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REVIEW article
Front. Drug Discov.
Sec. Technologies and Strategies to Enable Drug Discovery
Volume 4 - 2024 |
doi: 10.3389/fddsv.2024.1459962
This article is part of the Research Topic Exploring Drug Development With Single Cell Omics Analytics and Stem Cell-Based Disease Models View all articles
Single-cell technology for drug discovery and development
Provisionally accepted
Anzhuo Zhang
1*
Jiawei Zou
2*
Yue Xi
3*
Lianchong Gao
4*
Fulan Deng
1*
Yujun Liu
5*
Pengfei Gao
6*
Henry H. Y Tong
7
Lianjiang Tan
1*
Xin Zou
8,9*
Jie Hao
10*- 1 School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai, Shanghai Municipality, China
- 2 Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CAS), Shanghai, Shanghai Municipality, China
- 3 Department of Reproductive Medicine, Shandong First Medical University, Affiliated Jinan Central Hospital, Jinan, Shandong Province, China, Shandong, China
- 4 Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, Shanghai Municipality, China
- 5 Department of Radiation Oncology, Shanghai Cancer Center, Fudan University, Shanghai, Shanghai Municipality, China
- 6 Department of Traditional Chinese Medicine, Jinshan Hospital, Fudan University, Shanghai, Shanghai Municipality, China
- 7 Centre for Artificial Intelligence Driven Drug Discovery, Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, Macau Region, China
- 8 National Oral Disease Clinical Medicine Research Center, Shanghai Ninth People’s Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
- 9 Institute of Translational Medicine, Shanghai Jiao Tong University, Shangahi, China
- 10 Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
The success rate of drug development today remains low, with long development cycles and high costs, especially in areas such as oncology, neurology, immunology, and infectious diseases.Single-cell omics, encompassing transcriptomics, genomics, epigenomics, proteomics, and metabolomics enable the analysis of gene expression profiles and cellular heterogeneity from the perspective of individual cells, offering a high-resolution view of their functional diversity. These technologies can help reveal disease mechanisms, drug target identification and validation, selection of preclinical models and candidate drugs, and clinical decision-making based on disease response to drugs, all at the single-cell level. The development of deep learning technology has provided a powerful tool for research in drug discovery based on single-cell techniques, which has evolved with the advent of large-scale public databases to predict drug responses and targets. In addition, traditional Chinese medicine (TCMs) research has also entered the era of single-cell technology. Single-cell omics technologies offer an alternative way in deciphering the mechanisms of TCMs in disease treatment, revealing drug targets, screening new drugs, and designing combinations of TCMs. This review aims to explore the application of single-cell omics technologies in drug screening and development comprehensively, highlighting how they accelerate the drug development process and facilitate personalized medicine by precisely identifying therapeutic targets, predicting drug responsiveness, deciphering mechanisms of action. It is also concluded that drug development process and therapeutic efficacy of drugs can be improved by combining singlecell omics and artificial intelligence techniques.
Keywords: Single cell technology, Drug Discovery, deep learning, machine learning, Traditional Chinese Medicine
Received: 05 Jul 2024; Accepted: 04 Oct 2024.
Copyright: © 2024 Zhang, Zou, Xi, Gao, Deng, Liu, Gao, Tong, Tan, Zou and Hao. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Anzhuo Zhang, School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai, 200235, Shanghai Municipality, China
Jiawei Zou, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CAS), Shanghai, 200031, Shanghai Municipality, China
Yue Xi, Department of Reproductive Medicine, Shandong First Medical University, Affiliated Jinan Central Hospital, Jinan, Shandong Province, China, Shandong, China
Lianchong Gao, Shanghai Center for Systems Biomedicine, Shanghai Jiao Tong University, Shanghai, 200240, Shanghai Municipality, China
Fulan Deng, School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai, 200235, Shanghai Municipality, China
Yujun Liu, Department of Radiation Oncology, Shanghai Cancer Center, Fudan University, Shanghai, 200032, Shanghai Municipality, China
Pengfei Gao, Department of Traditional Chinese Medicine, Jinshan Hospital, Fudan University, Shanghai, Shanghai Municipality, China
Lianjiang Tan, School of Materials Science and Engineering, Shanghai Institute of Technology, Shanghai, 200235, Shanghai Municipality, China
Xin Zou, National Oral Disease Clinical Medicine Research Center, Shanghai Ninth People’s Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, 200011, China
Jie Hao, Institute of Clinical Medicine, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
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