OMOP2OBO
Published October 1, 2020 | Version V1.1
Dataset Open

OMOP2OBO Drug Exposure Ingredient Mappings

Authors/Creators

  • 1. Computational Bioscience Program, Department of Pharmacology, University of Colorado Anschutz Medical Campus
  • 2. Department of Physical Medicine and Rehabilitation, School of Medicine, University of Colorado Anschutz School of Medicine
  • 3. Translational and Integrative Sciences Lab, University of Colorado Anschutz School of Medicine
  • 4. Department of Pediatrics, Section of Pediatric Critical Care, School of Medicine, University of Colorado Anschutz School of Medicine

Contributors

Project member:

  • 1. Department of Biomedical Informatics, University of Pittsburgh School of Medicine
  • 2. Center for Health AI, University of Colorado Anschutz Medical Campus
  • 3. Keck School of Medicine, University of Southern California
  • 4. Department of Biomedical Informatics, Columbia University Medical Center
  • 5. Department of Clinical Pharmacy and Medicine, University of Colorado Anschutz Skaggs School of Pharmacy and Pharmaceutical Sciences and School of Medicine
  • 6. Computational Bioscience Program, Department of Pharmacology, Aurora, CO, 80045, USA, University of Colorado Anschutz Medical Campus
  • 7. Department of Research Informatics, Children's Hospital Colorado

Description

OMOP2OBO Drug Exposure Ingredient Mappings V1.0

These mappings were created by the OMOP2OBO mapping algorithm (see links below).  OMOP2OBO - the first health system-wide, disease-agnostic mappings between standardized clinical terminologies and eight Open Biomedical Ontology (OBO) Foundry ontologies spanning diseases, phenotypes, anatomical entities, cell types, organisms, chemicals, vaccines, and proteins. These mappings are also the first to be explicitly created using standard terminologies in the Observational Medical Outcomes (OMOP) common data model (CDM), ensuring both semantic and clinical interoperability across a space of N conditions [and N relationships curated in these ontologies].

The mappings in this repository were created between OMOP standard drug exposure concepts at the ingredient-level (i.e., RxNorm) to the Chemical Entities of Biological Interest (ChEBI), the National Center for Biotechnology Information Taxon Ontology (NCBITaxon), the Protein Ontology (PRO), and the Vaccine Ontology (VO). All concepts were aligned to at least one ChEBI concept and the remaining ontologies (NCBITaxon, PR, and VO) were mapped by their drug class and/or type (e.g., biologics versus vaccines). For these OMOP domains, owl:intersectionOf (“and”), and owl:unionOf (“or”) constructors were used to construct semantically expressive mappings.


Mapping Details
Mappings included in this set were generated automatically using OMOP2OBO or through the use of a Bag-of-words embedding model using TF-IDF. Cosine similarity is used to compute similarity scores between all pairwise combinations of OMOP and OBO concepts and ancestor concepts. To improve the efficiency of this process, the algorithm searches only the top 𝑛 most similar results and keeps the top 75th percentile among all pairs with scores >= 0.25. Manually created mappings are also included.

Mapping Categories

  • Automatic One-to-One Concept: Exact label or synonym, dbXRef, or expert validated mapping @ concept-level; 1:1
  • Automatic One-to-One Ancestor: Exact label or synonym, dbXRef, or expert validated mapping @ concept ancestor-level; 1:1
  • Automatic One-to-Many Concept: Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many
  • Automatic One-to-Many Ancestor: Exact label or synonym, dbXRef, cosine similarity, or expert validated mapping @ concept-level; 1:Many
  • Manual One-to-One: Hand mapping created using expert suggested resources; 1:1
  • Manual One-to-Many: Hand mapping created using expert suggested resources; 1:Many
  • Cosine Similarity: score suggested mapping -- manually verified
  • UnMapped: No suitable mapping or not mapped type

Mapping Statistics
Additional statistics have been provided for the mappings and are shown in the table below. This table presents the counts of OMOP concepts by mapping category and ontology:

Mapping category ChEBI NCBITaxon PRO VO
Automatic One-to-One Concept 3151 155 43 108
Automatic One-to-Many Constructor 404 1 1 0
Automatic One-to-One Ancestor 147 17 20 4
Automatic One-to-Many Ancestor 210 3 2 2
Cosine Similarity 109 4241 18 17
Manual 322 230 157 21
Manual One-to-Many 72 14 8 2
UnMapped 7392 7146 11558 11653


Provenance and Versioning: The V1.0 deposited mappings were created by OMOP2OBO v1.0.0 on October 2022 using the OMOP Common Data Model V5.0 and OBO Foundry ontologies downloaded on September 14, 2020. 

Caveats: Please note that these are the original mappings that were created for the preprint. They have not been updated to current versions of the ontologies. In our experience, this should result in very few errors, but we do suggest that you check the ontology concepts used against current versions of each ontology before using them.

 

Important Resources and Documentation

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Additional details

Related works

Is cited by
Preprint: 10.5281/zenodo.5716421 (DOI)
Is compiled by
Software: https://github.com/callahantiff/OMOP2OBO (URL)
Is published in
Other: http://tiffanycallahan.com/OMOP2OBO_Dashboard (URL)
Is referenced by
Thesis: 10.5281/zenodo.5716401 (DOI)