Defranoux Nadine A, Stokes Cynthia L, Young Daniel L, Kahn Arnold J
In Silico R&D Department, Entelos, Inc., Foster City, California, USA.
J Bone Miner Res. 2005 Jul;20(7):1079-84. doi: 10.1359/JBMR.050401. Epub 2005 Apr 4.
Contemporary, computer-based mathematical modeling techniques make it possible to represent complex biological mechanisms in a manner that permits hypothesis testing in silico. This perspective shows how such approaches might be applied to bone remodeling and therapeutic research. Currently, the dominant conceptual model applied in bone research involves the dynamic balance between the continual build-up and breakdown of bone matrix by two cell types, the osteoblasts and osteoclasts, acting together as a coordinated, remodeling unit. This conceptualization has served extraordinarily well as a focal point for understanding how mutations, chemical mediators, and mechanical force, as well as external influences (e.g., drugs, diet) affect bone structure and function. However, the need remains to better understand and predict the consequences of manipulating any single factor, or combination of factors, within the context of this complex system's multiple interacting pathways. Mathematical models are a natural extension of conceptual models, providing dynamic, quantitative descriptions of the relationships among interacting components. This formalization creates the ability to simulate the natural behavior of a system, as well as its modulation by therapeutic or dietetic interventions. A number of mathematical models have been developed to study complex bone functions, but most include only a limited set of biological components needed to address a few specific questions. However, it is possible to develop larger, multiscale models that capture the dynamic interactions of many biological components and relate them to important physiological or pathological outcomes that allow broader study. Examples of such models include entelos' physiolab platforms. These models simulate the dynamic, quantitative interactions among a biological system's biochemicals, cells, tissues, and organs and how they give rise to key physiologic and pathophysiologic outcomes. We propose that a similar predictive, dynamical, multiscale mathematical model of bone remodeling and metabolism would provide a better understanding of the mechanisms governing these phenomena as well as serve as an in silico platform for testing pharmaceutical and clinical interventions on metabolic bone disease.
当代基于计算机的数学建模技术,使得以一种能够在计算机上进行假设检验的方式来呈现复杂的生物机制成为可能。本文阐述了如何将这些方法应用于骨重塑和治疗研究。目前,骨研究中应用的主要概念模型涉及两种细胞类型(成骨细胞和破骨细胞)对骨基质持续形成和分解之间的动态平衡,它们共同作为一个协调的重塑单元发挥作用。这一概念化对于理解突变、化学介质、机械力以及外部影响(如药物、饮食)如何影响骨骼结构和功能起到了非常好的聚焦作用。然而,在这个复杂系统的多个相互作用途径的背景下,仍需要更好地理解和预测操纵任何单个因素或因素组合的后果。数学模型是概念模型的自然延伸,它提供了相互作用组件之间关系的动态、定量描述。这种形式化使得能够模拟系统的自然行为及其通过治疗或饮食干预的调节。已经开发了许多数学模型来研究复杂的骨功能,但大多数只包含解决几个特定问题所需的有限生物组件集。然而,有可能开发更大的多尺度模型,该模型能够捕捉许多生物组件的动态相互作用,并将它们与重要的生理或病理结果相关联,从而允许进行更广泛的研究。此类模型的示例包括Entelos的PhysioLab平台。这些模型模拟生物系统的生化物质、细胞、组织和器官之间的动态、定量相互作用,以及它们如何产生关键的生理和病理生理结果。我们认为,类似的骨重塑和代谢的预测性、动态性多尺度数学模型将有助于更好地理解这些现象背后的机制,并作为一个计算机平台来测试针对代谢性骨病的药物和临床干预措施。