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Zhang YQ, Guo RR, Chen YH, Li TC, Du WZ, Xiang RW, Guan JB, Li YP, Huang YY, Yu ZQ, Cai Y, Zhang P, Ling GX. Ionizable drug delivery systems for efficient and selective gene therapy. Mil Med Res 2023; 10:9. [PMID: 36843103 PMCID: PMC9968649 DOI: 10.1186/s40779-023-00445-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 02/01/2023] [Indexed: 02/28/2023] Open
Abstract
Gene therapy has shown great potential to treat various diseases by repairing the abnormal gene function. However, a great challenge in bringing the nucleic acid formulations to the market is the safe and effective delivery to the specific tissues and cells. To be excited, the development of ionizable drug delivery systems (IDDSs) has promoted a great breakthrough as evidenced by the approval of the BNT162b2 vaccine for prevention of coronavirus disease 2019 (COVID-19) in 2021. Compared with conventional cationic gene vectors, IDDSs can decrease the toxicity of carriers to cell membranes, and increase cellular uptake and endosomal escape of nucleic acids by their unique pH-responsive structures. Despite the progress, there remain necessary requirements for designing more efficient IDDSs for precise gene therapy. Herein, we systematically classify the IDDSs and summarize the characteristics and advantages of IDDSs in order to explore the underlying design mechanisms. The delivery mechanisms and therapeutic applications of IDDSs are comprehensively reviewed for the delivery of pDNA and four kinds of RNA. In particular, organ selecting considerations and high-throughput screening are highlighted to explore efficiently multifunctional ionizable nanomaterials with superior gene delivery capacity. We anticipate providing references for researchers to rationally design more efficient and accurate targeted gene delivery systems in the future, and indicate ideas for developing next generation gene vectors.
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Affiliation(s)
- Yu-Qi Zhang
- Faculty of Medical Device, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Ran-Ran Guo
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Yong-Hu Chen
- School of Pharmacy, Yanbian University, Yanji, 133002, Jilin, China
| | - Tian-Cheng Li
- School of Pharmacy, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Wen-Zhen Du
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Rong-Wu Xiang
- Faculty of Medical Device, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China
| | - Ji-Bin Guan
- Masonic Cancer Center, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Yu-Peng Li
- Masonic Cancer Center and Department of Medicinal Chemistry, University of Minnesota, Minneapolis, MN, 55455, USA
| | - Yuan-Yu Huang
- Advanced Research Institute of Multidisciplinary Science; School of Life Science; School of Medical Technology; Key Laboratory of Molecular Medicine and Biotherapy; Key Laboratory of Medical Molecule Science and Pharmaceutics Engineering, Beijing Institute of Technology, Beijing, 100081, China
| | - Zhi-Qiang Yu
- Department of Laboratory Medicine, Dongguan Institute of Clinical Cancer Research, Affiliated Dongguan Hospital, Southern Medical University, Dongguan, 523018, Guangdong, China
| | - Yin Cai
- Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hong Kong, Hong Kong SAR, China
| | - Peng Zhang
- Wuya College of Innovation, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China.
| | - Gui-Xia Ling
- Faculty of Medical Device, Shenyang Pharmaceutical University, Shenyang, 110016, Liaoning, China.
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Li M, Ren J, Si X, Sun Z, Wang P, Zhang X, Liu K, Wei B. The global mRNA vaccine patent landscape. Hum Vaccin Immunother 2022; 18:2095837. [PMID: 35797353 PMCID: PMC9746484 DOI: 10.1080/21645515.2022.2095837] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2022] [Revised: 06/10/2022] [Accepted: 06/27/2022] [Indexed: 12/15/2022] Open
Abstract
In light of their quick development and low risk, mRNA vaccines are gradually replacing traditional vaccines. In order to characterize the patent landscape of mRNA vaccines, this study collated mRNA vaccine-related applications that have been registered since 1962. Accordingly, the 1852 patent families were discussed in relation to their temporal distribution, geographic scope, organizational assignees, and co-patenting activities. mRNA vaccines were shown to demonstrate promise in infectious disease, cancer immunotherapy, and allergic disease, with a focus on lipid nanoparticles. Notably, these vaccines are being developed against a backdrop of fierce industrial competition and intensive collaboration with a rise in applications. The findings of this study highlighted cutting-edge inventions, key players, and collaboration dynamics among institutions. By understanding the landscape of mRNA vaccine patents, researchers and those in industry may better comprehend the latest trends in this area, which may also assist relevant decision-making by academics, government officials, and industrial leaders.
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Affiliation(s)
- Mengyao Li
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Jianxiong Ren
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Xingyong Si
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Zhaocai Sun
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Pingping Wang
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Xiaoming Zhang
- Department of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Kunmeng Liu
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
| | - Benzheng Wei
- Center for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China
- Qingdao Academy of Chinese Medical Sciences, Shandong University of Traditional Chinese Medicine, Qingdao, China
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