What Can Big Data on Academic Interest Reveal about a Drug? Reflections in Three Major US Databases.

The different stages of the life cycle of a drug - 'prenatal' stage, birth of a drug, rapid growth, maturity and stability, decline, and status before 'death' - are reflected in the three following databases: journal articles (PubMed-www.ncbi.nlm.nih.gov/pubmed); patents (US Patent Office-https://partfl1.uspto.gov/netahtml/PTO/search-adv.htlm); and approved drugs (FDA - www.accessdata.fda.gov/scripts/cder/drugsatfda/index/cfm). These databases are huge, from authoritative sources, correctly classified, and they properly link different datasets. Analysis of such data can uncover hidden patterns important for the assessment of drug status and may also yield some predictions regarding its future prospects. Drug-related, publication-based academic bibliographic records are especially numerous and support the development of various scientometric indices. In combination with information from other types of databases, they can outline various trends in pharmacology. Scientometric indices can be classified into those indicating a change in the status of a drug, and those assessing the chances for success, or even drug discontinuation. Here, we present big data analytics on publication-based academic interest in two segments: (i) description of scientometric indices and (ii) their applications for the assessment of the status of a drug.