Natural language processing-based assessment of consistency in summaries of product characteristics of generic antimicrobials.

ABSTRACT: To investigate consistency in summaries of product characteristics (SmPCs) of generic antimicrobials, we used natural language processing (NLP) to analyze and compare large amounts of text quantifying consistency between original and generic SmPCs. We manually compared each section of generic and original SmPCs for antimicrobials listed in the electronic Medicines Compendium in the United Kingdom, focusing on omissions and additions of clinically significant information (CSI). Independently, we quantified differences between the original and generic SmPCs using Kachako, a fully automatic NLP platform. Among the 137 antimicrobials listed in the electronic Medicines Compendium, we identified 193 pairs of original and generic antimicrobial SmPCs for the 48 antimicrobials for which generic SmP

SUBMITTER: Shimazawa R 

PROVIDER: S-EPMC6230812 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature