GalenOWL: Ontology-based drug recommendations discovery

Abstract

BackgroundIdentification of drug-drug and drug-diseases interactions can pose a difficult problem to cope with, as the increasingly large number of available drugs coupled with the ongoing research activities in the pharmaceutical domain, make the task of discovering relevant information difficult. Although international standards, such as the ICD-10 classification and the UNII registration, have been developed in order to enable efficient knowledge sharing, medical staff needs to be constantly updated in order to effectively discover drug interactions before prescription. The use of Semantic Web technologies has been proposed in earlier works, in order to tackle this problem.ResultsThis work presents a semantic-enabled online service, named GalenOWL, capable of offering real time drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standards such as the aforementioned ICD-10 and UNII, provide the backbone of the common representation of medical data, while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome. A comparison of the developed ontology-based system with a similar system developed using a traditional business logic rule engine is performed, giving insights on the advantages and drawbacks of both implementations.ConclusionsThe use of Semantic Web technologies has been found to be a good match for developing drug recommendation systems. Ontologies can effectively encapsulate medical knowledge and rule-based reasoning can capture and encode the drug interactions knowledge.

Panacea, a semantic-enabled drug recommendations discovery framework

“…The comparisons were focused on the usability of the framework in a production environment as the rule base has been validated in [9]. Three parameters were measured.…”

An Ontology-Based Recommender System Architecture for Semantic Searches in Vehicles Sales Portals

“…GalenOWL [16] is a recommender system for discovering drug recommendations and interactions. The rules are defined based on some patient's characteristics such as age, gender, and etc.…”

“…Ontologies also are used in many applications, e.g., entertainment [11][12], ecommerce [13][14], nutrition [15], medicine [16][17][18], services [19][20], and etc.…”

A 2012 Workshop: Vaccine and Drug Ontology in the Study of Mechanism and Effect (VDOSME 2012)

“…The six papers selected for this thematic issue are extended versions of the original full-length papers presented at the VDOSME 2012 [1-6]. These papers cover a wide range of topics including ontology modeling and analysis, ontology-based knowledge extraction from big data case reports and literature, and ontology-based Semantic Web applications.…”

“…The profiling outcomes support meaningful use of SPL drug labels in clinical applications through standard NDF-RT and RxNorm. In another paper, Doulaverakis et al present a semantic enabled online service called GalenOWL that offers real time drug-drug and drug-disease interaction discovery [6]. A rule based inference method combining ontology information was developed to provide drug recommendations.…”