| Literature DB >> 35847804 |
Kunmeng Liu1,2, Xiaoming Zhang3, Yuanjia Hu4, Weijie Chen4, Xiangjun Kong4, Peifen Yao4, Jinyu Cong1,2, Huali Zuo5, Jian Wang6, Xiang Li1,2, Benzheng Wei1,2.
Abstract
Two years after COVID-19 came into being, many technologies have been developed to bring highly promising bedside methods to help fight this epidemic disease. However, owing to viral mutation, how far the promise can be realized remains unclear. Patents might act as an additional source of information for informing research and policy and anticipating important future technology developments. A comprehensive study of 3741 COVID-19-related patents (3,543 patent families) worldwide was conducted using the Derwent Innovation database. Descriptive statistics and social network analysis were used in the patent landscape. The number of COVID-19 applications, especially those related to treatment and prevention, continued to rise, accompanied by increases in governmental and academic patent assignees. Although China dominated COVID-19 technologies, this position is worth discussing, especially in terms of the outstanding role of India and the US in the assignee collaboration network as well as the outstanding invention portfolio in Italy. Intellectual property barriers and racist treatment were reduced, as reflected by individual partnerships, transparent commercial licensing and diversified portfolios. Critical technological issues are personalized immunity, traditional Chinese medicine, epidemic prediction, artificial intelligence tools, and nucleic acid detection. Notable challenges include balancing commercial competition and humanitarian interests. The results provide a significant reference for decision-making by researchers, clinicians, policymakers, and investors with an interest in COVID-19 control.Entities:
Keywords: COVID-19; bibliometric patent analysis; citation network; coronavirus; patent landscape; patent mining; social network analysis
Year: 2022 PMID: 35847804 PMCID: PMC9283760 DOI: 10.3389/fmed.2022.925369
Source DB: PubMed Journal: Front Med (Lausanne) ISSN: 2296-858X
FIGURE 1Current tendency for time and geographical distribution of COVID-19 patents. (A) The annual and cumulative number of COVID-19 patents. (B) The country landscape by nationalities of jurisdictions. The darker the color, the more patents. (C) The map shows the number of patent families by the top six locations of patent inventors temporally. (D) Violin plot of the time period between patent application and publication. The short white horizontal line is the median; the white dot is the mean; the black bar in the center of the violin is the interquartile range; and the black lines stretching from the bar are defined as the first quartile –1.5 IQR and third quartile + 1.5 IQR.
Leading COVID-19 patent assignees.
| Rank | Assignee | DWPI families | Patent files | Average | Type |
| 1 | Chinese Academy of Medical Sciences | 62 | 63 | 1.02 | A&G |
| 2 | PLA Academy of Military Medical Sciences | 53 | 53 | 1.00 | A&G |
| 3 | Sun Yat-sen University | 44 | 45 | 1.02 | A&G |
| 4 | Fudan University | 28 | 32 | 1.14 | A&G |
| 5 | West China Hospital Sichuan University | 27 | 28 | 1.04 | A&G |
| 6 | Chongqing Medical University | 27 | 27 | 1.00 | A&G |
| 7 | Suntrap Life Technologies Ltd. | 19 | 19 | 1.00 | C |
| 8 | Jiangsu Provincial Center for Disease Control and Prevention | 16 | 16 | 1.00 | A&G |
| 9 | Zhejiang University | 13 | 15 | 1.15 | A&G |
| 10 | Tsinghua University | 14 | 14 | 1.00 | A&G |
| 11 | Lovely Professional University | 13 | 14 | 1.08 | A&G |
| 12 | Shanghai Jiao Tong University | 13 | 14 | 1.08 | A&G |
| 13 | Chinese Centre for Disease Control and Prevention | 13 | 13 | 1.00 | A&G |
| 14 | Peking University | 13 | 13 | 1.00 | A&G |
| 15 | Jilin University | 10 | 13 | 1.30 | A&G |
| 16 | Bioscience (Tianjin) Diagnostic Technology Co., Ltd. | 12 | 12 | 1.00 | C |
| 17 | Shanghai National Engineering Research Center for Nanotechnology Co., Ltd. | 12 | 12 | 1.00 | C |
| 18 | ACROBiosystems Co., Ltd. | 11 | 11 | 1.00 | C |
| 19 | Dalian Polytechnic University | 11 | 11 | 1.00 | A&G |
| 20 | Shanghai Public Health Clinical Centre | 11 | 11 | 1.00 | A&G |
| 21 | Rigel Pharmaceuticals | 7 | 11 | 1.57 | C |
C, commercial assignee; A&G, industrial and academic assignee; Average, Average number of patents per DWPI family.
Type: Institutional type of assignee.
FIGURE 2Spatial and institutional dimensions of research collaboration. (A) The bar chart shows the patent numbers for each assignee type of institution. (B) Top collaboration partners. The nodes (organizational patent assignee colored with country) and edges (collaboration) in the network visualization map represent the co-assignee relations. The institutional collaboration network does not include the individual assignee and labels names of top active institutions by Cytoscape. (C) Networks of country relationship modes. Nodes (individual and organizational patent assignees) denote locations, and edges denote the count of domestic, bilateral, and multilateral country collaborations. Node size is scaled to the numerical value of the network degree (co-patent number), while the thickness of the edges is determined by the numerical value of the network weighted degree (frequency of cooperation). Countries are represented in different colors. The regional cooperation network is displayed in the “yFiles Organic layout” based on the force-directed layout paradigm by Cytoscape.
FIGURE 3Distribution of the types of functional classification of COVID-19 patents. (A) The temporal evolution of the leading 20 International Patent Classification (IPC) codes. (B) Sunburst chart by focused functions. The area of the graph represents the percentage of technology.
FIGURE 4Network visualization map of citations by COVID-19 patents. (A) Citation network illustrating the evidence sources cited in 117 recommendation patent documents. The larger the circle is, the more frequently the patents received citations. Lines represent the citation direction. The force-directed layout algorithm of “Fruchterman Reingold” by Gephi is used to make the network distribution. Different circle colors indicate different technologies. (B) The main path from the typical key-route citation weighted with the top 10 patents of citation out-degree. In the visual analysis of the main path based on patent citation, time was added to the technology trajectory calculated by Gephi software, which clearly shows the research focus and direction of this field in different time periods.