Research on Evolution of Gene Editing Technology Based on Patent Analysis and Social Network Analysis

doi:10.13560/j.cnki.biotech.bull.1985.2020-1139

Abstract

Abstract:

Gene editing has shown great application value in the fields of agriculture,industry and biomedicine. The research of its evolutionary trend and evolutionary law are of great significance to the relevant decision makers in formulating technology strategies. Based on the Derwent patent database,this article makes an overall analysis of the research progress of gene editing technology. The evolution process of the technology is revealed by analyzing the patent application situation,national and regional distribution,main patentees and core technology topics of gene editing technology. The results show that:1）From the perspective of patent application trend,gene editing technology is currently in a high-speed development stage. 2）The number of patent applications in developed countries is still in a dominant position,while China plays an important role in protecting patent intellectual property rights,attracting many high-quality patents. 3）Compared with foreign patentees,China’s patentees’ comprehensive strength has improved significantly,but there is still a lack of direct contact with enterprises. 4）The development direction of gene editing is mainly affected by social needs. Reducing potential risks through optimization technology is an important goal in the future.

Key words: gene editing technology, evolutionary analysis, patent analysis, social network analysis

LIU Jia, WEI Jia-qi, LIU Yu-qin, SHI Ge-ge, GUO Jing. Research on Evolution of Gene Editing Technology Based on Patent Analysis and Social Network Analysis[J]. Biotechnology Bulletin, 2021, 37(12): 274-284.

Figures/Tables 15

References 22

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专利权人 Patentee	专利总数 Total number of patents	Degree	Betweennees	所属国家 Country	涉及年份 Year	近3年专利占比 Proportion of patents in the past three years/%
麻省理工学院	133	0.210 5	0.105 3	USA	1995-2019	52.6
哈佛大学	113	0.210 5	0.105 3	USA	1990-2019	63.7
加州大学	107	0.315 8	0.251 5	USA	1996-2019	61.7
Broad研究所	95	0.210 5	0.097 5	USA	2012-2019	61.1
先锋国际良种公司	77	0.052 6	0.070 2	USA	1991-2019	57.1
Cellectis公司	70	0	0	France	2002-2019	20.0
江南大学	66	0	0	China	2006-2019	57.6
上海交通大学	62	0	0	China	2003-2019	45.2
天津科技大学	43	0	0	China	2008-2019	74.4
Sangamo公司	42	0.052 6	0.070 2	USA	2000-2019	23.8
CRISPR Therapeutics AG	40	0	0	Switzerland	2016-2019	92.5
芜湖英特菲尔生物制品产业研究院	40	0	0	China	2017-2018	100
Editas Medicine公司	38	0	0	USA	2015-2019	94.7
宾夕法尼亚大学	36	0.052 6	0.070 2	USA	1997-2019	80.6
GEN HOSPITAL CORP	36	0.157 9	0.093 6	Netherlands	2006-2019	69.4
中国科学院上海生命科学研究院	36	0	0	China	2010-2019	72.2
浙江大学	35	0	0	China	2003-2019	65.7
孟山都公司	34	0	0	USA	1999-2019	47.1
美国卫生与公众服务部	33	0.210 5	0.074 1	USA	1993-2019	36.4
华中农业大学	33	0	0	China	2004-2019	75.8

专利权人 Patentee	专利总数 Total number of patents	Degree	Betweennees	所属国家 Country	涉及年份 Year	近3年专利占比 Proportion of patents in the past three years/%
麻省理工学院	133	0.210 5	0.105 3	USA	1995-2019	52.6
哈佛大学	113	0.210 5	0.105 3	USA	1990-2019	63.7
加州大学	107	0.315 8	0.251 5	USA	1996-2019	61.7
Broad研究所	95	0.210 5	0.097 5	USA	2012-2019	61.1
先锋国际良种公司	77	0.052 6	0.070 2	USA	1991-2019	57.1
Cellectis公司	70	0	0	France	2002-2019	20.0
江南大学	66	0	0	China	2006-2019	57.6
上海交通大学	62	0	0	China	2003-2019	45.2
天津科技大学	43	0	0	China	2008-2019	74.4
Sangamo公司	42	0.052 6	0.070 2	USA	2000-2019	23.8
CRISPR Therapeutics AG	40	0	0	Switzerland	2016-2019	92.5
芜湖英特菲尔生物制品产业研究院	40	0	0	China	2017-2018	100
Editas Medicine公司	38	0	0	USA	2015-2019	94.7
宾夕法尼亚大学	36	0.052 6	0.070 2	USA	1997-2019	80.6
GEN HOSPITAL CORP	36	0.157 9	0.093 6	Netherlands	2006-2019	69.4
中国科学院上海生命科学研究院	36	0	0	China	2010-2019	72.2
浙江大学	35	0	0	China	2003-2019	65.7
孟山都公司	34	0	0	USA	1999-2019	47.1
美国卫生与公众服务部	33	0.210 5	0.074 1	USA	1993-2019	36.4
华中农业大学	33	0	0	China	2004-2019	75.8

主题词 Subject	IDF因子 IDF factor	度中心度 Degree centrality	网络密度 Network density
Natural cell strain	3.303 22	32.734	0.094 7
Type B hepatitis	3.303 22	32.734
HBs antibody	3.303 22	32.734
HBs antigen	3.303 22	32.734
Selectable marker	2.833 21	18.934
DNA construct	2.610 07	16.533
Plant cell	1.868 13	11.793
Nucleotide sequence	1.478 67	11.300
Transgenic plant	2.204 61	10.365
Cell line	2.022 28	8.269
DNA sequence	1.275 07	6.479
Recombinant plasmid	2.022 28	6.000
Base pairs	2.966 75	6.000
Host cell	1.734 60	4.777
DNA fragment	1.868 13	0
Genetic engineering	0	0
Hepatitis B virus	2.715 43	0
Recombinant DNA	2.022 28	0
Eukaryotic cell	2.966 75	0
Genome DNA	2.715 43	0

主题词 Subject	IDF因子 IDF factor	度中心度 Degree centrality	网络密度 Network density
Natural cell strain	3.303 22	32.734	0.094 7
Type B hepatitis	3.303 22	32.734
HBs antibody	3.303 22	32.734
HBs antigen	3.303 22	32.734
Selectable marker	2.833 21	18.934
DNA construct	2.610 07	16.533
Plant cell	1.868 13	11.793
Nucleotide sequence	1.478 67	11.300
Transgenic plant	2.204 61	10.365
Cell line	2.022 28	8.269
DNA sequence	1.275 07	6.479
Recombinant plasmid	2.022 28	6.000
Base pairs	2.966 75	6.000
Host cell	1.734 60	4.777
DNA fragment	1.868 13	0
Genetic engineering	0	0
Hepatitis B virus	2.715 43	0
Recombinant DNA	2.022 28	0
Eukaryotic cell	2.966 75	0
Genome DNA	2.715 43	0

主题词 Subject	IDF因子 IDF factor	度中心度 Degree centrality	网络密度 Network density
Biological sample	1.922 65	44.496	0.647 4
Contiguous nucleotides	2.277 69	42.217
Nucleic acid	1.325 97	41.981
Mature form	2.987 36	39.012
Test compound	2.229 68	38.442
Gene product	1.899 93	38.299
Fusion protein	1.528 75	34.985
Plant cell	1.706 43	32.862
Hybridization complex	2.922 83	30.708
Isolated polypeptide	1.725 12	30.219
Isolated polynucleotide	1.536 53	29.627
Amino acid sequence	0.875 13	27.723
Gene expression	1.282 62	26.028
Transgenic plant	1.969 72	25.165
Host cell	0.711 81	21.987
Immune response	2.198 91	21.368
Candidate compound	2.559 92	21.237
Nucleotide sequence	0.592 50	20.104
Expression vector	1.246 90	19.426
DNA sequence	1.022 59	11.494