Department of Biomedical Engineering, Cornell University, 205 Weill Hall, Ithaca, NY 14853, USA.
Ann Biomed Eng. 2012 Nov;40(11):2345-54. doi: 10.1007/s10439-012-0558-8. Epub 2012 Apr 6.
Our hemostatic system, when called to action, depends on the complex arrangement of a tightly regulated and extensive network of molecules with versatile functionality. Experimental methods have demonstrated marked improvement through enhanced condition-control and monitoring. However, this approach continues to provide limited explanations of the role of individual elements or of a specific component within the entire system. To fill this void, multiscale simulations based on high throughput computing and comprehensive mathematical models are showing their strength in not only revealing hidden physiological mechanisms but also predicting pharmacological/phenotypical outcome in hemostasis reactions based on quantitative analysis. In this review article, we present up-to-date computational methods that simulate the process of platelet adhesion and thrombus growth, compare and summarize their advantages and drawbacks, verify their predictive power, and project their future directions. We provide an in-depth summary of one such computational method-Platelet Adhesive Dynamics (PAD)-and discuss its application in simulating platelet aggregation and thrombus development.
我们的止血系统在被调用时,依赖于一个紧密调节和广泛的分子网络的复杂排列,这些分子具有多功能性。实验方法已经通过增强条件控制和监测得到了显著的改善。然而,这种方法仍然无法充分解释单个元素或整个系统中特定组件的作用。为了填补这一空白,基于高通量计算和全面数学模型的多尺度模拟正在显示其强大之处,不仅可以揭示隐藏的生理机制,还可以基于定量分析预测止血反应中的药理/表型结果。在这篇综述文章中,我们介绍了最新的计算方法,这些方法模拟了血小板黏附与血栓形成的过程,比较并总结了它们的优缺点,验证了它们的预测能力,并预测了它们的未来发展方向。我们深入总结了其中一种计算方法——血小板黏附动力学(PAD),并讨论了它在模拟血小板聚集和血栓形成中的应用。