Towards structured publishing of potential drug-drug interaction knowledge and evidence

<p>A huge amount of human time and effort is spent in "keeping up" with the explosion of trials and papers. Policymakers and scientists need to quickly access what is known on a given topic at the present time.</p> <p>In this project, part of the “Addressing Gaps in Clinically Useful Evidence on Drug-Drug Interactions”, an NLM R01 grant, we are exploring new methods for abstracting and indexing deep knowledge about medication safety.</p> <p>Potential drug-drug interactions are a significant source of preventable drug-related harm. Unfortunately, most drug information sources disagree substantially in their content. One contributing factor is that there is no standard way to represent PDDI knowledge claims and associated evidence in a computable form.</p> <p>Our approach is to </p> <p>(1) construct both an evidence base and a knowledge base</p> <p>(2) model knowledge with ontologies; and</p> <p>(3) annotate the scientific literature and other source documents.</p> <p>Annotations stored in the evidence base (as micropublications) can be filtered to generate a knowledge base (published in the nanopublication format).</p> <p>Ontologies and data models that we use include:</p> <p>* Micropublications Ontology http://purl.org/mp</p> <p>* Nanopublications Ontology http://nanopub.org/</p> <p>* Open Annotation Data Model http://www.openannotation.org/spec/core/</p> <p>* The Potential Drug-drug Interaction and Potential Drug-drug Interaction Evidence Ontology https://github.com/DIDEO/DIDEO</p> <p>Code and data from the project is available at</p> <p> </p> <p>Related papers have been published at workshops of the International Semantic Web Conference, BDM2I 2015 at ISWC 2015 http://jodischneider.com/pubs/bdm2i.pdf</p> <p>and LISC 2014 at ISWC 2014 http://jodischneider.com/pubs/lisc2014.pdf</p>