化学
药物发现
计算生物学
领域(数学)
药物开发
纳米技术
数据科学
生化工程
药品
药理学
计算机科学
工程类
生物化学
生物
材料科学
纯数学
数学
作者
Mridula Chauhan,Shivansh Kumar,Arpon Biswas,Mukesh Kumar,Mukesh Kumar,Anjali Mishra,Vaishali Singh,Amol Chhatrapati Bisen,Sristi Agrawal,Abhijit Deb Choudhury,Ramkrishna Rayiti,Rabi Sankar Bhatta
出处
期刊:Letters in Drug Design & Discovery
[Bentham Science]
日期:2024-02-02
卷期号:21
被引量:4
标识
DOI:10.2174/0115701808287654240126112003
摘要
Abstract: Discovering new drugs is time-consuming and expensive and involves many different tools from various domains. Numerous omic technologies, such as genomics, transcriptomics, proteomics, and metabolomics, have been created to speed up the process. Leveraging genetic and genomic insights, these methodologies play a pivotal role. Genetic insights aid in target identification, prioritization, and the prediction of drug outcomes. Gene expression data informs drug discovery, while proteomics uncovers targets and facilitates high-throughput profiling. Enhancing drug efficacy necessitates mechanistic insights into downstream effects, enabling side effects and resistance prediction. Early-stage drug discovery now extensively employs diverse metabolomics platforms. This review underscores the recent strides of omic technologies in drug discovery, affirming their role in enhancing drug viability and regulatory approval. The emphasis lies on the latest advancements in genomics, transcriptomics, proteomics, and metabolomics, collectively fortifying drug development.
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