Agent-based computer simulation and SIRS: Building a bridge between basic science and clinical trials
Agent-based computer simulation and SIRS: Building a bridge between basic science and clinical trials
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DOI：
10.1097/00024382-200116040-00006
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发表时间：
2001-10-01
期刊：
影响因子：
3.1
通讯作者：
An, G
中科院分区：
文献类型：
--
作者：
An, G
系统性炎症反应综合征(SIRS)/多器官功能衰竭（MOF）的管理仍然是重症监护领域最大的挑战。在将基础科学研究成果转化为有效的治疗方案方面，一直存在着一致的困难。我们认为，这部分是由于未能解释炎症过程的复杂、非线性性质，其中SIRS/MOF代表了一种无序状态。试图在不了解系统动态的情况下操纵这一过程可能会产生意想不到的后果。基于agent的计算机仿真（ABCS）提供了一种手段，将从基础科学的线性分析中获得的信息综合到一个保持炎症系统复杂性的模型中。我们使用基于细胞水平的ABCS构建了炎症过程的抽象版本。尽管它是抽象的，但模拟产生了非线性行为并再现了炎症反应的动态结构。此外，调整模拟以模拟20世纪90年代一个不成功的初始抗炎试验，证明了在这些临床试验中观察到的不良结果。必须强调，目前的模型是极其抽象和简化的。然而，希望未来足够复杂的abcs最终可以提供一个重要的桥梁工具，将基础科学发现转化为临床应用。创建这些模拟将需要大量的协作努力，并且希望本文能够激发人们对这种形式的分析的兴趣。
The management of Systemic Inflammatory Response Syndrome (SIRS)/Multiple Organ Failure (MOF) remains the greatest challenge in the field of critical care. There has been uniform difficulty in translating the results of basic science research into effective therapeutic regimes. We propose that this is due in part to a failure to account for the complex, nonlinear nature of the inflammatory process of which SIRS/MOF represents a disordered state. Attempts to manipulate this process without an understanding of the dynamics of the system may potentially produce unintended consequences. Agent-Based Computer Simulation (ABCS) provides a means to synthesize the information acquired from the linear analysis of basic science into a model that preserves the complexity of the inflammatory system. We have constructed an abstracted version of the inflammatory process using an ABCS that is based at the cellular level. Despite its abstraction, the simulation produces non-linear behavior and reproduces the dynamic structure of the inflammatory response. Furthermore, adjustment of the simulation to model one of the unsuccessful initial anti-inflammatory trials of the 1990's demonstrates the adverse outcome that was observed in those clinical trials. It must be emphasized that the current model is extremely abstract and simplified. However, it is hoped that future ABCSs of sufficient sophistication eventually may provide an important bridging tool to translate basic science discoveries into clinical applications. Creating these simulations will require a large collaborative effort, and it is hoped that this paper will stimulate interest in this form of analysis.