Initial Experiments for Pharmacovigilance Analysis in Social Media Using Summaries of Product Characteristics

Leonardo Campillos Llanos, Cyril Grouin, Agnès Lillo-Le Louët, Pierre Zweigenbaum

Abstract: We report initial experiments for analyzing social media through an NLP annotation tool on web posts about medications of current interests (baclofen, levothyroxine and vaccines) and summaries of product characteristics (SPCs). We conducted supervised experiments on a subset of messages annotated by experts according to positive or negative misuse; results ranged from 0.62 to 0.91 of F-score. We also annotated both SPCs and another set of posts to compare MedDRA annotations in each source. A pharmacovigilance expert checked the output and confirmed that entities not found in SCPs might express drug misuse or unknown ADRs.