-In this poster we present novel development and extension of the Drug-drug Interaction and Drug-drug Interaction Evidence Ontology (DIDEO). We demonstrate how reasoning over this extension of DIDEO can a) automatically create a multi-level hierarchy of evidence types from descriptions of the underlying scientific observations and b) automatically subsume individual evidence items under the correct evidence type. Thus DIDEO will enable evidence items added manually by curators to be automatically categorized into a drug-drug interaction framework with precision and minimal effort from curators. As with all previous DIDEO development this extension is consistent with OBO Foundry principles.
The Drug-drug Interaction and Drug-drug Interaction
Evidence Ontology (DIDEO) is an ontology aimed at
representing drug-drug interactions, potential drug-drug
interactions and the underlying phenomena from physiology,
anatomy, pharmacology and laboratory science. The goal in
creating DIDEO is to provide a realism-based, semantically
rich, and logically consistent OWL representation for the Drug
Interaction Knowledge Base (DIKB) [
A key achievement of the initial version of DIDEO [
In this poster we present the development of a new, semantically rich OWL representation of types of evidence for William R. Hogan
The key strategy for achieving automatic categorization of evidence is to use a) necessary and sufficient conditions of evidence types and b) property assertions for evidence items and the related scientific observations. Fig. 1 shows the classes and relations used to create the necessary and sufficient axiom of the class randomized drug-drug interaction trial.
To represent the scientific observations and their properties, we imported terms from the following ontologies: Chemical Entities of Biological Importance (ChEBI) [10], Drug Ontology (DRON) [11], Gene Ontology (GO) [12], Ontology of Adverse Events (OAE) [13], Ontology of Biomedical Investigations (OBI) [14], and the Uberon multispecies anatomy ontology [15].
III. RESULTS
The extension of DIDEO currently available includes 24 formally defined evidence types. It can be accessed from http://purl.obolibrary.org/obo/dideo/2016-05-12/dideo.owl. Representation of additional evidence types and additional axioms is underway for our project and will be implemented in a subsequent version of DIDEO.
Running the HermiT 1.3.8.3 reasoner, we generate the inferred hierarchy of the evidence types: it is an exact match to the previous DIKB taxonomy as built by domain experts (Fig. 2). In addition, the example individuals were correctly sorted into the evidence types based on the specified properties of the scientific observation that the evidence type was about. This result can be recreated by the reader by running the HermiT 1.3.8.3 reasoner over the test file including examples of evidence items. This test file can be found here: http://purl.obolibrary.org/obo/dideo/EvidenceTypes/dideo.owl. Fig. 2. View of the inferred evidence type taxonomy in Protégé
Based on these results we conclude that the attributes of evidence as used by the DIKB are sufficient to infer a taxonomy of evidence types automatically. We also conclude that it is feasible to use these attributes to automatically categorize individual evidence items using OWL reasoning.
For all authors: This project is supported by a grant from the National Library of Medicine: “Addressing gaps in clinically useful evidence on drug-drug interactions” (R01LM011838). JS is supported by training grant T15LM007059 from the National Library of Medicine/National Institute of Dental and Craniofacial Research. [11] Drug Ontology (DRON), http://purl.obolibrary.org/obo/dron.owl. Last accessed June 17, 2016