Building a drug ontology based on RxNorm and other sources

J Biomed Semantics. 2013 Dec 18;4(1):44. doi: 10.1186/2041-1480-4-44.


Background: We built the Drug Ontology (DrOn) because we required correct and consistent drug information in a format for use in semantic web applications, and no existing resource met this requirement or could be altered to meet it. One of the obstacles we faced when creating DrOn was the difficulty in reusing drug information from existing sources. The primary external source we have used at this stage in DrOn's development is RxNorm, a standard drug terminology curated by the National Library of Medicine (NLM). To build DrOn, we (1) mined data from historical releases of RxNorm and (2) mapped many RxNorm entities to Chemical Entities of Biological Interest (ChEBI) classes, pulling relevant information from ChEBI while doing so.

Results: We built DrOn in a modular fashion to facilitate simpler extension and development of the ontology and to allow reasoning and construction to scale. Classes derived from each source are serialized in separate modules. For example, the classes in DrOn that are programmatically derived from RxNorm are stored in a separate module and subsumed by classes in a manually-curated, realist, upper-level module of DrOn with terms such as 'clinical drug role', 'tablet', 'capsule', etc.

Conclusions: DrOn is a modular, extensible ontology of drug products, their ingredients, and their biological activity that avoids many of the fundamental flaws found in other, similar artifacts and meets the requirements of our comparative-effectiveness research use-case.