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Paediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven African countries

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Kajungu, Dan K Erhart, Annette Talisuna, Ambrose Otau Bassat, Quique Karema, Corine Speybroeck, Niko [UCL]

Pharmacovigilance programmes monitor and help ensuring the safe use of medicines which is critical to the success of public health programmes. The commonest method used for discovering previously unknown safety risks is spontaneous notifications. In this study we examine the use of data mining algorithms to identify signals from adverse events reported in a phase IIIb/IV clinical trial evaluating the efficacy and safety of several Artemisinin-based combination therapies (ACTs) for treatment of uncomplicated malaria in African children.

Document type Article de périodique (Journal article) – Article de recherche
Access type Accès libre
Publication date 2014
Language Anglais
Journal information "PLoS One" - Vol. 9, no.5, p. e96388 (2014)
Peer reviewed yes
Publisher Public Library of Science (San Francisco, CA (USA))
issn 1932-6203
e-issn 1932-6203
Publication status Publié
Affiliation UCL - SSS/IRSS - Institut de recherche santé et société
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Bibliographic reference Kajungu, Dan K ; Erhart, Annette ; Talisuna, Ambrose Otau ; Bassat, Quique ; Karema, Corine ; et. al. Paediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven African countries. In: PLoS One, Vol. 9, no.5, p. e96388 (2014)
Permanent URL http://hdl.handle.net/2078.1/157788