title: Exploitation of semantic methods to cluster pharmacovigilance terms.
abstract: Pharmacovigilance is the activity related to the collection, analysis and prevention of adverse drug reactions (ADRs) induced by drugs. This activity is usually performed within dedicated databases (national, European, international...), in which the ADRs declared for patients are usually coded with a specific controlled terminology MedDRA (Medical Dictionary for Drug Regulatory Activities). Traditionally, the detection of adverse drug reactions is performed with data mining algorithms, while more recently the groupings of close ADR terms are also being exploited. The Standardized MedDRA Queries (SMQs) have become a standard in pharmacovigilance. They are created manually by international boards of experts with the objective to group together the MedDRA terms related to a given safety topic. Within the MedDRA version 13, 84 SMQs exist, although several important safety topics are not yet covered. The objective of our work is to propose an automatic method for assisting the creation of SMQs using the clustering of semantically close MedDRA terms. The experimented method relies on semantic approaches: semantic distance and similarity algorithms, terminology structuring methods and term clustering. The obtained results indicate that the proposed unsupervised methods appear to be complementary for this task, they can generate subsets of the existing SMQs and make this process systematic and less time consuming.
authors.affiliation: CNRS UMR 8163 STL; Université Lille 1&3, F-59653 Villeneuve d'Ascq, France ; Centre de Recherche des Cordeliers, Université Pierre et Marie Curie - Paris6, UMR_S 872, Paris F-75006, France ; INSERM, U872, Paris F-75006 France.
authors.forename: Marie
authors.initials: M
authors.lastname: Dupuch
authors.affiliation: Université Toulouse III Paul Sabatier, F-31062 Toulouse, France.
authors.forename: Laëtitia
authors.initials: L
authors.lastname: Dupuch
authors.affiliation: LIMSI-CNRS, BP133 Orsay, France ; Université Paris 13, Sorbonne Paris Cité, France.
authors.forename: Thierry
authors.initials: T
authors.lastname: Hamon
authors.affiliation: CNRS UMR 8163 STL; Université Lille 1&3, F-59653 Villeneuve d'Ascq, France.
authors.forename: Natalia
authors.initials: N
authors.lastname: Grabar
references.citation: Int J Med Inform. 2009 Dec;78(12):e97-e103
references.pmid: 19230751
references.citation: Proc AMIA Symp. 2001;:662-6
references.pmid: 11825268
references.citation: Drug Saf. 2007;30(7):617-9
references.pmid: 17604415
references.citation: Stud Health Technol Inform. 2010;160(Pt 2):1015-9
references.pmid: 20841837
references.citation: BMC Med Inform Decis Mak. 2010 Oct 28;10:66
references.pmid: 21029418
references.citation: PLoS Comput Biol. 2009 Jul;5(7):e1000443
references.pmid: 19649320
references.citation: BMC Med Inform Decis Mak. 2008 Oct 27;8 Suppl 1:S4
references.pmid: 19007441
references.citation: Pac Symp Biocomput. 2004;:214-25
references.pmid: 14992505
references.citation: Stud Health Technol Inform. 2012;180:73-7
references.pmid: 22874155
references.citation: Drug Discov Today. 2009 Apr;14(7-8):343-57
references.pmid: 19187799
references.citation: Drug Saf. 1999 Feb;20(2):109-17
references.pmid: 10082069
references.citation: Bioinformatics. 2004 Aug 4;20 Suppl 1:i169-77
references.pmid: 15262796
references.citation: AMIA Annu Symp Proc. 2008 Nov 06;:470-4
references.pmid: 18998828
references.citation: Drug Saf. 2002;25(6):459-65
references.pmid: 12071784
references.citation: Int J Med Inform. 2005 Aug;74(7-8):563-71
references.pmid: 15955732
references.citation: Eur J Clin Pharmacol. 1998 Jun;54(4):315-21
references.pmid: 9696956
references.citation: Bioinformatics. 2003 Jul 1;19(10):1275-83
references.pmid: 12835272
references.citation: Stud Health Technol Inform. 2009;150:522-6
references.pmid: 19745366
references.citation: AMIA Annu Symp Proc. 2006;:369-73
references.pmid: 17238365