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. 2019 Sep 10:10:975.
doi: 10.3389/fphar.2019.00975. eCollection 2019.

Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties

Affiliations

Ontological and Non-Ontological Resources for Associating Medical Dictionary for Regulatory Activities Terms to SNOMED Clinical Terms With Semantic Properties

Cédric Bousquet et al. Front Pharmacol. .

Abstract

Background: Formal definitions allow selecting terms (e.g., identifying all terms related to "Infectious disease" using the query "has causative agent organism") and terminological reasoning (e.g., "hepatitis B" is a "hepatitis" and is an "infectious disease"). However, the standard international terminology Medical Dictionary for Regulatory Activities (MedDRA) used for coding adverse drug reactions in pharmacovigilance databases does not beneficiate from such formal definitions. Our objective was to evaluate the potential of reuse of ontological and non-ontological resources for generating such definitions for MedDRA. Methods: We developed several methods that collectively allow a semiautomatic semantic enrichment of MedDRA: 1) using MedDRA-to-SNOMED Clinical Terms (SNOMED CT) mappings (available in the Unified Medical Language System metathesaurus or other mapping resources, e.g., the MedDRA preferred term "hepatitis B" is associated to the SNOMED CT concept "type B viral hepatitis") to extract term definitions (e.g., "hepatitis B" is associated with the following properties: has finding site liver structure, has associated morphology inflammation morphology, and has causative agent hepatitis B virus); 2) using MedDRA labels and lexical/syntactic methods for automatic decomposition of complex MedDRA terms (e.g., the MedDRA systems organ class "blood and lymphatic system disorders" is decomposed in blood system disorders and lymphatic system disorders) or automatic suggestions of properties (e.g., the string "cyclic" in preferred term "cyclic neutropenia" leads to the property has clinical course cyclic). Results: The Unified Medical Language System metathesaurus was the main ontological resource reusable for generating formal definitions for MedDRA terms. The non-ontological resources (another mapping resource provided by Nadkarni and Darer in 2010 and MedDRA labels) allowed defining few additional preferred terms. While the Ci4SeR tool helped the curator to define 1,935 terms by suggesting potential supplemental relations based on the parents' and siblings' semantic definition, defining manually all MedDRA terms remains expensive in time. Discussion: Several ontological and non-ontological resources are available for associating MedDRA terms to SNOMED CT concepts with semantic properties, but providing manual definitions is still necessary. The ontology of adverse events is a possible alternative but does not cover all MedDRA terms either. Perspectives are to implement more efficient techniques to find more logical relations between SNOMED CT and MedDRA in an automated way.

Keywords: Medical Dictionary for Regulatory Activities; SNOMED Clinical Terms; adverse drug reaction; clinical terminology; ontology; pharmacovigilance.

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Figures

Figure 1
Figure 1
Example of the formal definition of “hepatitis B” in OntoADR.
Figure 2
Figure 2
Extract of the MedDRA hierarchy showing preferred terms related or non-related to valvulopathies.
Figure 3
Figure 3
Three use case where data retrieval in a pharmacovigilance database is necessary.
Figure 4
Figure 4
MedDRA terms associated to a formal definition (only the 10 first MedDRA terms retrieved by the query are depicted). (A) MedDRA terms associated to upper gastrointestinal hemorrhage, (B) MedDRA terms describing medical conditions associated with erythema, (C) MedDRA terms describing infectious diseases induced by fungi.
Figure 5
Figure 5
Scenarios of the NeON methodology for implementing OntoADR.
Figure 6
Figure 6
Flow chart representing an overall representation of the several steps and tasks.
Figure 7
Figure 7
Formal definition associated to the preferred term “Shwachman-Diamond syndrome” before manual refinement.
Figure 8
Figure 8
Formal definition associated to the term “Shwachman-Diamond syndrome” after manual refinement.

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