International Patent Research Articles

UNLOCKING THE BRAZILIAN POTENTIAL OF FOOD TECHNOLOGIES TO ATTAIN SDG 2 – ZERO HUNGER

Brazil is working towards achieving United Nations Sustainable Development Goal 2 (SDG 2) of Zero Hunger, but reapeared on the world hunger map in 2019-20. This study seeks to identify the technologies existing in Brazil to address food security challenges effectively. A total of 5,084 patents from 45 food technological fields were analyzed in the Worldwide Espacenet database, using the International Patent Classification (IPC), spanning from 2000 to 2019. The key technologies comprise cocoa products, flour/dough, animal food, dairy products, preserved/ripened/canned products, nutritional modification/dietary products, microorganisms/enzymes for food, coffee/tea, sucrose production, new plants, and seafood. Academic patents encompass high-nutritional-value biodiversity products, indicating potential future specialties. Conversely, non-academic technologies mainly revolve around traditional colonial products exported as low-priced commodities.

Cross‐Border Patenting and the Margins of International Trade

ABSTRACTThis paper investigates the impact of cross‐border patenting on the margins of international trade using disaggregated data on international patenting and trade flows for a broad cross‐section of countries globally from 1995 to 2018. We develop a theoretical framework of trade and firms' patenting decisions that motivates our empirical analysis. The main results reveal that cross‐border patenting has a larger effect on the extensive margin of trade compared to the intensive margin. This finding suggests that firms tend to seek patent protection in international markets prior to entering those markets with new products, rather than with their existing products.

Exploring pre-diagnosis hospital contacts in women with endometriosis using ICD-10: a Danish case-control study.

How does pre-diagnosis use of hospital care differentiate between women later diagnosed with endometriosis and age-matched controls without a diagnosis? Women with hospital-diagnosed endometriosis had more frequent hospital contacts in the 10 years leading up to the diagnosis compared to women without a diagnosis of endometriosis, and the contacts were related to registered diagnoses in nearly all of the included ICD-10 chapters for the entire period. Only a few studies have investigated the utilization of health care among women with endometriosis in the time before diagnosis, but current research shows that women with endometriosis have a higher utilization compared to women without diagnosed endometriosis. To our knowledge, no study has investigated the type of contact related to the higher utilization by using the ICD-10 diagnoses registered to the hospital contact. This study was conducted as a national Danish registry-based case-control study of 129696 women. Cases were women with a first-time hospital-based diagnosis of endometriosis between 1 January 2000 and 31 December 2017. Using density sampling, we identified 21616 cases. Each case was matched on age at the date of diagnosis (index date) to five women without hospital-diagnosed endometriosis (n = 108080) at the time of matching. The utilization and registered ICD-10 diagnoses related to the hospital contact were included for the 10 years before the index date. The probability of having a high number of hospital contacts (six or more) was more common among women with endometriosis (68.6%) compared to women without endometriosis (55.7%) In general, women without endometriosis were more likely to have fewer than six contacts. The diagnoses registered to the contact among cases were related to a greater variety of ICD-10 chapters when compared to controls with the same number of contacts. For nearly all of the included ICD-10 chapters, women with endometriosis were more likely to have a diagnosis over the entire period compared to controls, with the only exception being in the chapter related to pregnancy. Our results are only applicable for women with hospital-based diagnosed endometriosis since we were not able to include women diagnosed at the general practitioner or private gynecologists. We were not able to make a causal interpretation, as we do not have information on the onset of symptoms of the included diseases. The association may be overestimated due to detection bias. However, a sensitivity analysis only changed the results slightly, indicating a low risk of this bias. This study is in accordance with previous studies on the subject, indicating that the utilization of health care prior to endometriosis is not necessarily restricted to endometriosis-related symptoms and that endometriosis can be associated with many other diseases. Future studies may explore hospital contacts and causes/diagnoses following the endometriosis diagnosis to further shed light on whether our results are due to a pattern of multiple pathologies or rather an expression of misdiagnoses among women with endometriosis before diagnosis. This study is supported by grants from the project Finding Endometriosis using Machine Learning (FEMaLe/101017562), which has received funding from The European Union's Horizon 2020 research and innovation program and Helsefonden (21-B-0141). A.W.H. received grant funding from NIHR, CSO, Roche Diagnostics, and Wellbeing of Women. A.W.H.'s institution received consultation fees from Theramex, Joii, Gesynta, and Gedeon Richter. A.W.H.'s institution received honoraria for lectures from Theramex and Gedeon Richter. A.W.H. is listed as co-inventor on a patent application (UK Patent App No. 2217921.2, International Patent App No. PCT/GB2023/053076). P.T.K.S.'s institution (University of Edinburgh) received consultation fees from Gesynta Pharma AB and BenevolentAI Bio Ltd. P.T.K.S's institution (University of Edinburgh) declares a patent application (UK Patent Application No. 2310300.5. Androgens in diagnostic strategies for endometriosis). P.T.K.S. is a treasurer of the World Endometriosis Society, Fellowship in the Royal Society of Edinburgh, and a Scientific Advisor of the Royal College of Obstetrics and Gynaecology. N/A.

Patent Development Strategy through PCT (Patent Cooperation Treaty) International Registration System: Challenge for Intellectual Property (IP) Attorneys in Indonesia

This research addresses the role of Intellectual Property (IP) Lawyers in patent registration and prosecution, particularly in the Patent Cooperation Treaty (PCT) context. In a complex research and development environment, an understanding of the risk of patent imitation is essential. This study aims to analyze the strategy of international patent registration through the PCT system and evaluate its effectiveness compared to national patent registration in Indonesia. This research uses a normative legal approach by analyzing the literature and practical aspects relating to international patent registration through the PCT system. The research findings show that Intellectual Property Lawyers need to have in-depth knowledge of the national and international patent registration systems. The research also highlights the challenges for inventors with limited budgets in choosing between national Patent and PCT registration, as well as the importance of strategic planning in registration to protect innovation. This research underscores the important role of IP Attorneys in assisting inventors through the patent registration process, both nationally and internationally, and emphasizes that the PCT system is a viable option to effectively protect innovation while managing costs.

Sanctions and Global Collaboration in Innovative Activities

ABSTRACTSanctions are one of the most prominent tools in international politics, designed to influence the target countries' policies by inflicting economic damage. Sanctions may also interfere with collaborative research relationships between countries, reducing knowledge diffusion and growth. In this paper, we study the impact of travel sanctions on patents that contain multiple inventors that are located in more than one country. Using a gravity model framework that includes 173 countries over 43 years, we find that travel sanctions negatively impact international patent collaboration. Specifically, travel sanctions reduce the intensity of collaboration by 43%. This impact only occurs during the sanctioning period, is persistent even in distant country pairs and is partially moderated by the availability of telecommunication technology.

Analysis of local and international patents for microfiltration process of different types of wine material

Analysis of local and international patents for microfiltration process of different types of wine material

Polysaccharide-Based Drug Carriers-A Patent Analysis.

Polysaccharide-based carriers as biomaterials for drug delivery have been inspiring scientists for years due to their exceptional characteristics, such as nontoxicity, biocompatibility, and degradability, as they are able to protect pharmaceutically active molecules and provide their controlled/modified release. This review focuses on selected drug delivery systems based on natural polymers, namely fucoidan, pullulan, dextran, and pectin, with the aim of highlighting published patent documents. The information contained in patents is very important because it is usually not published in any other document and is much less discussed as the state of the art in the scientific literature. The Espacenet-European Patent Office database and the International Patent Classification were used for the research to highlight the specific search procedure. The presented analysis of the innovative state of the art includes an overview from the first patent applications to the latest granted patents in this field.

A Review on Evolution and Challenges of Pharmaceutical Patent Protection in India

The Indian pharmaceutical patent system has undergone substantial changes through amendments to the Patents Act of 1970, particularly with the 2005 TRIPS compliance modifications. The system's cornerstone, Section 3(d), prevents patent extensions through minor molecular modifications unless significant therapeutic benefits are demonstrated. This provision gained global attention during the Novartis Glivec patent dispute, establishing India's firm stance on patentability criteria. India maintains specific safeguards within its patent framework, including a dual-opposition system and compulsory licensing provisions, which have proven crucial in maintaining medicine affordability. The Bayer-Natco case involving the cancer drug Nexavar highlighted the practical application of compulsory licensing to address public health needs. Patent office modernization efforts have targeted prolonged examination timelines and application backlogs, though administrative challenges persist. While multinational pharmaceutical companies express concerns about innovation protection, India's approach has enabled a robust generic drug industry that supplies affordable medicines globally. The patent system continues to evolve, balancing domestic healthcare requirements with international patent obligations. Recent technological upgrades in patent offices and refined examination guidelines demonstrate India's commitment to efficient patent administration while maintaining its public health priorities.

Tracking innovation via green patent classification systems: Are we truly capturing circular economy progress?

The transition to a circular economy (CE) is integral to the European Green Deal, where green technologies improve circularity across the supply chain. Emerging green patent classification systems can be used for finding and identifying trends in green technologies, as well as for tracking CE progress. The lack of harmonization in these systems for green and CE patents is reflected in differences within the emerging literature and what constitutes a CE framework, where metrics are overly-narrow. This creates challenges for strategic patent management in fostering CE innovation.This study evaluates how well patent classifications can be used to measure innovation in green technologies at the global level, and to indicate CE progress via these technologies at the European Union level. By comparing the International Patent Classification (IPC) system’s Green Inventory with the Cooperative Patent Classification (CPC) system, particularly the Y02W class (Climate Change Mitigation Technologies related to wastewater treatment or waste management) used by the EU, we first qualitatively establish the CPC has advantages in comprehensiveness, granularity, and lower risk of misclassification. Next, through an analysis of 1,634 patent abstracts within CPC Y02W filed from 2015-2021, we empirically assess the alignment between each of the 25 patent classes and the EU's 9 CE indicators, using Jacquard similarity index scoring (SIS) and ANOVA statistical tests for significance. We finally subsequently compare these abstracts with the 10 R-imperatives as a CE framework, also using keyword extraction.We identify gaps in the representation of certain CE indicators, and find that that some non-technological R-initiatives, such as repair and remanufacture, may be better captured by other CPC Y02 classes not currently included in EU monitoring. The study concludes that while the CPC Y02-tags provide a more detailed measure of green technology innovation globally and CE progress within the EU, further research is needed to refine the classification systems and ensure comprehensive monitoring of CE progress, particularly regarding non-technological innovations.

Plant Taxa as Raw Material in Plant-Based Meat Analogues (PBMAs)-A Patent Survey.

Background/Objectives: The environmental problems associated with meat production, the pain and distress of animals, and health problems have contributed to the increased appreciation of meat alternatives. Methods: The review of patented inventions presenting plant-based meat analogues (PBMAs) issued in the years 2014-2023 was conducted according to PRISMA statements across the ISI Web of Science, as well as Google Patents and Espacenet Patent Search engines. Results: The analysis of 183 patents showed an increase in patent numbers in the years 2020-2022, with the greatest number of patents developed by teams consisting of two authors. The authors and patent applicants were mainly affiliated with the United States, while Société des Produits Nestlé S.A. emerged as the leader among applicant institutions. The International Patent Classification (IPC) codes were given to 177 patents, which were mainly classified as Human Necessities (Section A). In total, inventors mentioned 184 taxa, including 28 genera, 1 section, 144 species, 5 subspecies and 6 varieties of vascular plants. The majority of taxa showed a high edibility rating and belonged to perennials, mainly herbaceous plants representing the families Fabaceae, Poaceae and Brassicaceae. The analysis of patents showed that plants are a promising source of protein, lipids, fibre, polyphenols, starch and gum in meat analogues. At the same time, the noticed slight use of numerous taxa, despite the substantial content of valuable constituents as well as high edibility rates, presumably might be caused by their underutilization in numerous regions of the world. Conclusions: The direction of future studies should focus on searching for novel plant-based meat analogues based on underutilized, promising plant sources and investigations of their usefulness.

Intellectual Property in Battery Cell Production: A Step-By-Step Regional Analysis

The decision to establish lithium-ion batteries (LIBs) as the technology of choice for electric vehicles (EVs) led to a remarkable and continuous growth in global demand for LIBs, further driven by the promotion of low-carbon transport. This promotion stimulated numerous technological innovations along the cell production value chain of LIBs, building on the implicit and explicit knowledge of the stakeholders in the sector. The assessment of this knowledge is enabled by data science methods that analyze innovative intellectual property (IP) and specialized Know-How, offering acceleration of development and cost savings. While previous data science approaches have focused on either materials in LIBs or holistic approaches to EVs, a void remains in the analysis of LIB cell production patents and the identification of less pronounced technology areas and potential white spots along the value chain. This work aims to address this void by identifying development pathways and investment opportunities for stakeholders and policy makers in LIB cell production. To achieve this, a new patent-based analysis framework is implemented, which addresses three sub-questions. First (1), the technological maturity of the state-of-the-art production processes from a regional perspective. Secondly (2), the international patenting trends to identify processes with the greatest potential for innovation. Finally (3), a network analysis approach to qualitatively assess the impact and competitiveness of various regions within each process and along the entire cell production value chain.To conduct the quantitative analysis, patent data from 1989 to 2023 was gathered and keywords were used to classify each cell production step. The patent quality was determined by calculating the mean eigenvector centralities for each region from the generated process-dependent networks. Eigenvector centralities are a valuable tool for gauging the impact of patents, as they describe the extent of connections between a single patent and other patents in the network.The study's results answered each sub-question, showing that (1) Japan’s technology lead was reversed after 2008 and overtaken by China in total patent numbers in 2018. Japan's former leadership and pioneering role in this field is reflected by a significant number of patents granted since 1993. In 2021, China holds the dominant position in technology patents across the whole production value chain with a share of 49%, witnessing the highest growth rate internationally since 2014. Moreover, the findings demonstrate (2) a maturation in the component production, expressed by a decrease in annual patenting, accompanied by a steady increase in patents for cell assembly processes to this date. The conditioning processes of the LIBs were identified as the most promising steps for innovation, with high potential to reduce costs and energy consumption. Finally, the qualitative analysis revealed (3) that the United States and Japan possess the broadest IP portfolios with the highest impact. The impact of China’s patent portfolio seems to be limited to partial connections within individual processes, thereby suggesting a preference on targeted innovations in one production step.In conclusion, this work has enabled the assessment of the state-of-the-art LIB cell production and identified technology areas and white spots. It will assist stakeholders and policy makers in selecting potential investments that can give them a competitive edge over other entities in the LIB market. In future work, the emphasis will be on the component production by implementing an analysis of the dry coating landscape. The introduction of dry coating can potentially eliminate the drying step, which is a major contributor to costs and energy consumption. Patent analysis will be adapted to evaluate trends in the key processes and the respective companies and institutions in this technology area.

Laser-based disassembly of end-of-life automotive traction batteries: A systematic patent analysis

Battery recycling is a vital component in the decarbonization of the transportation sector. The disassembly step represents a pivotal element within the process chain for battery recycling, as it paves the way for subsequent steps. Semi-destructive disassembly technologies will be key to developing efficient disassembly processes for end-of-life automotive traction batteries. Laser-based separation technologies have emerged as a promising emerging technological approach. Following a systematic search in multiple databases, the obtained records underwent a comprehensive descriptive analysis in terms of both regional and historical context, while key inventors and assignees were identified. Furthermore, citation networks have been identified to provide an overview of the patent landscape and the interrelations within this field. Moreover, an analysis concerning the International Patent Classification and the Cooperative Patent Classification was conducted. An in-depth analysis of relevant patents provides insights into the specific techno-strategic elements currently pursued. The study yields an implication and recommendation framework for research, industry, and policy makers to drive the industrialization of laser-based disassembly technologies as an avenue for efficient end-of-life automotive traction battery disassembly of the future. This framework enables relevant stakeholders to drive their techno-strategic developments in the field of laser-based disassembly, resulting in enhanced laser-based semi-destructive disassembly technologies.

Assessing Scientific Text Similarity: A Novel Approach Utilizing Non-Negative Matrix Factorization and Bidirectional Encoder Representations from Transformer

The patent serves as a vital component of scientific text, and over time, escalating competition has generated a substantial demand for patent analysis encompassing areas such as company strategy and legal services, necessitating fast, accurate, and easily applicable similarity estimators. At present, conducting natural language processing(NLP) on patent content, including titles, abstracts, etc., can serve as an effective method for estimating similarity. However, the traditional NLP approach has some disadvantages, such as the requirement for a huge amount of labeled data and poor explanation of deep-learning-based model internals, exacerbated by the high compression of patent content. On the other hand, most knowledge-based deep learning models require a vast amount of additional analysis results as training variables in similarity estimation, which are limited due to human participation in the analysis part. Thus, in this research, addressing these challenges, we introduce a novel estimator to enhance the transparency of similarity estimation. This approach integrates a patent’s content with international patent classification (IPC), leveraging bidirectional encoder representations from transformers (BERT), and non-negative matrix factorization (NMF). By integrating these techniques, we aim to improve knowledge discovery transparency in NLP across various IPC dimensions and incorporate more background knowledge into context similarity estimation. The experimental results demonstrate that our model is reliable, explainable, highly accurate, and practically usable.

Adaptive Taxonomy Learning and Historical Patterns Modeling for Patent Classification

Patent classification aims to assign multiple International Patent Classification (IPC) codes to a given patent. Existing methods for automated patent classification primarily focus on analyzing the text descriptions of patents. However, apart from the textual information, each patent is also associated with some assignees, and the knowledge of their previously applied patents can often be valuable for accurate classification. Furthermore, the hierarchical taxonomy defined by the IPC system provides crucial contextual information and enables models to leverage the correlations between IPC codes for improved classification accuracy. However, existing methods fail to incorporate the above aspects and lead to reduced performance. To address these limitations, we propose an integrated framework that comprehensively considers patent-related information for patent classification. To be specific, we first present an IPC codes correlations learning module to capture both horizontal and vertical information within the IPC codes. This module effectively captures the correlations by adaptively exchanging and aggregating messages among IPC codes at the same level (horizontal information) and from both parent and children codes (vertical information), which allows for a comprehensive integration of knowledge and relationships within the IPC hierarchical taxonomy. Additionally, we design a historical application patterns learning component to incorporate previous patents of the corresponding assignee by aggregating high-order temporal information via a dual-channel graph neural network. Finally, our approach combines the contextual information from patent texts, which encompasses the semantics of IPC codes, with assignees’ sequential preferences to make predictions. Experimental evaluations on real-world datasets demonstrate the superiority of our proposed approach over existing methods. Moreover, we present the model’s ability to capture the temporal patterns of assignees and the semantic dependencies among IPC codes.

Thermochromic Polymers in Food Packaging: A Comprehensive Systematic Review and Patent Landscape Analysis

This study addresses the gap in research on the application of thermochromic polymers (TPs) in food packaging and their potential for real-time temperature monitoring, aiding in the assessment of food quality and shelf-life. TPs exhibit a visible color change in response to temperature variations. A comprehensive systematic review (SR) across multiple engineering peer-review databases using predefined terms was conducted. Additionally, international patent databases were investigated using the same predefined terms. Independent experts reviewed the methodology to identify and address potential biases. A total of 288 eligible articles and 922 patents were identified. After a duplicate selection and extraction process according to the inclusion criteria, four related full-text publications were selected from the initial 288 articles, and five relevant patents were selected from the 922 patents. The qualitative review suggests that TPs hold significant promise as food packaging materials due to their unique physical properties. The study concludes that TPs offer valuable properties for the food packaging industry, meriting further investigation to exploit their benefits fully.

Cross-National Comparison of Technology Innovation Capabilities in Automation and Robotics

In today’s dynamic and global economic environment, technological innovations are a key determinant of international competitiveness. In the field of automation and robotics, the development of modern technologies is of particular significance, influencing not only industrial progress but also social aspects. Automation and robotics play a crucial role in the concept of modern industry, contributing to the creation of more sustainable, flexible, and human-centric production systems. The article aims to conduct an in-depth analysis of the patent activity in automation and robotics in Europe. Patent documentation serves as a source of knowledge about the directions of research, inventive activities, and consequently, the innovative and competitive potential of the economy. The number of patents over time reflects the dynamics of a country’s technological development. The article discusses the use of patent databases to evaluate a country’s innovation in automation and robotics. The conducted analysis of data on European countries enabled the identification of trends based on the International Patent Classification and specialisation from a geographical perspective using revealed comparative technological advantage. The European countries were classified using cluster analysis, demonstrating the diversity, and identifying leaders in each group.

A transfer learning based patent transfer prediction model: Discussion about the condition of China and U.S.

In the same patent classification, there are significant differences in the patent transfer quantity for different countries. For the countries with small patent transfer quantities, the performance of the patent transfer prediction is worse than that of high-transfer countries. To improve the performance of the patent prediction model learned for the low-transfer countries, we propose a transfer learning based patent transfer prediction model, for which the high-transfer countries are the source domain and the low-transfer countries are the target domain. In the model, the textual feature of each patent text is embedded using BERT-CNN with the parameters fine-tuned on the target domain from the source domain. The textual features are optimized to minimize the domain loss of Maximum Mean Discrepancy between source and target domain. What is more, we extract graph feature vectors by embedding the patent node in a three-layer heterogeneous network which consists of patent nodes, International Patent Classification nodes, consumer nodes, consumer location nodes and their relations. Finally, the patent text vectors, structural feature vectors, and graph feature vectors are spliced together to predict target domain patents transfer or not. The performance of the model is verified by some comparative experiments. The experimental results show that the proposed model outperforms significantly the baseline models in the values of Precision, Recall, and F1 of patent data improve by 6.47%, 6.54%, and 6.58% on average, respectively.

Exploring Electric Vehicle Patent Trends through Technology Life Cycle and Social Network Analysis

In response to environmental and energy challenges, electric vehicles (EVs) have re-emerged as a viable alternative to internal combustion engines. However, existing research lacks a comprehensive analysis of the technology life cycle of EVs in both global and South Korean contexts and offers limited strategic guidance. This study introduces a novel approach to address these gaps by integrating the S-curve model with social network analysis (SNA), time series analysis, and core applicant layouts. The study specifically utilizes the logistic curve to model technology growth. It applies SNA methods, including International Patent Classification (IPC) co-occurrence analysis and the betweenness centrality metric, to identify the stages of technological development and sustainable research directions for EVs. By analyzing patent data from 2004 to 2023, the study reveals that EV technologies have reached the saturation phase globally and in South Korea, with South Korea maintaining a two-year technological advantage. The research identifies sustainable research directions, including fast charging technology and charging infrastructure, battery monitoring and management, and artificial intelligence (AI) applications. Additionally, the study also determined the sustainability of these research directions by examining the sustainability challenges faced by EVs. These insights offer a clear view of EV technology trends and future directions, guiding stakeholders.

A CASE STUDY OF IMPLEMENTATION OF CIRCULAR ECONOMY PRINCIPLES TO WASTE MANAGEMENT: INTEGRATED TREATMENT OF CHEESE WHEY AND HI-TECH WASTE

In a global context characterized by severe environmental problems and increasing resource scarcity, waste represents both a challenge and an opportunity. This study aims to demonstrate with a real case the potential for optimizing the waste valorization action attainable through the synergic application of different treatments to residues of equally different nature and origin. In particular, bio-chemical (dark fermentation), chemical-physical (selective leaching) and thermo-chemical (hydrothermal carbonization) treatments were applied for the integrated valorization of whey from sheep cheese production and Hi-Tech waste (discarded electrical and electronic equipment). The treatments were applied at a laboratory scale on real samples of these residues. The organic acids used for selective leaching of valuable metals from Hi-Tech waste were obtained by dark fermentation of the cheese whey, while hydrothermal carbonization was used to convert the waste from previous stages into hydrochar feasible as solid fuel or soil improver. The dark fermentation tests have highlighted the possibility of recovering ≈ 100 g of organic acids from 1 L of whey; furthermore, it is also possible to recover bio-hydrogen depending on the operating conditions applied and the type of targeted organic acids. The leaching tests have demonstrated how the organic acids from whey fermentation have selective and quantitative mobilization capacities comparable to those of the same acids available on the market. The carbonization tests produced carbon-enriched hydrochar with promising fuel properties, as well as process waters suitable for anaerobic digestion with methane production. The results of the project led to the filing of an international patent.

Mapping the Nanotechnology Patent Landscape in the Field of Cancer.

Currently, cancer is still a significant disease that seriously endangers human health. Therefore, advanced diagnostic technology and treatment protocols are urgently needed. The rapid development of nanotechnology is expected to provide new ideas for cancer diagnosis and treatment. The research aims to comprehensively demonstrate the hotspots of nanotechnology applications in cancer. In this study, an International Patent Classification codes co-occurrence network is constructed to visualize the technology landscape by simultaneously locating and ranking technologies that play an integral role in nanotechnology diffusion and bridging in the field of cancer. In addition, community identification and topic modeling highlight the latent topics in patent documents. The visualization results of the patent network yield five main clusters: Cluster 0 is a nanoparticle composition delivery system with liposomes as the primary carrier. Cluster 1 is mainly represented by nano-immunotherapy with immune checkpoint inhibitors. Cluster 2 is nano phototherapy based on photodynamic therapy and photothermal therapy. Cluster 3 is diagnostic imaging involving nanotechnology. Cluster 4 is a drug delivery system with nanovesicles and albumin nanoparticles as carriers. It was found that carriers represented by liposomes, vesicles, and albumin nanoparticles are essential nanomaterials in the current anticancer drug delivery systems. Integrating next-generation immunosuppressants and nanotechnology will become an important development direction for future immunotherapy. Organic/inorganic nanomaterials are pivotal in cancer imaging diagnosis and phototherapy.