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

Hdl Handle:
http://hdl.handle.net/10144/318845
Title:
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
Authors:
Kajungu, D K; Erhart, A; Talisuna, A O; Bassat, Q; Karema, C; Nabasumba, C; Nambozi, M; Tinto, H; Kremsner, P; Meremikwu, M; D'Alessandro, U; Speybroeck, N
Journal:
PloS One
Abstract:
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.
Publisher:
Public Library of Science
Issue Date:
May-2014
URI:
http://hdl.handle.net/10144/318845
DOI:
10.1371/journal.pone.0096388
PubMed ID:
24787710
Language:
en
ISSN:
1932-6203
Appears in Collections:
Pharmacy

Full metadata record

DC FieldValue Language
dc.contributor.authorKajungu, D Ken_GB
dc.contributor.authorErhart, Aen_GB
dc.contributor.authorTalisuna, A Oen_GB
dc.contributor.authorBassat, Qen_GB
dc.contributor.authorKarema, Cen_GB
dc.contributor.authorNabasumba, Cen_GB
dc.contributor.authorNambozi, Men_GB
dc.contributor.authorTinto, Hen_GB
dc.contributor.authorKremsner, Pen_GB
dc.contributor.authorMeremikwu, Men_GB
dc.contributor.authorD'Alessandro, Uen_GB
dc.contributor.authorSpeybroeck, Nen_GB
dc.date.accessioned2014-06-04T07:42:06Z-
dc.date.available2014-06-04T07:42:06Z-
dc.date.issued2014-05-
dc.identifier.citationPaediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven african countries. 2014, 9 (5):e96388 PLoS ONEen_GB
dc.identifier.issn1932-6203-
dc.identifier.pmid24787710-
dc.identifier.doi10.1371/journal.pone.0096388-
dc.identifier.urihttp://hdl.handle.net/10144/318845-
dc.description.abstractPharmacovigilance 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.en_GB
dc.language.isoenen
dc.publisherPublic Library of Scienceen_GB
dc.rightsPublished by Public Library of Science, [url]http://www.plosone.org/[/url] Archived on this site by Open Access permissionen_GB
dc.subjectMalariaen_GB
dc.subjectPediatricsen_GB
dc.titlePaediatric pharmacovigilance: use of pharmacovigilance data mining algorithms for signal detection in a safety dataset of a paediatric clinical study conducted in seven african countriesen
dc.identifier.journalPloS Oneen_GB

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