Compartmental modeling in the analysis of biological systems.
Compartmental modeling in the analysis of biological systems.
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DOI：
10.1007/978-1-62703-050-2_17
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发表时间：
2012
影响因子：
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通讯作者：
J. Bassingthwaighte;Erik Butterworth;Bartholomew Jardine;G. Raymond
中科院分区：
文献类型：
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作者：
J. Bassingthwaighte;Erik Butterworth;Bartholomew Jardine;G. Raymond
隔室模型由多组相互连接的混合室或搅拌槽组成。系统的每种组分被认为是均匀的，立即混合，具有均匀的浓度。状态变量是化学物质的浓度或摩尔量。化学反应，跨膜转运，结合过程，在现实中确定的电化学驱动力和热力学定律的约束下，通常使用一阶速率方程处理。这种基本的简单性使它们易于计算，因为常微分方程（ODE）很容易数值求解，而且通常是解析求解。虽然房室系统具有仅仅是描述性的声誉，但它们可以通过细化动力学发展到提供现实机械特征的水平。一般来说，人们正在考虑多房室系统的现实建模。Combustion可以被用作没有明确内部结构的“黑”盒算子，但在药代动力学中，隔室被认为是特定溶质的均匀池，输入和输出被定义为流量或溶质通量，转换被表示为速率方程。在药代动力学（PK）中，房室模型广泛用于描述给药后药物浓度的浓度-时间曲线。这给出了它在体内保持可用的时间的描述，并且是定义剂量方案，递送方法和其效果预期的指南。药效学（PD）需要更深入的研究，因为它关注的是对药物或毒素的生理反应，因此激发了了解药物如何在生物系统中发挥作用的需求;由于PK和PD同时进行（PKPD），因此必须了解药物反应机制，然后回到递送机制（PK部分）。多年来已经开发了许多系统来帮助建模PKPD系统。几乎所有的都只解决了常微分方程，而在描述化学转化、求解方程的方法、显示结果和分析系统行为时，允许相当大的概念复杂性。房室分析系统包括模拟和应用数学，CoPasi（酶反应），Berkeley Madonna（生理系统），XPPaut（动力系统行为分析）以及许多其他系统。这里使用JSim，一个允许使用ODE和偏微分方程（描述空间分布）的系统。它是一个开源系统，这意味着它是免费的，可以由用户修改。它提供了一组独特的功能，使模型验证更可靠，更容易，并产生可以在所有标准计算机平台上共享的模型。
Compartmental models are composed of sets of interconnected mixing chambers or stirred tanks. Each component of the system is considered to be homogeneous, instantly mixed, with uniform concentration. The state variables are concentrations or molar amounts of chemical species. Chemical reactions, transmembrane transport, and binding processes, determined in reality by electrochemical driving forces and constrained by thermodynamic laws, are generally treated using first-order rate equations. This fundamental simplicity makes them easy to compute since ordinary differential equations (ODEs) are readily solved numerically and often analytically. While compartmental systems have a reputation for being merely descriptive they can be developed to levels providing realistic mechanistic features through refining the kinetics. Generally, one is considering multi-compartmental systems for realistic modeling. Compartments can be used as “black” box operators without explicit internal structure, but in pharmacokinetics compartments are considered as homogeneous pools of particular solutes, with inputs and outputs defined as flows or solute fluxes, and transformations expressed as rate equations.Descriptive models providing no explanation of mechanism are nevertheless useful in modeling of many systems. In pharmacokinetics (PK), compartmental models are in widespread use for describing the concentration–time curves of a drug concentration following administration. This gives a description of how long it remains available in the body, and is a guide to defining dosage regimens, method of delivery, and expectations for its effects. Pharmacodynamics (PD) requires more depth since it focuses on the physiological response to the drug or toxin, and therefore stimulates a demand to understand how the drug works on the biological system; having to understand drug response mechanisms then folds back on the delivery mechanism (the PK part) since PK and PD are going on simultaneously (PKPD).Many systems have been developed over the years to aid in modeling PKPD systems. Almost all have solved only ODEs, while allowing considerable conceptual complexity in the descriptions of chemical transformations, methods of solving the equations, displaying results, and analyzing systems behavior. Systems for compartmental analysis include Simulation and Applied Mathematics, CoPasi (enzymatic reactions), Berkeley Madonna (physiological systems), XPPaut (dynamical system behavioral analysis), and a good many others. JSim, a system allowing the use of both ODEs and partial differential equations (that describe spatial distributions), is used here. It is an open source system, meaning that it is available for free and can be modified by users. It offers a set of features unique in breadth of capability that make model verification surer and easier, and produces models that can be shared on all standard computer platforms.