建模和分析能够为建立可靠和有效的治疗方案提供有价值的见解。综合疗法的数学模型相当复杂，并且由于所追求的疗法不同，由多输入控制系统来描述。在这个项目中，现代最优控制中的几何方法将根据需要应用和发展，以分析化疗或放射治疗与抗血管生成治疗相结合的这些系统。从简化的、但经过生物验证的模型开始，将纳入越来越现实的医学特征，如药物的药代动力学和肿瘤免疫系统的相互作用。对于这些模型，出现了非常规的数学结构，这些结构以前没有在生物医学应用的背景下进行过分析，并且值得根据其本身的优点进行研究。我们的分析使用的工具远远超出了最优的标准必要条件的应用，目的是全面综合最优控制，即完全解决任意初始数据的问题。这些解决方案将设定理论基准，以便与其他更简单且可实际实现的协议进行比较。最终目标是为联合治疗设计健壮和有效的可实现方案。由于其应用性和跨学科的特点，该项目包含了包括数学、生物和工程在内的不同领域的学生感兴趣的大量教育内容。目前吸引妇女和少数群体参加该项目的努力将继续下去。