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Scientometric and patentometric analyses to determine the knowledge landscape in innovative technologies: The case of 3D bioprinting

机译：科学计量和专利计量分析以确定创新技术中的知识格局：3D生物打印的情况

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This research proposes an innovative data model to determine the landscape of emerging technologies. It is based on a competitive technology intelligence methodology that incorporates the assessment of scientific publications and patent analysis production, and is further supported by experts’ feedback. It enables the definition of the growth rate of scientific and technological output in terms of the top countries, institutions and journals producing knowledge within the field as well as the identification of main areas of research and development by analyzing the International Patent Classification codes including keyword clusterization and co-occurrence of patent assignees and patent codes. This model was applied to the evolving domain of 3D bioprinting. Scientific documents from the Scopus and Web of Science databases, along with patents from 27 authorities and 140 countries, were retrieved. In total, 4782 scientific publications and 706 patents were identified from 2000 to mid-2016. The number of scientific documents published and patents in the last five years showed an annual average growth of 20% and 40%, respectively. Results indicate that the most prolific nations and institutions publishing on 3D bioprinting are the USA and China, including the Massachusetts Institute of Technology (USA), Nanyang Technological University (Singapore) and Tsinghua University (China), respectively. Biomaterials and Biofabrication are the predominant journals. The most prolific patenting countries are China and the USA; while Organovo Holdings Inc. (USA) and Tsinghua University (China) are the institutions leading. International Patent Classification codes reveal that most 3D bioprinting inventions intended for medical purposes apply porous or cellular materials or biologically active materials. Knowledge clusters and expert drivers indicate that there is a research focus on tissue engineering including the fabrication of organs, bioinks and new 3D bioprinting systems. Our model offers a guide to researchers to understand the knowledge production of pioneering technologies, in this case 3D bioprinting.
机译：这项研究提出了一种创新的数据模型来确定新兴技术的前景。它基于竞争性技术情报方法论，该方法论结合了科学出版物和专利分析产品的评估，并得到了专家反馈的进一步支持。通过分析包括关键字聚类在内的国际专利分类代码，可以根据在该领域产生知识的排名靠前的国家，机构和期刊来定义科学技术产出的增长率，并确定主要的研究和开发领域并同时存在专利权人和专利代码。此模型已应用于3D生物打印的发展领域。检索了来自Scopus和Web of Science数据库的科学文献，以及来自27个主管部门和140个国家的专利。从2000年到2016年中，共确定了4782篇科学出版物和706项专利。过去五年中发表的科学文件和专利数量分别年均增长20％和40％。结果表明，出版3D生物打印的国家和机构最多的分别是美国和中国，包括麻省理工学院（美国），南洋理工大学（新加坡）和清华大学（中国）。生物材料和生物制造是主要期刊。专利最多的国家是中国和美国。而Organovo Holdings Inc.（美国）和清华大学（中国）是领先的机构。国际专利分类代码显示，大多数用于医学目的的3D生物打印发明都应用了多孔或细胞材料或生物活性材料。知识集群和专家驱动程序表明，对组织工程的研究重点包括器官，生物墨水和新型3D生物打印系统的制造。我们的模型为研究人员提供了指南，以了解开创性技术（在本例中为3D生物打印）的知识生产。

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