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Encoder models at the European Patent Office: Pre-training and use cases

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-25 DOI: 10.1016/j.wpi.2025.102360

Volker D. Hähnke, Arnaud Wéry, Matthias Wirth, Alexander Klenner-Bajaja

Patents are organized using systems of technical concepts like the Cooperative Patent Classification. Classification information is extremely valuable for patent professionals, particularly for patent search. Language models have proven useful in Natural Language Processing tasks, including document classification. Generally, pre-training on a domain is essential for optimal downstream performance. Currently, there are no models pre-trained on patents with sequence length above 512. We pre-trained a RoBERTa model with sequence length 1024, increasing the fully covered claims sections from 12% to 53%. It has a ‘base’ configuration, reducing free parameters compared to ‘large’ models in the patent domain three-fold. We fine-tuned the model on classification tasks in the CPC, up to leaf level. Our tokenizer produces sequences on average 5% and up to 10% shorter than the general English RoBERTa tokenizer. With our pre-trained ‘base’ size model, we reach classification performance better than general English models, comparable to ‘large’ models pre-trained on patents. On the finest CPC granularity, 88% of test documents have at least one ground truth symbol in the top 10 predictions. Our CPC prediction models and data sets are publicly accessible. With the described procedures, we can periodically repeat pre-training and fine-tuning to cope with drift effects.

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引用次数: 0

Dynamics of regional intellectual property systems in China: A spatiotemporal synergy analysis

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-19 DOI: 10.1016/j.wpi.2025.102359

Li Chen , Liang Gao , Sibei Sheng

In the context of a burgeoning scientific and technological revolution and evolving norms, the push towards innovation-driven development has become crucial for achieving high-quality national growth. Such development is essential for enhancing the coordinated evolution of regional intellectual property (IP) systems. This study analyses data from 30 provincial units in China to develop an evaluation index system for regional IP synergy, encompassing the following four subsystems: IP creation, utilization, protection, and service. Using the entropy method, this study assesses the organizational level within each subsystem from 2009 to 2022 and evaluates the degree of coordinated development of regional IP systems. Furthermore, this work examines interregional disparities through the coefficient of variation, the Gini coefficient, and the Theil index. The findings reveal that the synergy of China's regional IP systems is characterized by growth fluctuations and significant regional disparities. Low levels of synergy can impede the enhancement of regional IP capabilities and reduce the efficiency of IP output. Disparities in synergy levels among regions are the main obstacles to connectivity and cooperation within the relevant network.

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引用次数: 0

Patenting telemedicine tools: A cross-country analysis of technologies related to remote patient monitoring

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-14 DOI: 10.1016/j.wpi.2025.102361

Gazala Parveen, Padmavati Manchikanti

Telemedicine has been practised since digital technology emerged in the mid-to-late 20th century. It evolved with technological advancements such as satellite communication in the 1960s, the internet in the 1990s and mobile health applications in the 2000s. Today, telemedicine forms a sub-set of digital health. In telemedicine, healthcare professionals provide medical services through information and communication technologies. The patenting of telemedicine tools is quite active, encompassing advancements in software applications, medical devices, and integrated systems for remote diagnosis, monitoring, and treatment. Effective protection of intellectual property for telemedicine tools relies on organised patent management and precise claim drafting. A study on the filing trends of the patents related to telemedicine tools and patent prosecution will give a better understanding of issues related to the patenting of such technologies. It highlights new developments that are expanding the scope of patent claims, particularly the increasing integration of telemedicine and software-enabled medical devices.

{"title":"Patenting telemedicine tools: A cross-country analysis of technologies related to remote patient monitoring","authors":"Gazala Parveen, Padmavati Manchikanti","doi":"10.1016/j.wpi.2025.102361","DOIUrl":"10.1016/j.wpi.2025.102361","url":null,"abstract":"<div><div>Telemedicine has been practised since digital technology emerged in the mid-to-late 20th century. It evolved with technological advancements such as satellite communication in the 1960s, the internet in the 1990s and mobile health applications in the 2000s. Today, telemedicine forms a sub-set of digital health. In telemedicine, healthcare professionals provide medical services through information and communication technologies. The patenting of telemedicine tools is quite active, encompassing advancements in software applications, medical devices, and integrated systems for remote diagnosis, monitoring, and treatment. Effective protection of intellectual property for telemedicine tools relies on organised patent management and precise claim drafting. A study on the filing trends of the patents related to telemedicine tools and patent prosecution will give a better understanding of issues related to the patenting of such technologies. It highlights new developments that are expanding the scope of patent claims, particularly the increasing integration of telemedicine and software-enabled medical devices.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":"Article 102361"},"PeriodicalIF":2.2,"publicationDate":"2025-04-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Expanding the concept of drug lifecycle management to chimeric antigen receptor T-cell products through product-patent linkage analysis

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-09 DOI: 10.1016/j.wpi.2025.102357

Yasuaki Kawai, Shingo Kano

Chimeric antigen receptor T (CAR-T) cell therapies have been actively developed, and five CAR-T products have been commercialized in Japan. Due to the ongoing development of CAR-T cell therapies, including next-generation variants, the patent landscape is expected to become increasingly complex. Therefore, understanding patent strategies for each CAR-T product is essential.

In the pharmaceutical industry, lifecycle management (LCM) centered on regulatory and patent protection has been implemented to maximize product value. While studies have reported CAR-T patents through patent landscape analysis to gain insights into the overall CAR-T technology, there is a lack of research on product-related patents for CAR-T products. As a result, the foundational knowledge regarding the LCM of CAR-T products remains unclear.

Therefore, we identified product-patent linkages for CAR-T products in the Japanese market by combining patent term extension (PTE) data with publicly available data and assessed the applicability of drug LCM to CAR-T products. Our identification of precise product-patent linkages revealed that all CAR-T products met the criteria for drug LCM. This study suggests that LCM activities can be implemented for CAR-T products and that the concept of drug LCM can be expanded to CAR-T products.

{"title":"Expanding the concept of drug lifecycle management to chimeric antigen receptor T-cell products through product-patent linkage analysis","authors":"Yasuaki Kawai, Shingo Kano","doi":"10.1016/j.wpi.2025.102357","DOIUrl":"10.1016/j.wpi.2025.102357","url":null,"abstract":"<div><div>Chimeric antigen receptor T (CAR-T) cell therapies have been actively developed, and five CAR-T products have been commercialized in Japan. Due to the ongoing development of CAR-T cell therapies, including next-generation variants, the patent landscape is expected to become increasingly complex. Therefore, understanding patent strategies for each CAR-T product is essential.</div><div>In the pharmaceutical industry, lifecycle management (LCM) centered on regulatory and patent protection has been implemented to maximize product value. While studies have reported CAR-T patents through patent landscape analysis to gain insights into the overall CAR-T technology, there is a lack of research on product-related patents for CAR-T products. As a result, the foundational knowledge regarding the LCM of CAR-T products remains unclear.</div><div>Therefore, we identified product-patent linkages for CAR-T products in the Japanese market by combining patent term extension (PTE) data with publicly available data and assessed the applicability of drug LCM to CAR-T products. Our identification of precise product-patent linkages revealed that all CAR-T products met the criteria for drug LCM. This study suggests that LCM activities can be implemented for CAR-T products and that the concept of drug LCM can be expanded to CAR-T products.</div></div>","PeriodicalId":51794,"journal":{"name":"World Patent Information","volume":"81 ","pages":""},"PeriodicalIF":2.2,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143799537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Do large language models understand patents? Enhancing patent classification through AI-generated summaries

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-05 DOI: 10.1016/j.wpi.2025.102353

Naoya Yoshikawa , Ralf Krestel

Patent classification plays a crucial role in intellectual property management, but remains a challenging task due to the complexity of patent documents. This study explores a novel approach to enhance automatic patent classification by leveraging summaries generated by large language models (LLMs). Our approach involves using the GPT-3.5-turbo model to create concise summaries from different sections of patent texts, which are then used to fine-tune the RoBERTa and XLM-RoBERTa models for classification tasks. We conducted experiments on English and Japanese patent documents using two datasets: the well-established USPTO-70k and the newly developed JPO-70k, that we specifically created for this study.

Our findings show that models trained on AI-generated summaries – particularly those derived from patent claims or detailed descriptions – outperform models trained on original abstracts in both subclass-level multi-label classification and subgroup-level single-label classification. In particular, using detailed description summaries improved the micro-average F1 score for subclass-level classification by 2.9 points on the USPTO-70k and 3.0 points on the JPO-70k, compared to using original abstracts.

These results indicate that LLM-generated summaries effectively capture information relevant to patent classification from various sections of patent texts, offering a promising approach to enhance the accuracy and efficiency of patent classification across different languages.

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引用次数: 0

Integrating Generative Artificial Intelligence techniques into technology function matrix analysis

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-04-03 DOI: 10.1016/j.wpi.2025.102352

Huei-Yu Wang , Shu-Hao Chang , Chia-Yi Chuang

This study proposes a novel method for automating the construction of technology-function matrices using generative artificial intelligence (GAI), specifically focusing on quantum technologies. By leveraging GAI to analyze International Patent Classification (IPC) definitions and benchmark reports, we developed a system that rapidly generates technology-function matrices, significantly reducing the time required for manual analysis. The method was applied to 2,399 quantum technology patents from 2023 to March 2024, covering four key areas: secure communications, computing, quantum simulators, and sensors. This approach not only aids government agencies in identifying new technological opportunities but also facilitates the industrialization of potential technologies. By combining GAI with established analytical frameworks, this study contributes to both the theoretical understanding and practical application of patent analysis in emerging fields.

引用次数: 0

Knowledge flows in technology-intensive publicly listed company - Evidence from Chinese patent citation data

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-29 DOI: 10.1016/j.wpi.2025.102354

Shi Chen , Yifa Wang

This empirical study utilizes patent citations from technology-intensive publicly listed companies in China between 2000 and 2019 to analyze the current state of knowledge flow within and among these companies. While capital markets are crucial for innovation, the extent to which publicly listed firms facilitate knowledge flow remains unclear. This research delineates the circulation of technological knowledge both intra- and inter-company, across similar and disparate industries, and between listed companies and non-listed innovative entities. The findings indicate a pronounced tendency among technology-intensive listed companies to cite their patents extensively. Self-citations comprise nearly 60 % of total citations, suggesting that technological knowledge primarily circulates within individual companies. Furthermore, the exchange of technological knowledge among different listed companies within the same industry is notably sparse, with only a fractional increase in the frequency of knowledge flows within the industry compared to across industry boundaries. Predominantly, the technological knowledge that technology-intensive listed companies acquire from non-listed innovative entities stems from domestic unlisted companies, with foreign entities and universities contributing to a lesser extent. When examining the spillover of technological knowledge to non-listed innovative entities, it is observed that other non-listed companies predominantly absorb such knowledge, with universities and individual innovators receiving lesser proportions. Finally, this study is significant as it provides empirical evidence on the flow of technological knowledge within and between publicly listed technology-intensive companies in China, revealing the dominance of self-citations and limited cross-company knowledge exchange. By analyzing patent citation data, this research provides valuable insights into the interactions between listed companies and non-listed innovative entities. The findings highlight the significant role of non-listed firms, universities, and foreign entities in shaping technological development. Strengthening these connections can further foster innovation and en hance knowledge diffusion across sectors.

本实证研究利用 2000 年至 2019 年间中国技术密集型上市公司的专利引用情况，分析这些公司内部和之间的知识流动现状。虽然资本市场对创新至关重要，但上市公司在多大程度上促进了知识流动仍不清楚。本研究描述了技术知识在公司内部和公司之间、同类行业和不同行业之间以及上市公司和非上市创新实体之间的流通情况。研究结果表明，技术密集型上市公司有广泛引用其专利的明显趋势。自我引用占总引用量的近 60%，这表明技术知识主要在单个公司内部流通。此外，同一行业内不同上市公司之间的技术知识交流明显稀少，与跨行业相比，行业内的知识流动频率仅有零点几的增长。技术密集型上市公司从非上市创新实体获得的技术知识主要来自国内非上市公司，外国实体和大学的贡献较小。在研究技术知识向非上市创新实体的溢出时，发现其他非上市公司主要吸收这些知识，而大学和个人创新者获得的比例较小。最后，本研究的重要意义在于为中国技术密集型上市公司内部和之间的技术知识流动提供了实证证据，揭示了自我引用占主导地位和跨公司知识交流有限的问题。通过分析专利引用数据，本研究为上市公司与非上市创新实体之间的互动提供了有价值的见解。研究结果凸显了非上市公司、大学和外国实体在影响技术发展方面的重要作用。加强这些联系可以进一步促进创新，推动跨行业的知识传播。

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引用次数: 0

Progress in patent technologies for methane catalytic combustion catalysts research

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-27 DOI: 10.1016/j.wpi.2025.102355

Bo Yuan , Tao Zhu , Meidan Wang , Xueli Zhang , Chen Li , Xinyue Zhang , Xudong Xu , Qian Sun

Catalytic combustion is an important approach to the effective utilization of methane, with the key being the search for efficient catalysts to maximize catalytic activity and resistance to poisoning. This work is based on the IncoPat commercial global patent database, combined with search results from the China Patent Abstracts database and the Derwent World Patents Index database, employing patent analysis methods to conduct a comprehensive analysis of the development trends in the global methane catalytic combustion catalyst materials technology field. By analyzing the trends in patent application and patent family numbers, the distribution of applicant countries/organizations, and leading applicants, this study summarizes the classification, preparation methods, and other technical key points of methane catalytic combustion catalyst materials, clarifying the latest developments in global methane catalytic combustion catalyst materials technology. This provides technical references for companies producing methane combustion catalytic materials in terms of product development and patent strategy layout, and supports the rapid development of the global methane combustion catalytic materials industry. The research findings indicate that global methane catalytic combustion catalyst technology is in a phase of rapid development, with research and applications in this field accelerating globally among countries and organizations, displaying intense technological competition and cooperation trends. Future research will focus on enhancing the activity, stability, and resistance to poisoning of catalysts, to aid in methane reduction and provide technical support for achieving global climate goals.

催化燃烧是有效利用甲烷的重要途径，关键在于寻找高效催化剂，最大限度地提高催化活性和抗中毒能力。本研究基于 IncoPat 全球商业专利数据库，结合中国专利文摘数据库和德文特世界专利索引数据库的检索结果，采用专利分析方法，对全球甲烷催化燃烧催化剂材料技术领域的发展趋势进行了全面分析。本研究通过对专利申请量、专利族数量变化趋势、申请人国别/机构分布、主要申请人等方面的分析，总结了甲烷催化燃烧催化剂材料的分类、制备方法等技术要点，阐明了全球甲烷催化燃烧催化剂材料技术的最新发展动态。这为甲烷燃烧催化材料生产企业在产品研发、专利战略布局等方面提供了技术参考，助力全球甲烷燃烧催化材料产业的快速发展。研究结果表明，全球甲烷催化燃烧催化剂技术正处于快速发展阶段，各国、各组织在该领域的研究和应用在全球范围内加速推进，呈现出激烈的技术竞争与合作趋势。未来的研究重点将放在提高催化剂的活性、稳定性和抗中毒能力上，以帮助甲烷减排，为实现全球气候目标提供技术支持。

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引用次数: 0

Literature listing

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-24 DOI: 10.1016/j.wpi.2025.102351

Susan Bates (Independent Researcher)

Welcome to the latest quarterly Literature Listing intended as a current awareness service for readers indicating newly published books, journal, and conference articles on IP management; Information Retrieval Techniques; Patent Landscapes; Education & Certification; and Legal & Intellectual Property Office Matters. The current Literature Listing was compiled mid-February 2025. Key resources include Scopus, Digital Commons, publishers' RSS feeds, and serendipity! This article gives a selection of interesting references to whet your appetite - the full list of references can be found in the companion datafile.

引用次数: 0

Patent litigation mining using a large language model—Taking unmanned aerial vehicle development as the case domain

IF 2.2 Q2 INFORMATION SCIENCE & LIBRARY SCIENCE

World Patent Information

Pub Date : 2025-03-01 DOI: 10.1016/j.wpi.2024.102332

Amy J.C. Trappey , Shao-Chien Chou , Gi-Kuen J. Li

As unmanned aerial vehicle (UAV), also called “drone”, swiftly advances with innovative functions and applications, the surge in patent applications has profoundly reshaped the intellectual property (IP) landscape in the UAV industry, leading to a growing number of litigations. This study is structured in two phases, aiming to develop an intelligent approach to analyzing the trend and evolution of patent litigations. The first phase involves macro- and micro-patent analyses of the related technology domain. Macro patent analysis elucidates the fundamental patent information in the drone industry, while micro patent analysis leverages the technology function matrix (TFM) to identify R&D hotspots and potentials. The second phase involves litigation (judgement) mining based on large language model (LLM). Beginning with the construction of a knowledge ontology, the domain infringement landscape can be detected through TFMs. A comparative analysis of the two-phase TFMs (i.e., both TFMs of patent and infringement allocations) is then conducted to pinpoint the key legal actions and the relevant technology. To drill deeper in infringement mining, dynamic topic modeling (DTM) is applied to analyze trends and dynamics in drone controller technology over time. This study aims to strengthen IP protection by developing an intelligent litigation mining approach that adopts large language model (LLM) and uses UAV/drone litigation studies as examples to show how the approach being applied in the industry.

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