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
(2014) PLoS One — Vol. 9, n° 5, p. e96388 (2014)
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- 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.
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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. (2014). 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. PLoS One, 9(5), e96388. https://doi.org/10.1371/journal.pone.0096388 (Original work published 2014)