AUTHOR=Le Huyen , Chen Ru , Harris Stephen , Fang Hong , Lyn-Cook Beverly , Hong Huixiao , Ge Weigong , Rogers Paul , Tong Weida , Zou Wen 

TITLE=RxNorm for drug name normalization: a case study of prescription opioids in the FDA adverse events reporting system

JOURNAL=Frontiers in Bioinformatics

VOLUME=Volume 3 - 2023

YEAR=2024

URL=https://www.frontiersin.org/journals/bioinformatics/articles/10.3389/fbinf.2023.1328613

DOI=10.3389/fbinf.2023.1328613

ISSN=2673-7647

ABSTRACT=Numerous studies have been conducted on the US Food and Drug Administration (FDA) Adverse Events Reporting System (FAERS) database to assess post-marketing reporting rates for drug safety review and risk assessment. However, the drug names in the adverse event (AE) reports from FAERS were heterogeneous due to a lack of uniformity of information submitted mandatorily by pharmaceutical companies and voluntarily by patients, health care professionals, and the public. Studies using FAERS and other spontaneous reporting AEs database without drug name normalization may encounter incomplete collection of AE reports from non-standard drug names and the accuracies of the results might be impacted. In this study, we demonstrated applicability of RxNorm, developed by the National Library of Medicine, for drug name normalization in FAERS. Using prescription opioids as a case study, we used RxNorm application program interface (API) to map all FDA-approved prescription opioids described in FAERS AE reports to their equivalent RxNorm Concept Unique Identifiers (RxCUIs) and RxNorm names. The different names of the opioids were then extracted,