The recent outbreak of one of the RNA viruses (2019-nCoV) has affected most of the population and the fatalities reported may label it as a modern-day scourge. Active research on RNA virus infections and vaccine development had more commercial impact which leads to an increase in patent filings. Patents are a goldmine of information whose mining yields crucial technological inputs for further research. In this research article, we have investigated both the patent applications and granted patents, to identify the technological trends and their impact on 2019-nCoV infection using biotechnology-related keywords such as genes, proteins, nucleic acid etc. related to the RNA virus infection. In our research, patent analysis was majorly focused on prospecting for patent data related to the RNA virus infections. Our patent analysis specifically identified spike protein (S protein) and nucleocapsid proteins (N proteins) as the most actively researched macromolecules for vaccine and/or drug development for diagnosis and treatment of RNA virus based infectious diseases. The outcomes of this patent intelligence study will be useful for the researchers who are actively working in the area of vaccine or drug development for RNA virus-based infections including 2019-nCoV and other emerging and re-emerging viral infections in the near future.
For FULL-TEXT https://doi.org/10.1016/j.ijbiomac.2022.08.169
Author(s): Pratap Devarapalli, Pragati Kumari, Seema Soni, Vandana Mishra, Saurabh Yadav
Organization(s): University of Tasmania, Queensland University of Technology, H.N.B. Garhwal University
Source: International Journal of Biological Macromolecules
Artificial intelligence (AI) is emerging as a technology at the center of many political, economic, and societal debates. This paper formulates a new AI patent search strategy and applies this to provide a landscape analysis of AI innovation dynamics and technology evolution. The paper uses patent analyses, network analyses, and source path link count algorithms to examine AI spatial and temporal trends, cooperation features, cross-organization knowledge flow and technological routes. Results indicate a growing yet concentrated, non-collaborative and multi-path development and protection profile for AI patenting, with cross-organization knowledge flows based mainly on interorganizational knowledge citation links.
Full-Text available at https://doi.org/10.1371/journal.pone.0262050
Author(s): Na Liu, Philip Shapira, Xiaoxu Yue, Jiancheng Guan
Organization(s): Shandong Technology and Business University, University of Manchester, Tsinghua University, University of Chinese Academy of Sciences
Source: PLoS ONE
Patent mining and patent analysis of patented technologies will help protect the interests of intellectual property rights and provide enterprises with correct scientific research directions. In order to study the profitable patents of pharmaceutical companies, this paper proposes an Abstractive RL-LSTM neural network method based on patent texts. The reinforcement learning method is introduced into LSTM. The purpose is to rely on Q-learning to learn the relationship between the main layers. The two parallel layers share the weight of attention from the Q value, and realize the hierarchical control between the LSTM structure of the patent document and the LSTM structure of the sentence. The experimental results show that compared with other methods, the method proposed in this paper can further improve the ROUGE index and alleviate the dependence of the decoder on the input.
The team uses Derwent Data Analyzer to provide information about patent trends. Globally, until August 2020, there are a total of 192 patents on gene therapy.
Author(s): Yong Ji
Organization(s): Renmin University of China
Source: 7th International Conference on Systems and Informatics (ICSAI)
In accordance with the UN Sustainable Development Goals (SDGs), several SDGs target global food issues, including zero hunger (food security and sustainable agriculture), responsible consumption and production (food losses), climate action (greenhouse gas emissions from food waste), and partnerships for the goals (research collaboration). As such, it is vital to identify technology and market opportunities to support advanced development by exploring scientific and technological research on such SDGs. The significance of technological innovation and evaluations of activity, productivity, and collaboration aids and guides future research streams. Motivated by the growing severity of the global food waste crisis, this paper focuses on the case study of shelf-life extension technology for food and applies a scientometric analysis of patents based on text mining. VantagePoint was used to analyze 2516 patents issued between 2000 and 2020, with the aim of understanding the conceptual structure of knowledge and the social relationships among key players. The results indicate that the technology is experiencing a period of growth, and it can be clustered into five technology sectors. Across all technology clusters, China outperformed other countries in terms of the number of patents. Almost all of China’s patents applied for technology commercialization domestically, whereas other countries tended to apply for patents overseas to exploit opportunities. The findings have implications for both policymaking and strategic decision-making using a multi-layered network innovation system
For FULL-TEXT go to https://doi.org/10.3390/publications9040057
Author(s): Jakkrit Thavorn, Veera Muangsin, Chupun Gowanit, Nongnuj Muangsin
Organization(s): Chulalongkorn University
Source: Publications 2021
Emerging and resurgent arboviral diseases are a major public health problem for developing countries, particularly in Latin America and Africa, for the severity of their symptoms and lethality. Vaccines are recognized as the most powerful preventive, low-risk and cost-effective interventions. For this reason, vaccines against these arboviral diseases could have an extensive impact on global health. Nevertheless, many gaps persist in innovation and technological development of these vaccines and it is necessary and urgent to accelerate new funding mechanisms and incentives, such as “patent pools”, with active participation of manufacturers in developing countries, to assure their cost-effectiveness, efficacy and minimize their potential adverse effects. In this global scenario, intellectual property, especially patents documents, have emerged as a crucial issue for vaccine development. The global patent landscape for vaccines against these four arboviral diseases has undergone drastic changes in the past 5 years, with breakthroughs resulting from advances in molecular biology and genetic engineering: DNA vaccines, recombinant vaccines based on antigens expressed in vectors (viral, bacterial, yeast) and vaccines obtained through reverse vaccinology, with the selection of potential candidates at the genetic level rather than the protein level. Our main aim is to transcend the conventional debate on vaccine development and ethical, regulatory and policy issues, already explored in many scientific publications in the past three decades and determine which of these issues should be considered new and specific to this new perspective. Finally, an adequate use of patent documents, as indicated here, can be a valuable source of information, supporting technological prospect tools in more effective knowledge governance strategies.
Author(s): Cristina Possas, Adelaide M. S. Antunes, Flavia M. L. Mendes, Reinaldo M. Martins, Akira Homma
Organization(s): Oswaldo Cruz Foundation (FIOCRUZ), Federal University of Rio de Janeiro (UFRJ), National Institute of Industrial Property (INPI)
Source: Intellectual Property Issues in Microbiology (pp 337-352)
Technological developments in nanomaterials can be tracked using patent indicators. However, the traditional International Patent Classification indicators cannot be considered conclusive, since nanotechnology is not easily defined as a field of research as well as there are different types of nanomaterials not well delineated into hierarchical codes. Therefore, text mining approaches can be used to enhance patent analysis and provide insightful trends to support research and development, competitive intelligence, and policy making. This study aims at proposing a method to classify nanomaterials into main types and mapping technological developments using an advanced text mining-based method to compile patent indicators. Patent records were provided by Derwent Innovations Index database, which indexes an enhanced bibliographic data of patents filed worldwide. A comparison between the IPC indicators and those developed here by text mining is presented. We concluded that the proposed method provides useful outcomes for decision-making, technological forecasting, and material selection process.
Author(s): Douglas Henrique Milanez, Leandro Innocentini Lopes de Faria, Daniel Rodrigo Leiva
Organization(s): Federal University of São Carlos
Source: Journal of Nanoparticle Research
The purpose of this paper is to effectively evaluate the innovation ability and classification of technical talents in the intelligent robot field, and to be able to carry out adaptive learning and mining technical innovation talents according to the real-time change data corresponding to different indicators. Taking inventor’s patent information retrieved and cleaned from DI database as research object, it constructs the evaluation index system of technological innovation talents. It reduces the dimension of the index and cluster automatically, shows the visual effect, and mines the similar technical innovation talents through t-SNE algorithm. For a large number of patent information data, machine learning algorithm improves the traditional recognition method. According to inventor similarity, automatic classification is realized. Combined with DWPI manual code mining, the corresponding innovators and members of the technical team in the intelligent robot technology field were found. According to the results of visual dimensional reduction, the specific inventors can be traced. Machine learning algorithm t-SNE can reduce dimension and analysis clustering. It breaks the limitations of artificial statistics, deals with the larger order of magnitude data, and analyzes data timely, accurate and intuitive.
Author(s): Ning Zhao, Guohui Yang, Yang Cao
Organization(s): Harbin Institute of Technology
Source: 2020 IEEE International Conference on Artificial Intelligence and Computer Applications (ICAICA)
Quantum technologies attracted much attention for their disruptive potential in last two decades. The article analyzes the worldwide patent landscape for quantum technologies based on data extracted from Derwent Innovation and Web of Science. The quantum technologies were grouped
into three distinct technology areas of quantum computing, quantum communication and quantum sensing, to demonstrate detailed development and trends respectively. It shows that quantum technology is a highly competitive research field, and United States, China and Japan are the most prominent countries, in particular China made a great progress in recent years. United States has a significant advantage in the field of quantum computing, which is the most promising field, meanwhile China has a significant advantage in the field of quantum communication and succeeds in launching a quantum satellite.
Author(s): Juan Zhang, Qianfei Tian, Chuan Tang, Lina Wang, Jing Xu, and Junmin Fang
Organization(s): Chengdu Library and Information Center
Source: International Journal of Information and Education Technology
This work aims to analyse a relational structure of patents in automotive sector, especially for electric vehicles. The automotive industry is equivalent to 22% of Brazil’s industrial gross domestic product (GDP), 4% of Brazil’s total GDP, and worldwide it should reach a mark of 100 million vehicles sold by 2020. In recent decades, innovation processes have become a matter of survival for companies. Resource Based View admits that companies are looking for strategic resources that are a source of competitive advantage. This work comprises the automotive market as an organizational field in which the actors struggle to reach more favourable positions from the available resources. The network approach was used together with patent analysis to highlight the existing relationships within this industry in the construction of innovation, through the analysis of patents of high commercial value in the automotive sector, collected through the Derwent database.
For FULL-TEXT see http://leblog.gerpisa.org/node/4456
Author: Filippo Filippo Savoi de Assis
Organization: Universidade Federal de São Carlos – UFSCar
Source: Gerpisa Colloquium
As technological innovation plays important role in today’s knowledge economy, intellectual property as the most important output of technological development is valued highly for generating monopoly position in providing payoffs to innovation. Intellectual Property Management (IPM) helps organizations to identify, enhance and evaluate their technological strength. Patent portfolio Model (PPM) is built for assessing the advantages and disadvantages of organization, identifying the opportunities of development potentials and optimal distribution, to support the decision-making for optimizing resource allocation and developing layout for technical field. The case study of research institute in china show that this method is feasible and fulfilled the needs of different institutions, so as to provide suggestions for R&D technology management.
Author(s): Li Shuyin, Zhang Xian, Xu Haiyun, Fang Shu
Organization(s): Chengdu Library and Information Center, Chinese Academy of Sciences
Source: IEEE Xplore: 2019 Portland International Conference on Management of Engineering and Technology (PICMET)