Systems Biology: A Powerful Tool for Drug Development

被引:9
|
作者
Rai, Sneha [1 ]
Raj, Utkarsh [2 ,3 ]
Varadwaj, Pritish Kumar [3 ]
机构
[1] Univ Delhi, Netaji Subhas Inst Technol, Div Biotechnol, New Delhi, India
[2] NIIT Univ, Dept Biotechnol & Bioinformat, Neemrana, Rajasthan, India
[3] Indian Inst Informat Technol, Dept Bioinformat & Appl Sci, Allahabad, Uttar Pradesh, India
关键词
Network models; Dynamical models; Biomarkers; Drug repurposing; Drug combinations; CVD; BREAST-CANCER SUSCEPTIBILITY; NETWORK MOTIFS; SIGNALING NETWORK; PREDICTION; DISCOVERY; GENES; MODEL; IDENTIFICATION; PHARMACOLOGY; COMPLEXES;
D O I
10.2174/1568026618666181025113226
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
The conventional way of characterizing a disease consists of correlating clinical symptoms with pathological findings. Although this approach for many years has assisted clinicians in establishing syndromic patterns for pathophenotypes, it has major limitations as it does not consider preclinical disease states and is unable to individualize medicine. Moreover, the complexity of disease biology is the major challenge in the development of effective and safe medicines. Therefore, the process of drug development must consider biological responses in both pathological and physiological conditions. Consequently, a quantitative and holistic systems biology approach could aid in understanding complex biological systems by providing an exceptional platform to integrate diverse data types with molecular as well as pathway information, leading to development of predictive models for complex diseases. Furthermore, an increase in knowledgebase of proteins, genes, metabolites from high -throughput experimental data accelerates hypothesis generation and testing in disease models. The systems biology approach also assists in predicting drug effects, repurposing of existing drugs, identifying new targets, facilitating development of personalized medicine and improving decision making and success rate of new drugs in clinical trials.
引用
收藏
页码:1745 / 1754
页数:10
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