An Engineering Control System Paradigm for Quantitative Understanding of Hemostasis

用于定量理解止血的工程控制系统范例

• 批准号: 0925202
• 负责人: Babatunde Ogunnaike
• 金额: $ 39.59万
• 依托单位: University of Delaware
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0925202&HistoricalAwards=false
• 关键词: Engineering; Control; System; Paradigm; Quantitative

0925202OgunnaikeThe primary goal of this research is to develop and validate an engineering control system paradigm for obtaining quantitative insight into how multiple interdependent hemostatic processes interact to control blood loss safely and effectively following vessel injury. A novel quantitative modular modeling and analysis technique for organizing the mechanistic details of this biological process will be developed and validated experimentally. The resulting mathematical model will be used to elucidate mechanisms of hemostatic disorders from a control system perspective, and to generate testable hypotheses about effective treatment. The specific question to be answered is: Quantitatively, how do the various components of the entire hemostatic process work together to produce fast, effective and stable responses to vascular injury under normal conditions? The specific tasks that will be performed are: Task 1: Model Development. Develop a detailed control system block diagram representation of the components of hemostasis, derive mathematical models for each component and integrate into a holistic, comprehensive dynamic model. Task 2: Model Validation (Experimental). In a continuing collaboration the PIs will validate the predictions of each principal module of the overall model against independent experimental data. Task 3: Model Analysis and Hypothesis Generation. Computation studies and theoretical analyses of the model will be carried out; derivation of quantitative insight into pathological disorders from a control system perspective; and generation of hypothesis regarding effective treatment regimens in terms of optimal compensation for component malfunction responsible for the identified disorder. Intellectual Merit Systemic changes in life sciences research have created opportunities for mathematical modeling to play a major role in developing quantitative and predictive understanding of complex biological phenomena. With ever improving experimental capabilities facilitating the acquisition of more refined data on the most intricate cellular and molecular mechanisms, increasing computational power has steadily steered mathematical modeling in systems biology towards adopting ?bigger and more complex? representations of these complex systems. For the specific problem of hemostasis there are currently no holistic quantitative models of the complete hemostasis process perhaps because many of the constituent components are quite complex in their own right, and a ?standard? attempt at developing a holistic model is not likely to be very useful. By recognizing that at the heart of hemostasis is an automatic biological control system, this research aims to deploy concepts from engineering control systems to develop a comprehensive hemostatic process model that achieves fidelity without sacrificing analytical tractability. The PIs envision two kinds of primary impact for this research: (i) Technical: an improved quantitative understanding of how this biological process is regulated under normal circumstances, and how the characteristics of the whole emerge from the connection of the individual component parts, with implications for clinical practice in the form of more precise treatment of hemophilia and thrombophilia; (ii) Methodological: demonstrating how to achieve high-fidelity and analytical tractability simultaneously in models of extremely complex biological phenomena. Broader Impact At the heart of the evolving undergraduate training program is the issue of how to integrate biology within the classical chemical engineering curriculum. This research addresses theoretically and with experimental validation, issues that are perfect for introducing students to biological control systems, and how to employ such simulation tools as SIMULINK for modeling and understanding such systems. The results of this research will be integrated into the teaching curricula and widely disseminated through publications and presentations to other educators and researchers. In addition, the PI, as a minority himself, is committed to recruiting under-represented groups into the chemical engineering discipline in general and systems biology research in particular, and should be able to attract minority students to participate in this effort.

0925202Ogunnaike 这项研究的主要目标是开发和验证一种工程控制系统范例，以定量了解多个相互依赖的止血过程如何相互作用，以安全有效地控制血管损伤后的失血。将开发并通过实验验证一种新颖的定量模块化建模和分析技术，用于组织该生物过程的机械细节。由此产生的数学模型将用于从控制系统的角度阐明止血障碍的机制，并生成有关有效治疗的可检验的假设。需要回答的具体问题是：定量地讲，整个止血过程的各个组成部分在正常情况下如何协同工作，对血管损伤产生快速、有效、稳定的反应？将执行的具体任务是： 任务 1：模型开发。开发止血组件的详细控制系统框图表示，导出每个组件的数学模型，并集成到整体、综合的动态模型中。任务 2：模型验证（实验）。在持续的合作中，PI 将根据独立的实验数据验证整个模型的每个主要模块的预测。任务 3：模型分析和假设生成。将进行模型的计算研究和理论分析；从控制系统的角度对病理疾病进行定量分析；以及根据对造成所识别疾病的组件故障的最佳补偿来产生关于有效治疗方案的假设。智力优势生命科学研究的系统性变化为数学建模创造了机会，使其在发展对复杂生物现象的定量和预测性理解方面发挥重要作用。随着实验能力的不断提高，有助于获取有关最复杂的细胞和分子机制的更精细的数据，计算能力的提高已稳步引导系统生物学中的数学模型采用“更大、更复杂”的方向。这些复杂系统的表征。对于止血的具体问题，目前还没有完整的止血过程的整体定量模型，也许是因为许多组成部分本身就相当复杂，并且没有一个“标准”。尝试开发一个整体模型不太可能很有用。通过认识到止血的核心是自动生物控制系统，本研究旨在部署工程控制系统的概念，开发一个全面的止血过程模型，在不牺牲分析易处理性的情况下实现保真度。 PI 设想了本研究的两种主要影响： (i) 技术：更好地定量理解正常情况下如何调节该生物过程，以及整体的特征如何从各个组成部分的连接中显现出来，以更精确地治疗血友病和血栓形成倾向的形式对临床实践的影响； (ii) 方法论：展示如何在极其复杂的生物现象模型中同时实现高保真度和分析易处理性。更广泛的影响 不断发展的本科生培训计划的核心问题是如何将生物学整合到经典化学工程课程中。这项研究从理论上和实验验证上解决了一些问题，这些问题非常适合向学生介绍生物控制系统，以及如何使用 SIMULINK 等仿真工具来建模和理解此类系统。这项研究的结果将被纳入教学课程，并通过出版物和向其他教育工作者和研究人员的演示广泛传播。此外，PI本人作为少数族裔，致力于招募代表性不足的群体进入化学工程学科，特别是系统生物学研究，并且应该能够吸引少数族裔学生参与这一努力。