An integrated approach for inference and mechanistic modeling for advancing drug development

被引:25
作者
Aksenov, SV
Church, B
Dhiman, A
Georgieva, A
Sarangapani, R
Helmlinger, G
Khalil, IG
机构
[1] Novartis Inst Biomed Res Inc, Cambridge, MA 02139 USA
[2] Gene Network Sci Inc, Ithaca, NY 14850 USA
[3] Novartis Pharmaceut, E Hanover, NJ 07936 USA
关键词
drug development; systems biology; computational biology; biomarker; efficacy; toxicity; omic;
D O I
10.1016/j.febslet.2005.02.012
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
An important challenge facing researchers in drug development is how to translate multi-omic measurements into biological insights that will help advance drugs through the clinic. Computational biology strategies are a promising approach for systematically capturing the effect of a given drug on complex molecular networks and on human physiology. This article discusses a two-pronged strategy for inferring biological interactions from large-scale multi-omic measurements and accounting for known biology via mechanistic dynamical simulations of pathways, cells, and organ- and tissue level models. These approaches are already playing a role in driving drug development by providing a rational and systematic computational framework. (c) 2005 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:1878 / 1883
页数:6
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