Extending the "web of drug identity" with knowledge extracted from United States product labels. Hassanzadeh, O., Zhu, Q., Freimuth, R., & Boyce, R. AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science, 2013:64–68, 2013.
abstract   bibtex   
Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical and translational research, especially if it can be linked to other sources that provide data about drug targets, chemical properties, interactions, and biological pathways. Unfortunately, SPLs currently provide coarsely-structured drug information and lack the detailed annotation that is required to support computational use cases. To help address this issue we created LinkedSPLs, a Linked Data resource that extends the "web of drug identity" using information extracted from SPLs. In this paper we describe the mapping that LinkedSPLs provides between SPL active ingredients and DrugBank chemical entities. These mappings were created using three approaches: InChI chemical structure descriptors comparison, exact string matching based on the chemical name, and automatic (unsupervised) linkage identification. Comparison of the approaches found that, while these three approaches are complementary, the automatic approach performs well in terms of precision and recall.
@article{hassanzadeh_extending_2013,
	title = {Extending the "web of drug identity" with knowledge extracted from {United} {States} product labels.},
	volume = {2013},
	issn = {2153-4063},
	abstract = {Structured Product Labels (SPLs) contain information about drugs that can be valuable to clinical and translational research, especially if it can be linked to  other sources that provide data about drug targets, chemical properties,  interactions, and biological pathways. Unfortunately, SPLs currently provide  coarsely-structured drug information and lack the detailed annotation that is  required to support computational use cases. To help address this issue we created  LinkedSPLs, a Linked Data resource that extends the "web of drug identity" using  information extracted from SPLs. In this paper we describe the mapping that  LinkedSPLs provides between SPL active ingredients and DrugBank chemical entities.  These mappings were created using three approaches: InChI chemical structure  descriptors comparison, exact string matching based on the chemical name, and  automatic (unsupervised) linkage identification. Comparison of the approaches found  that, while these three approaches are complementary, the automatic approach  performs well in terms of precision and recall.},
	language = {eng},
	journal = {AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science},
	author = {Hassanzadeh, Oktie and Zhu, Qian and Freimuth, Robert and Boyce, Richard},
	year = {2013},
	pmid = {24303301},
	pmcid = {PMC3814463},
	keywords = {Product Labels},
	pages = {64--68},
}

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