Uncovering 3D bioprinting research trends: A keyword network mapping analysis

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Leonardo Azael Garcia-Garcia, Marisela Rodriguez-Salvador


A scientometric analysis as part of a Competitive Technology Intelligence methodology was used to determine the main research efforts in 3D bioprinting. Papers from Scopus and Web of Science (WoS) published between 2000 and 2017 were analysed. A network map of the most frequently occurring keywords in these articles was created, and their average publication year (APY) was determined. The analysis focused on the most relevant keywords that occurred at least five times. A total of 1,759 keywords were obtained, and a co-occurrence analysis was developed for APYs with more keywords: 2011–2016. The results indicated that Polylactic Acid (PLA) is the material used most often. Applications mainly focused on bone tissue engineering and regeneration. The most frequently used technique was inkjet printing, and the main cell sources were Mesenchymal Stem Cells (MSC). From a general perspective, ‘Treatment’ and ‘Bioink’ were the most frequent keywords. The former was mainly related to cancer, regenerative medicine, and MSC and the latter, to multicellular spheroid deposition and the use of hydrogels like GelMA (gelatin methacryloyl). This analysis provides insights to stakeholders involved in 3D bioprinting research and development who need to keep abreast of scientific progress in the field.


scientometric analysis; data mining; competitive technology intelligence

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DOI: http://dx.doi.org/10.18063/ijb.v4i2.147


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