This article shows the variability of the various international classifications and nomenclatures, the need for structured guidelines with more attention to precise wording and the need for classification expertise embedded in sophisticated terminological resources. End users need support to perform their clinical work in their own language, while still assuring standardised and semantic interoperable medical registration. Collaboration between computational linguists, knowledge engineers, health informaticians and domain experts is needed.

The aim was (1) to analyse the features of the EDQM terminology, (2) to formulate proposals for minor changes and (3) to create a small ontology of dose forms, based on characteristics of EDQM, and suitable for alignment with other dose form terminologies. The 428 Pharmaceutical Dose Forms (PDF) (“human and veterinary” only) were extracted from the EDQM Standard Terms database. A quantitative and qualitative analysis of the textual definitions of the terms was conducted. Through an analysis of unique combinations of different sets of descriptors and characteristics, a small ontology was built in three levels. For the 143 transformable PDFs, the administrable dose form was made explicit, with 121 requiring only one transformation and 22 multiple transformations, of which 10 include “no transformation”. Different levels of aggregations of the 428 PDFs were tested in 4 analyses, ranging from 206 to 383 unique combinations. An ontology in Webprotégé was created of 22 higher-level concepts (based on the intended site characteristics) and 69 intermediate-level terms (newly created) to accommodate the 428 PDFs of EDQM. EDQM Dose Form terminology is suitable terminology in terms of granularity, for defining dose forms of medicinal products, to enable fair comparison of similar medicinal products, and global identification of medicinal products (IDMP). Recommendations for minor improvements and a simple ontology for dose forms are proposed.

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Clinical trials for drug repositioning aim at evaluating the effectiveness and safety of existing drugs as new treatments. This involves managing and semantically correlating many interdependent parameters and details in order to clearly identify the research question of the clinical trial. This work, which is carried out within the PONTE (Efficient Patient Recruitment for Innovative Clinical Trials of Existing Drugs) project, aims to improve the trial design process, by not only offering access to a variety of relevant data sourcesincluding, but not limited to, drug profiles, diseases and their mechanisms, genes and past trial results -but also providing the ability to navigate through these sources, perform queries on them and intelligently fuse the available information through semantic reasoning. This article describes our intention to consume and aggregate information from Linked Data sources in order to produce answers for the clinical researcher's questions.