Evidence map›Paper›PMID 35847804›Full record

ArticleFrontiers in medicine2022

What, Where, When and How of COVID-19 Patents Landscape: A Bibliometrics Review.

Kunmeng Liu, Xiaoming Zhang, Yuanjia Hu, Weijie Chen, Xiangjun Kong, Peifen Yao, Jinyu Cong, Huali Zuo, Jian Wang, Xiang Li and 1 more

Abstract read
In one paragraph

Article in Frontiers in medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Kunmeng LiuCenter for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China.
Xiaoming ZhangDepartment of Cardiovascular Surgery, The Affiliated Hospital of Qingdao University, Qingdao, China.
Yuanjia HuState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, Macao SAR, China.
Weijie ChenState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, Macao SAR, China.
Xiangjun KongState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, Macao SAR, China.
Peifen YaoState Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao, Macao SAR, China.
Jinyu CongCenter for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China.
Huali ZuoWarshel Institute for Computational Biology, The Chinese University of Hong Kong, Shenzhen, Hong Kong SAR, China.
Jian WangScience College, Shandong Jiaotong University, Jinan, China.
Xiang LiCenter for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China.
Benzheng WeiCenter for Medical Artificial Intelligence, Shandong University of Traditional Chinese Medicine, Qingdao, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

bibliometric patent analysiscitation networkcoronavirusCOVID-19patent landscapepatent miningsocial network analysis

Identifiers

PMID35847804
PMCPMC9283760

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.