Nano-Enabled Drug Delivery in Cancer Therapy: Literature Analysis Using the MeSH System

Background: Biomedical literature provides abundant knowledge on R development and emerging themes and techniques to researchers and to enhance clinical treatment. Tracing research topic activity and researcher connections, and understanding evolving research landscapes, support identification of research domain potential and informs R portfolio management. Methods: We offer a systematic approach to summarize biomedical research information compiled from the MEDLINE database. Selected MeSH qualifiers are applied as properties for clustering terms. Linkages among clusters are measured based on an object-attributevalue, relative research concentration. By arraying selected technical dimensions against each other, we enable identification and evaluation of latent connections. Results: 10354 MEDLINE records from 2000 to 2013 on nano-enabled drug delivery (NEDD) for cancer treatment are retrieved and analyzed. Seven topical clusters are generated with relatively clear boundaries. Elements with high relative research concentration but low number of records show emerging trends. And the concentrations’ decline indicates the universalization of drugs and nano components in cancer treatment. Conclusion: This systematic topical analysis process helps explore particular technological trends and potentials in biomedical areas. It combines an algorithm to reveal latent connections hidden in literature text content with expert judgement. From the standpoint of technology assessment, it provides researchers and administrators the ability to capture biomedical research dynamics.