| Literature DB >> 30545608 |
Manfred Hauben1, Robert Reynolds2, Patrick Caubel2.
Abstract
Data science is making increasing contributions to pharmacovigilance. Although the technical innovation of these works are indisputable, efficient progress in real-world pharmacovigilance signal detection may be hampered by corresponding technology life cycle effects, with a resulting tendency to conclude that, with large enough datasets and intricate algorithms, "the numbers speak for themselves," discounting the importance of clinical and scientific judgment. A practical consequence is overzealous declarations regarding the safety or lack of safety of drugs. We describe these concerns through a critical discussion of key results and conclusions from case studies selected to illustrate these points.Entities:
Keywords: Big data; Clinical judgement; Informatics; Pharmacovigilance; Safety signals
Mesh:
Year: 2018 PMID: 30545608 DOI: 10.1016/j.clinthera.2018.10.021
Source DB: PubMed Journal: Clin Ther ISSN: 0149-2918 Impact factor: 3.393