Using multiple drug similarity networks to promote adverse drug event detection.

ABSTRACT: The occurrence of an adverse drug event (ADE) has become a serious social concern of public health. Early detection of ADEs can lower the risk of drug safety as well as the expense of the drug. While post-market spontaneous reports of ADEs remain a cornerstone of pharmacovigilance, most existing signal detection algorithms rely on substantial accumulated data, limiting their applicability to early ADE detection when reports are scarce. To address this issue, we propose a label propagation model for generating enhanced drug safety signals using multiple drug features. We first construct multiple drug similarity networks using a range of drug features. We then calculate initial drug safety signals using conventional signal detection algorithms. These original signals are subsequently propaga

SUBMITTER: Padhi B 

PROVIDER: S-EPMC11693886 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature