An Gary, Bartels John, Vodovotz Yoram
Department of Surgery, University of Chicago, Chicago, IL 60637.
Drug Dev Res. 2011 Mar 1;72(2):187-200. doi: 10.1002/ddr.20415.
The clinical translation of promising basic biomedical findings, whether derived from reductionist studies in academic laboratories or as the product of extensive high-throughput and -content screens in the biotechnology and pharmaceutical industries, has reached a period of stagnation in which ever higher research and development costs are yielding ever fewer new drugs. Systems biology and computational modeling have been touted as potential avenues by which to break through this logjam. However, few mechanistic computational approaches are utilized in a manner that is fully cognizant of the inherent clinical realities in which the drugs developed through this ostensibly rational process will be ultimately used. In this article, we present a Translational Systems Biology approach to inflammation. This approach is based on the use of mechanistic computational modeling centered on inherent clinical applicability, namely that a unified suite of models can be applied to generate in silico clinical trials, individualized computational models as tools for personalized medicine, and rational drug and device design based on disease mechanism.
有前景的基础生物医学研究成果的临床转化，无论是源自学术实验室的还原论研究，还是生物技术和制药行业广泛的高通量及高内涵筛选的产物，都已进入一个停滞期，即研发成本不断攀升，新药却越来越少。系统生物学和计算建模被吹捧为突破这一僵局的潜在途径。然而，很少有机械性的计算方法能以充分认识到通过这一表面上合理的过程开发的药物最终将被使用的固有临床现实的方式被利用。在本文中，我们提出了一种针对炎症的转化系统生物学方法。这种方法基于以固有临床适用性为核心的机械性计算建模的应用，也就是说，可以应用一套统一的模型来生成虚拟临床试验、作为个性化医疗工具的个体化计算模型，以及基于疾病机制的合理药物和器械设计。
