The Drug-Drug Interactions Ontology: DINTO
DINTO is an OWL ontology that systematically organizes all drug-drug interaction (DDI) related information. Drug-drug interactions (DDIs) form a significant risk group for adverse effects associated with pharmaceutical treatment. These interactions are often reported in the literature, however, they are sparsely represented in machine-readable resources, such as online databases, thesauri or ontologies. DINTO is an ontology that describes and categorizes DDIs and all the possible mechanisms that can lead to them (including both pharmacodynamic and pharmacokinetic DDI mechanisms).
Latest version of DINTO 1.2 includes adverse drug events (ADE) from the Ontology of Adverse Events (OAE) and drug-ADE relationships from the database SIDER.
The first version of DINTO is still available here (DINTO_1.owl). Also, you can download a version mapped to the Basic Formal Ontology (BFO) (DINTO_1BFO.owl).
Additional files used in different experiments can be found in folders DINTO_1 and DINTO_1.2, along to a description and reference to the papers describing them.
DINTO can be combined with specifically created Semantic Web Rule Language (SWRL) rules to infer DDIs and their different mechanisms (both pharmacokinetic and pharmacodynamic). To demonstrate this, we have conducted different experiments described in Herrero-Zazo, María; Segura-Bedmar, Isabel; Hastings, Janna; Martínez, Paloma (2015). DINTO: Using OWL ontologies and SWRL rules to infer drug-drug interactions and their mechanisms. Journal of Chemical Information and Modeling. DOI: 10.1021/acs.jcim.5b00119 [http://pubs.acs.org/doi/abs/10.1021/acs.jcim.5b00119]
The application of DINTO to different natural language tasks – i.e., drug named entity recognition (NER) and DDI relation extraction (RE) – is described in Herrero-Zazo, María; Segura-Bedmar, Isabel; Hastings, Janna; Martínez, Paloma (2015). Application of Domain Ontologies to Natural Language Processing: A Case Study for Drug-Drug Interactions. (2015) International Journal of Information Retrieval Research (IJIRR). 5(3), 19-38.[http://www.igi-global.com/article/application-of-domain-ontologies-to-natural-language-processing/132500/]
A detailed description of DINTO, the methodology followed to create and evaluate it, and the different application scenarios where it has been used can be found in the PhD Dissertation Semantic Resources in Pharmacovigilance: a Corpus and an Ontology for Drug-Drug Interactions (2015). Herrero-Zazo, María. Universidad Carlos III de Madrid [http://labda.inf.uc3m.es/doku.php?id=es:labda_asignacion_tesis/]
First steps in the creation of DINTO are described in Herrero-Zazo, María; Hastings, Janna; Segura-Bedmar, Isabel; Croset, Samuel; Martínez, Paloma; Steinbeck, Christoph (2013). An ontology for drug-drug interactions. 6th International Workshop on Semantic Web Applications and Tools for Life Sciences (SWAT4LS) Edinburgh, UK.[http://ceur-ws.org/Vol-1114/]
This ontology has been created by the Advanced Databases Group at University Carlos III of Madrid in collaboration with the ChEBI ontology team at the European Bioinformatics Institute. Contact address: firstname.lastname@example.org and email@example.com