Detecting Personalized Determinants During Drug Treatment from Omics Big Data

个性化医疗 精密医学 基因组 组学 大数据 背景(考古学) 数据科学 药物反应 基因组学 计算机科学 计算生物学 生物信息学 医学 药品 生物 数据挖掘 基因组 药理学 遗传学 基因 病理 古生物学
作者
Lu Wang,Xiangtian Yu,Chengming Zhang,Tao Zeng
出处
期刊:Current Pharmaceutical Design [Bentham Science]
卷期号:24 (32): 3727-3738 被引量:10
标识
DOI:10.2174/1381612824666181106102111
摘要

Targeted therapy is the foundation of personalized medicine in cancer, which is often understood as the right patient using the right drug. Thinking from the viewpoint of determinants during personalized drug treatment, the genetics, epigenetics and metagenomics would provide individual-specific biological elements to characterize the personalized responses for therapy.Such personalized determinants should be not only understood as specific to one person, while they should have certain replicate observations in a group of individuals but not all, which actually provide more credible and reproducible personalized biological features. The requirement of detecting personalized determinants is well supported by novel high-throughput sequencing technologies and newly temporal-spatial experimental protocols, which quickly produce the omics big data.In this mini-review, we would like to give a brief introduction firstly on the advanced drug or drug-like therapy with genetics, epigenetics and metagenomics, respectively, from the viewpoint of personalized determinants; then summarize the computational methods helpful to analyze the corresponding omics data under the consideration of personalized biological context; and particularly focus on metagenomics to discuss current data, method, and opportunity for personalized medicine.Totally, detecting personalized determinants during drug treatment from omics big data will bring the precision medicine or personalized medicine from concept to application. More and more inspiring biotechnologies, data resources, and analytic approaches will benefit All of US in the near future.
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