Preliminary Report on Patent Literature, Search Methodology and Patent Status of Medicines on the WHO EML 2009

Over the past several decades the World Health Organization (WHO) has produced the Essential Medicines List (EML) to assist countries in deciding what medicines should be essential and available in National Essential Medicine Lists.1 WHO, through the work of regional offices, supports nations using the EML to ensure the quality, availability, and affordability of pharmaceuticals required to promote and advance public health in nations across the globe. However in some cases, access to EML pharmaceuticals might be complicated by existing patents, i.e., where issued, patent rights might pose obstacles to access and inclusion in national EMLs. Indeed, in developed and emerging economy national jurisdictions patent protection may be in effect for a not insignificant number of the WHO EML pharmaceuticals (Figure 2A). However, in developing countries, it is uncertain whether these patents have been filed or issued. Without patent data predicated on an established, reproducible protocol for accessing and assembling patent information on the EML pharmaceuticals, discussions, debates and strategic approaches to understanding and managing patents with regard to access and delivery to developing countries remain in the dark. Indeed, it is absurd to make policy and formulate strategy without solid patent information: the critical foundation for rational debate. To analyze the degree and scope of patenting of EML pharmaceuticals, WIPO (with WHO) approached the Franklin Pierce Center for Intellectual Property at the University of New Hampshire School of Law, specifically the International Technology Transfer Institute (ITTI) to generate a preliminary overview of patents appurtenant to recently added pharmaceutical updates to the EML.2 As part of this work, with inputs from WHO and WIPO, ITTI developed novel methodology and a detailed protocol for identifying EML pharmaceutical patents in national jurisdictions, with an easily reproducible yet cost effective template. Herein is described the development of such a protocol and a preliminary pool of patent information that illustrates its utility. The protocol yields data in a layered approach thereby allowing a user to quickly and effectively obtain both broad and detailed patent information for medications on the WHO EML. In addition, the protocol can be used as an initial path for targeted strategic analysis of potentially relevant patent information in national jurisdictions. In sum, the objectives for this project were: To develop a robust methodology to assess the patent status of medicines on the WHO Model List of Essential Medicines; To place in the public domain a detailed report on the present (2010) patent status of medicines that were on patent in 2003 and those medicines added to the Model List since 2003 by country and level of development; and To analyze the patent status of these Essential Medicines by the development status of countries. The report describes the development of the protocol and presents a preliminary list of EML and corresponding patents in certain jurisdictions to illustrate the utility of the approach. Results will be discussed both in terms of global access and patents, and in the context of establishing standard, systematic, protocols for periodic patent searches related to EML content. 1 WORLD HEALTH ORGANIZATION, CONTINUITY AND CHANGE IMPLEMENTING THE THIRD WHO MEDICINES STRATEGY 2008--‐2013 20 (WHO Press, 3rd ed. 2009). 2 This report covers the EML up to and including updates until 2009

Natural Language Processing in-and-for Design Research

We review the scholarly contributions that utilise Natural Language Processing (NLP) methods to support the design process. Using a heuristic approach, we collected 223 articles published in 32 journals and within the period 1991-present. We present state-of-the-art NLP in-and-for design research by reviewing these articles according to the type of natural language text sources: internal reports, design concepts, discourse transcripts, technical publications, consumer opinions, and others. Upon summarizing and identifying the gaps in these contributions, we utilise an existing design innovation framework to identify the applications that are currently being supported by NLP. We then propose a few methodological and theoretical directions for future NLP in-and-for design research

A Comprehensive Classification of Business Activities in the Market of Intellectual Property Rights-related Services

Technology and intellectual property markets have witnessed great developments in the last few decades. Due to intellectual property rights gaining more importance and technology companies opening up their innovation processes, a wide range of intellectual property rights related services have emerged in the last two decades. The goal of this research is to develop a comprehensive classification system of intellectual property rights related services (IPSC). The classification is created by applying an ontology engineering process. The IPSC consists of 72 various IPR services divided into six main categories (100 Legal Service; 200 IP Consulting; 300 Matchmaking and Trading; 400 IP Portfolio Processing; 500 IPR-related Financial Service; 600 IPR-related Communication Service). The implications of the thesis are directed to policy makers, technology transfer managers, C-level executives and innovation researchers. The IPSC enables practitioners and researchers to organize industry data that can be thereafter analyzed for better strategy and policy making. In addition, this contributes towards organizing a more transparent and single intellectual property market.:Acknowledgements I Abstract II Contents IV List of Figures VI List of Tables VII 1. Introduction 1 1.1. Introduction to Technology Markets 1 1.2. Explanation of Key Concepts 5 1.3. Research Questions and Goals 9 1.4. Readers Guide 13 2. Literature Review 15 2.1. Intellectual Property Markets State of the Art Review 15 2.2. Ontology Engineering State of the Art Review 22 3. Methodology 26 3.1. Methontology 26 3.2. Planning the IPSC 29 3.3. Specification 30 3.4. Conceptualization 31 3.5. Formalization 32 3.6. Integration 32 3.7. Evaluation 33 3.8. Documentation 33 3.9. Realization and Maintenance 33 4. Data description and collection framework 34 5. Applying Methontology 46 5.1. Knowledge Acquisition and Planning the IPSC 46 5.2. Specification 46 5.3. Conceptualization 47 5.4. Formalization 54 100 Legal Service 56 200 IP Consulting 60 300 Matchmaking and Trading 65 400 IP Portfolio Processing 72 500 IPR-related Financial Service 76 600 IPR-related Communication Service 81 5.5. Integration 86 5.6. Evaluation 95 5.7. Documentation 104 5.8. Realization and Maintenance of the IPSC 106 6. Interview Results and Further Discussions 108 6.1. Implications for Industry 108 6.2. Contributions of the IPSC 110 6.3. Limitations of the IPSC and Future Work 112 7. Conclusions 116 References 120 List of experts interviewed and the date of interview 129 Appendices 13

Unbundling dynamic capabilities for inter-organizational collaboration

Purpose The purpose of this paper is to explore two distinct subsets of dynamic capabilities that need to be deployed when pursuing innovation through inter-organizational activities, respectively, in the contexts of broad networks and specific alliances. The authors draw distinctions and explore potential interdependencies between these two dynamic capability reservoirs, by integrating concepts from the theoretical perspectives they are derived from, but which have until now largely ignored each other – the social network perspective and the dynamic capabilities view. Design/methodology/approach The authors investigate nanotechnology-driven R&D activities in the 1995–2005 period for 76 publicly traded firms in the electronics and electrical equipment industry and in the chemicals and pharmaceuticals industry, that applied for 580 nanotechnology-related patents and engaged in 2,459 alliances during the observation period. The authors used zero-truncated Poisson regression as the estimation method. Findings The findings support conceptualizing dynamic capabilities as four distinct subsets, deployed for sensing or seizing purposes, and across the two different inter-organizational contexts. The findings also suggest potential synergies between these subsets of dynamic capabilities, with two subsets being more macro-oriented (i.e. sensing and seizing opportunities within networks) and the two other ones more micro-oriented (i.e. sensing and seizing opportunities within specific alliances). Practical implications The authors show that firms differ in their subsets of dynamic capabilities for pursuing different types of inter-organizational, boundary-spanning relationships (such as alliances vs broader network relationships), which ultimately affects their innovation performance. Originality/value The authors contribute to the growing body of work on dynamic capabilities and firm-specific advantages by unbundling the dynamic capability subsets, and investigating their complex interdependencies for managing different types of inter-organizational linkages. The main new insight is that the “linear model” of generating more innovations through higher inter-firm collaboration in an emerging field paints an erroneous picture of how high innovation performance is actually achieved

Query refinement for patent prior art search

A patent is a contract between the inventor and the state, granting a limited time period to the inventor to exploit his invention. In exchange, the inventor must put a detailed description of his invention in the public domain. Patents can encourage innovation and economic growth but at the time of economic crisis patents can hamper such growth. The long duration of the application process is a big obstacle that needs to be addressed to maximize the benefit of patents on innovation and economy. This time can be significantly improved by changing the way we search the patent and non-patent literature.Despite the recent advancement of general information retrieval and the revolution of Web Search engines, there is still a huge gap between the emerging technologies from the research labs and adapted by major Internet search engines, and the systems which are in use by the patent search communities.In this thesis we investigate the problem of patent prior art search in patent retrieval with the goal of finding documents which describe the idea of a query patent. A query patent is a full patent application composed of hundreds of terms which does not represent a single focused information need. Other relevance evidences (e.g. classification tags, and bibliographical data) provide additional details about the underlying information need of the query patent. The first goal of this thesis is to estimate a uni-gram query model from the textual fields of a query patent. We then improve the initial query representation using noun phrases extracted from the query patent. We show that expansion in a query-dependent manner is useful.The second contribution of this thesis is to address the term mismatch problem from a query formulation point of view by integrating multiple relevance evidences associated with the query patent. To do this, we enhance the initial representation of the query with the term distribution of the community of inventors related to the topic of the query patent. We then build a lexicon using classification tags and show that query expansion using this lexicon and considering proximity information (between query and expansion terms) can improve the retrieval performance. We perform an empirical evaluation of our proposed models on two patent datasets. The experimental results show that our proposed models can achieve significantly better results than the baseline and other enhanced models

Deep Learning for Technical Document Classification

In large technology companies, the requirements for managing and organizing technical documents created by engineers and managers have increased dramatically in recent years, which has led to a higher demand for more scalable, accurate, and automated document classification. Prior studies have only focused on processing text for classification, whereas technical documents often contain multimodal information. To leverage multimodal information for document classification to improve the model performance, this paper presents a novel multimodal deep learning architecture, TechDoc, which utilizes three types of information, including natural language texts and descriptive images within documents and the associations among the documents. The architecture synthesizes the convolutional neural network, recurrent neural network, and graph neural network through an integrated training process. We applied the architecture to a large multimodal technical document database and trained the model for classifying documents based on the hierarchical International Patent Classification system. Our results show that TechDoc presents a greater classification accuracy than the unimodal methods and other state-of-the-art benchmarks. The trained model can potentially be scaled to millions of real-world multimodal technical documents, which is useful for data and knowledge management in large technology companies and organizations.Comment: 16 pages, 8 figures, 9 table

Current policy issues in the governance of the European patent system

The European Parliament has been working towards building a discussion platform and a resource for further policy actions in the field of intellectual property rights. The Science and Technology Options Assessment Panel has set the goal of further enlarging the area of investigation in light of recent policy developments at the European level. In particular, the current study covers current policy issues in the governance of the European patent system, such as the backlog issue, the enhancement of patent awareness within the European Parliament, patent enforcement, the regional dimension of intellectual property in Europe, patents and standardisation, the use of existing patents, and patents and competition. These issues were discussed in the conference with stakeholders from European to national patent offices, from private to public sector actors. As a result of the conference, it was stated the need for an IP strategy for Europ

Evaluating Information Retrieval and Access Tasks

This open access book summarizes the first two decades of the NII Testbeds and Community for Information access Research (NTCIR). NTCIR is a series of evaluation forums run by a global team of researchers and hosted by the National Institute of Informatics (NII), Japan. The book is unique in that it discusses not just what was done at NTCIR, but also how it was done and the impact it has achieved. For example, in some chapters the reader sees the early seeds of what eventually grew to be the search engines that provide access to content on the World Wide Web, today’s smartphones that can tailor what they show to the needs of their owners, and the smart speakers that enrich our lives at home and on the move. We also get glimpses into how new search engines can be built for mathematical formulae, or for the digital record of a lived human life. Key to the success of the NTCIR endeavor was early recognition that information access research is an empirical discipline and that evaluation therefore lay at the core of the enterprise. Evaluation is thus at the heart of each chapter in this book. They show, for example, how the recognition that some documents are more important than others has shaped thinking about evaluation design. The thirty-three contributors to this volume speak for the many hundreds of researchers from dozens of countries around the world who together shaped NTCIR as organizers and participants. This book is suitable for researchers, practitioners, and students—anyone who wants to learn about past and present evaluation efforts in information retrieval, information access, and natural language processing, as well as those who want to participate in an evaluation task or even to design and organize one

Patentometric Profile of Social Water

There are regions of the planet that are affected by climatological conditions that cause water scarcity. Thus, innovative techniques have emerged with the purpose of mitigating the reflexes caused by the natural factor: drought. These innovations arise with the objective of capturing, storing and carrying out rainwater treatment for the population. These, called social water technologies, comprise products, techniques or replicable methodologies that are developed specifically to solve the problem of water shortages. The present work aims to analyze the profile of innovations generated by social water technologies through the LATIPAT, INPI and WIPO bases. To search for patents, keywords that were relevant to the research were used and combined with Boolean operators. 907 patents were identified, the largest concentration of deposits in China, justified by the fact that the country adopts development policies that invest in R&D, differentiating itself from other countries. Among the patents analyzed there is a higher concentration of deposits related to the area of ​​human needs and water treatment