Publications and patents have long been regarded as useful sources of technological knowledge in the biomedical sector; thus, they have been analyzed to monitor technology trends and opportunities. However, most previous efforts have focused either on publications as outputs of scientific discovery or patents as outputs of technological development. Few have combined the two databases to derive meaningful implications for identifying new technology opportunities in the biomedical sector. In particular, transforming scientific discovery based on research activities into technological development leading further to commercialization is essential for clinical applications in this sector. Facilitating this process may help achieve efficient and successful research and development (R&D) that requires significant time and cost. Therefore, this study proposed an approach to compare research trends with patenting activities aimed at supporting technology commercialization in the biomedical sector. To achieve this, we employed a semantic analysis of publication data to identify the causal relationships between diseases. We also used co-occurrence analysis of patent data to extract co-treatment relationships between diseases. The analysis results were then integrated to identify diseases that require further drug development. The proposed approach was applied to dementia, and the findings may provide useful insights into technology opportunities for decision-makers in charge of technology planning and commercialization in the biomedical sector.
This work was supported by the New Faculty Startup Fund from Seoul National University ( 0661-20210042 ) and the National Research Foundation of Korea (NRF) grant funded by the Korean Government ( Ministry of Science and ICT ) ( NRF-2022R1A2C2012862 ).