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→Pharmacoracle - a REST API based on the OWLAPI
The Pharmacoracle was implemented as an attempt to understand the field of pharmacogenomics, based on data from PharmGKB, and solving the same problem as [https://github.com/PharmGKB/PharmCAT/wiki PharmGKBs PharmCAT software], but in the context of the technology and clinical recommendations of our clinic. It may be sensible to integrate PharmCAT in the Pharmacoracle, as soon as PharmCAT becomes the gold standard for VCF to PGx recommendations.
Queries to Pharmacoracle are written in the [https://www.w3.org/TR/owl2-manchester-syntax/ Manchester syntax] in the same way as for the [https://protegewiki.stanford.edu/wiki/DLQueryTab DL Query Tab] of [https://protege.stanford.edu/ Stanford's desktop Protégé]. An advantage of this approach is that the queries replaces the need of a separate rules engine (rules are to some extent built into the OWL semantics). A disadvantage is that the performance in a production environment may be suboptimal (slow). I believe that the standard way to use OWL is to make a triplet store database (RDF database, e.g. JENA) based on the OWL ontology. The rules can then be written as SPARQL queries to this database. It is possible that there are more lessons to be learned from the PGx clinical decision support ontology of [https://bioportal.bioontology.org/ontologies/GENE-CDS Mathias Samwald], who is involved in the [http://upgx.eu UPGx] project.
The Pharmacoracle infrastructure is written in Python. But the [http://owlcs.github.io/owlapi/ OWLAPI] is mainly JAVA technology, and making the Pharmacoracle totally JAVA, might speed up things. A link between OWL and Python is provided by [http://www.lesfleursdunormal.fr/static/_downloads/article_owlready_aim_2017.pdf Jean Baptiste Lamy's Owlready2], which we use to translate PharmGKB's JSON-LD to OWL, but it seems that the OWLAPI should be run separately.