生物经济核心产业专题 |
|
|
|
|
未来生物医药产业发展趋势研究 |
裘卉青1,杨子杰2,郭放3,詹御涛1,**() |
1 西湖大学未来产业研究中心 杭州 310024 2 西湖大学生命科学学院 杭州 310024 3 西湖大学工学院 杭州 310024 |
|
Development Trends of the Industries of the Future Biopharmaceuticals |
Huiqing QIU1,Zijie YANG2,Fang GUO3,Yutao ZHAN1,**() |
1 Research Center for Industries of the Future, Westlake University, Hangzhou 310024, China 2 School of Life Sciences, Westlake University, Hangzhou 310024, China 3 School of Engineering, Westlake University, Hangzhou 310024, China |
引用本文:
裘卉青, 杨子杰, 郭放, 詹御涛. 未来生物医药产业发展趋势研究[J]. 中国生物工程杂志, 2024, 44(1): 8-18.
Huiqing QIU, Zijie YANG, Fang GUO, Yutao ZHAN. Development Trends of the Industries of the Future Biopharmaceuticals. China Biotechnology, 2024, 44(1): 8-18.
链接本文:
https://manu60.magtech.com.cn/biotech/CN/10.13523/j.cb.2308100
或
https://manu60.magtech.com.cn/biotech/CN/Y2024/V44/I1/8
|
[1] |
李晓华, 王怡帆. 未来产业的演化机制与产业政策选择. 改革, 2021(2): 54-68.
|
|
Li X H, Wang Y F. The evolution mechanism of future industry and choice of industrial policy. Reform, 2021(2): 54-68.
|
[2] |
DiMasi J A, Grabowski H G, Hansen R W. Innovation in the pharmaceutical industry: new estimates of R&D costs. Journal of Health Economics, 2016, 47: 20-33.
doi: 10.1016/j.jhealeco.2016.01.012
|
[3] |
Hay M, Thomas D W, Craighead J L, et al. Clinical development success rates for investigational drugs. Nature Biotechnology, 2014, 32(1): 40-51.
doi: 10.1038/nbt.2786
pmid: 24406927
|
[4] |
Kennedy D, Norman C. What don’t we know? Science, 2005, 309(5731): 75.
|
[5] |
国家自然科学基金委员会科学传播与成果转化中心. Science发布:全世界最前沿的125个科学问题. [2023-08-06]. https://www.nsfc.gov.cn/csc/20340/20289/22023/index.html.
|
|
Center for Science Communication and Transformation, National Natural Science Foundation of China. Science release: 125 of the world’s most cutting-edge scientific questions. [2023-08-06]. https://www.nsfc.gov.cn/csc/20340/20289/22023/index.html.
|
[6] |
周泉. 2021年全球及中国生物医药行业现状分析. [2023-08-06]. https://m.huaon.com/detail/787854.html.
|
|
Zhou Q. Analysis of global and Chinese biopharmaceutical industry status in 2021. [2023-08-06]. https://m.huaon.com/detail/787854.html.
|
[7] |
IQVIA. 2023年全球医药研发全景展望. [2023-08-06]. https://www.iqvia.com/zh-cn/locations/china/library/brochures/global-trends-in-r-and-d-2023.
|
|
IQVIA. Global trends in biopharmaceutical R&D 2023. [2023-08-06]. https://www.iqvia.com/zh-cn/locations/china/library/brochures/global-trends-in-r-and-d-2023.
|
[8] |
Giglio P, Micklus A. Biopharma dealmaking in 2022. Nature Reviews Drug Discovery, 2023, 22(2): 92-93.
doi: 10.1038/d41573-023-00012-0
|
[9] |
Micklus A, Giglio P. Biopharma dealmaking in 2021. Nature Reviews Drug Discovery, 2022, 21(2): 93-94.
doi: 10.1038/d41573-022-00017-1
pmid: 35043002
|
[10] |
Food and Drug Administration. Novel drug approvals for 2022. [2023-08-06]. https://www.fda.gov/drugs/new-drugs-fda-cders-new-molecular-entities-and-new-therapeutic-biological-products/novel-drug-approvals-2022.
|
[11] |
European Medicines Agency.Human medicines: highlights of 2022. [2023-08-06]. ttps://www.ema.europa.eu/en/news/human-medicines-highlights-2022.
|
[12] |
Pharmaceuticals and Medical Devices Agency. List of approved products. [2023-08-06]. https://www.pmda.go.jp/english/review-services/reviews/approved-information/drugs/0002.html.
|
[13] |
医药魔方. 2022年中国批准上市的新药. [2023-08-06]. https://xueqiu.com/8965749698/239470918.
|
|
Pharmcube. New drugs approved by China in 2022. [2023-08-06]. https://xueqiu.com/8965749698/239470918.
|
[14] |
王美华. 中国医药, 迈向创新. 人民日报海外版, 2021-02-02( 11).
|
|
Wang M H. Chinese medicine, towards innovation. People’s Daily Overseas Edition, 2021-02-02(11).
|
[15] |
中商产业研究院. 2022年中国生物医药行业产业链上中下游市场剖析. [2023-08-06]. https://www.askci.com/news/chanye/20220510/1635011851682_4.shtml.
|
|
Zhongshang Industrial Research Institute. Analysis of the middle and downstream markets of China’s biopharmaceutical industry chain in 2022. [2023-08-06]. https://www.askci.com/news/chanye/20220510/1635011851682_4.shtml.
|
[16] |
Shang J B, Liu J L, Jiang M, et al. Automated phrase mining from massive text corpora. IEEE Transactions on Knowledge and Data Engineering, 2018, 30(10): 1825-1837.
doi: 10.1109/TKDE.2018.2812203
pmid: 31105412
|
[17] |
Gu X T, Wang Z H, Bi Z Y, et al. UCPhrase: unsupervised context-aware quality phrase tagging. Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, 2021, DOI:10.1145/3447548.3467397.
doi: 10.1145/3447548.3467397
|
[18] |
Cohan A, Feldman S, Beltagy I, et al. Specter: document-level representation learning using citation-informed transformers. Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020: 2270-2282.
|
[19] |
Han J W, Pei J, Yin Y W, et al. Mining frequent patterns without candidate generation: a frequent-pattern tree approach. Data Mining and Knowledge Discovery, 2004, 8: 53-87.
doi: 10.1023/B:DAMI.0000005258.31418.83
|
[20] |
Lu J H, Yang L Y, Mac Namee B, et al. A rationale-centric framework for human-in-the-loop machine learning. Annual Meeting of the Association for Computational Linguistics, 2022, DOI:10.48550/arXiv.2203.12918.
doi: 10.48550/arXiv.2203.12918
|
[21] |
Guo F, Luo Y, Yang L Y, et al. SciMine: an efficient systematic prioritization model based on richer semantic information. Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information, 2023, DOI: 10.1145/3539618.3591764.
doi: 10.1145/3539618.3591764
|
[22] |
Yang Z J, Wang Y K, Zhang L J. AI becomes a masterbrain scientist. bioRxiv, 2023, DOI: 10.1101/2023.04.19.537579.
doi: 10.1101/2023.04.19.537579
|
|
Viewed |
|
|
|
Full text
|
|
|
|
|
Abstract
|
|
|
|
|
Cited |
|
|
|
|
|
Shared |
|
|
|
|
|
Discussed |
|
|
|
|