The bigger picture: the history of antibiotics and antimicrobial resistance displayed by scientometric data.

Monitoring the rapid global spread of antimicrobial resistance requires an over-regional and fast surveillance tool. Data from major surveillance studies based on aggregated results of selected sentinel laboratories or retrospective strain collections are not available for the whole scientific community and are limited by time and region. Thus, we tested an alternative approach to monitor resistance trends by automated semantic and scientometric analysis of all (>100000) related PubMed entries. A semantic search was done using 'Gene Ontology' and MeSH vocabulary and additional search terms for further data refinement. Data extraction was performed using the semantic search engine 'GoPubMed'. The timely relationship between introduction of novel β-lactam antibiotic classes into the market and emergence of respective resistance was investigated using nearly 22300 publications over the last 70 years. Further analysis was done with around 54000 publications related to 'infectious diseases' and an additional 50000 publications related to 'antimicrobial resistance' to estimate current trends in publication interest regarding resistance development since 1940. Scientometric results were compared with data from the major surveillance network EARS-Net. Furthermore, the relationship between micro-organism, year and antibiotic market introduction was investigated for eight key antibiotics using nearly 37500 publications. Owing to influencing factors such as availability of alternative antibiotics, scientometric analysis correlated only partly with resistance development. However, it provides a fast, reliable and global overview of the clinical and public health importance of a specific resistance including the period of the 1940s-1980s, when resistance surveillance studies were not yet established.