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Building a drug ontology based on RxNorm and other sources
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 difficult...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931349/ https://www.ncbi.nlm.nih.gov/pubmed/24345026 http://dx.doi.org/10.1186/2041-1480-4-44 |
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author | Hanna, Josh Joseph, Eric Brochhausen, Mathias Hogan, William R |
author_facet | Hanna, Josh Joseph, Eric Brochhausen, Mathias Hogan, William R |
author_sort | Hanna, Josh |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3931349 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-39313492014-02-22 Building a drug ontology based on RxNorm and other sources Hanna, Josh Joseph, Eric Brochhausen, Mathias Hogan, William R J Biomed Semantics Research 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. BioMed Central 2013-12-18 /pmc/articles/PMC3931349/ /pubmed/24345026 http://dx.doi.org/10.1186/2041-1480-4-44 Text en Copyright © 2013 Hanna et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Hanna, Josh Joseph, Eric Brochhausen, Mathias Hogan, William R Building a drug ontology based on RxNorm and other sources |
title | Building a drug ontology based on RxNorm and other sources |
title_full | Building a drug ontology based on RxNorm and other sources |
title_fullStr | Building a drug ontology based on RxNorm and other sources |
title_full_unstemmed | Building a drug ontology based on RxNorm and other sources |
title_short | Building a drug ontology based on RxNorm and other sources |
title_sort | building a drug ontology based on rxnorm and other sources |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3931349/ https://www.ncbi.nlm.nih.gov/pubmed/24345026 http://dx.doi.org/10.1186/2041-1480-4-44 |
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