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We develop a systematic approach to measuring combinatorial innovation in thebiomedical sciences based upon the comprehensive ontology of Medical SubjectHeadings (MeSH). This approach leverages an expert-defined knowledge ontologythat features both breadth (27,875 MeSH analyzed across 25 million articlesindexed by PubMed from 1902 onwards) and depth (we differentiate between Majorand Minor MeSH terms to identify differences in the knowledge networkrepresentation constructed from primary research topics only). With this levelof uniform resolution we differentiate between three different modes ofinnovation contributing to the combinatorial knowledge network: (i) conceptualinnovation associated with the emergence of new concepts and entities (measuredas the entry of new MeSH); and (ii) recombinant innovation, associated with theemergence of new combinations, which itself consists of two types: peripheral(i.e., combinations involving new knowledge) and core (combinations comprisedof pre-existing knowledge only). Another relevant question we seek to addressis whether examining triplet and quartet combinations, in addition to the moretraditional dyadic or pairwise combinations, provide evidence of any newphenomena associated with higher-order combinations. Analysis of the size,growth, and coverage of combinatorial innovation yield results that are largelyindependent of the combination order, thereby suggesting that the common dyadicapproach is sufficient to capture essential phenomena. Our main results aretwofold: (a) despite the persistent addition of new MeSH terms, the network isdensifying over time meaning that scholars are increasingly exploring andrealizing the vast space of all knowledge combinations; and (b) conceptualinnovation is increasingly concentrated within single research articles, aharbinger of the recent paradigm shift towards convergence science.

Evolution of biomedical innovation quantified via billions of distinct article-level MeSH keyword combinations