## 2 Material and Methods  
Data was obtained in April 2017 from the Science Citation Index (SCI)-expanded database of Thomson Scientific Web of ScienceTM (WoS). To retrieve a comprehensive set of the bioprinting literature, all original articles or reviews published in English with the keyword \"bioprinting\" (or \"3D printing\") in the titles or abstracts were included. The corresponding Wos data (title, authors, institutions, year of publication, journal name, abstracts, keywords, subjects, disciplines, references, etc.) were downloaded for further bibliometric analyses. Data sets were selected, analyzed, and ranked in decreasing order of productivity by country and journal, using Microsoft Excel. When mentioned, two time-slices of 5 years were compared: 2006-2010 and 2011-2015. After excluding review papers, original articles were considered and analyzed to assess the maturity of the bioprinting technology. For this purpose, we used the technology readiness level (TRL) for medical devices, which was the same scale designed by the US Army Medical Research and Materiel Command (MRMC) to assess the maturity of developing medical technologies [18]. Its 9 levels ranked from \"basic principles observed and reported\" to \"actual system proven through successful operation\". The scale needed adjustments and was called the bioprinting technology readiness level (BTRL). Data sets of original publications were divided into 4 groups for analysis: in vitro levels (BTRL levels 1-4), animal in vivo levels (BTRL level 5), human in vivo levels (BTRL levels 6-8) and the clinical follow-up level (BTRL level 9). Two investigators went independently through the retrieved abstracts to determine the level of each study. When uncertain, investigators went through the full paper. At the end, the sorting of both investigators was compared and discussed until agreement was reached. Combining various bibliometric tools, such as science mapping and topic analysis, allowed a better overview of the evolution of the technology. Science maps are spatial representations of relationships that help in deciphering a network. These graphic references point out emerging research fronts and profile insights to elaborate strategies. They analyze measure similarities through many bibliometric indicators, such as citation analysis, co-citation analysis and co-word analysis. These tools uncover innovative and dynamic concepts by exploring the relationships between either the publications that were co-cited frequently or the terms from textual records. Science mapping of WoS categories:  
In order to explore research fronts, a science mapping was applied to locate bioprinting research and development among the WoS categories (threshold value at 1) [21; 22]. The 225 WoS categories classify journals included in the SCI. The aggregated journal-journal citation matrix contained in the Journal Citation Reports were aggregated on the basis of these categories. In this study, the 53 retrieved-WoS categories were grouped into \"macro-discilines\": Matter Sciences (such as chemistry and physics), Engineering (technology), Biology (bio-related sciences) and Medicine. Keyword co-occurrence:  
Keyword co-occurrence networking was also used to examine subject domains in various fields (threshold value at 5). This tool is used to measure, via a term-document matrix, the document similarities between clusters of topics such as scientific domains. This tool is less precise than the citation-based analysis but is remarkable for big data analysis. Citation and co-citation network analysis:  
Citation analysis and co-citation analysis were introduced for topic identification, such as emerging topics, that can be useful for Research & Development strategies. Co-citation analysis was developed to analyze interdisciplinary relationships, multidimensional indicators or geographical maps using large scale publication datasets. It was used here for identifying journals of the bioprinting literature by agglomerations of papers based on common references (threshold value at 20).