An Engineering Control System Paradigm for Quantitative Understanding of Hemostasis

本研究的主要目标是开发和验证工程控制系统范例，以定量了解多种相互依赖的止血过程如何相互作用，从而安全有效地控制血管损伤后的失血。将开发一种新的定量模块建模和分析技术来组织这一生物过程的机制细节，并进行实验验证。由此产生的数学模型将被用来从控制系统的角度阐明止血疾病的机制，并产生关于有效治疗的可检验的假设。需要回答的具体问题是：从数量上讲，在正常情况下，整个止血过程的各个组成部分如何协同工作，对血管损伤产生快速、有效和稳定的反应？将执行的具体任务是：任务1：模型开发。制定止血组件的详细控制系统框图表示法，推导出每个组件的数学模型，并集成到整体、全面的动态模型中。任务2：模型验证(试验性)。在持续的协作中，PI将对照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。将对模型进行计算研究和理论分析；从控制系统的角度推导对病理障碍的定量见解；并根据对造成所确定的障碍的部件故障的最佳补偿，产生关于有效治疗方案的假设。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，有助于获取关于最复杂的细胞和分子机制的更精细的数据，不断增加的计算能力已稳步引导系统生物学中的数学建模采用？更大和更复杂的？这些复杂系统的表示。对于具体的止血问题，目前还没有完整的止血过程的整体量化模型，可能是因为许多组成部分本身相当复杂，并且有一个标准？试图开发一个整体模型不太可能是非常有用的。通过认识到止血的核心是自动生物控制系统，本研究旨在运用工程控制系统的概念来开发一个全面的止血过程模型，该模型在不牺牲分析可操作性的情况下实现保真度。PIs为这项研究设想了两种主要影响：(I)技术：改进了对正常情况下如何调节这一生物过程的量化理解，以及如何从单个组成部分的连接中产生整体特征，并通过更精确地治疗血友病和血栓病的形式对临床实践产生影响；(Ii)方法：展示如何在极其复杂的生物现象的模型中同时实现高保真和分析易操作性。在不断发展的本科培训计划中，更广泛影响的核心是如何将生物学融入经典的化学工程课程。这项研究从理论和实验验证两个方面探讨了最适合向学生介绍生物控制系统的问题，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讲广泛传播。此外，作为少数族裔，该协会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，并应能够吸引少数族裔学生参与这一努力。

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.