Introduction and Background: Since June 2011, the European legislation allows patients and patients' organizations to report adverse drug reactions (ADRs). In France, in 2017, more than 32,000 ADRs were reported by patients representing 42% of all ADRs collected yearly and an unexpected increase in patient reports (5.8% in 2016). Most of these cases involved the new Levothyrox® formulation (available since March 2017), leading to the "French Levothyrox® Crisis" [1]. To evaluate whether such crises can be predicted by analyzing social media data, the PHARES multidisciplinary consortium carried out the Levothyrox® case study that is described in this abstract. The PHARES project was funded from 2017 to 2019 by the French National Agency for the Safety of Medicines and Health Products (ANSM [2]) with the objective to implement a computerized tool for social media mining. Objectives: Quantitative and qualitative analysis of Levothyrox® mentions in a French web site dedicated to thyroid pathology to investigate whether social media may be useful to predict ADR-related crises. Methods: All posts published in the forums of the "Vivre sans thyroïde" website were collected and annotated automatically using machine learning and natural language processing methods to identify mentions of drugs and potential Adverse Events (AE) [3, 4]. Only posts containing at least one mention of Levothyrox® or levothyroxine were considered as our analysis collection. From this data sample, we first counted the number of posts per each verbatim detected by the annotation algorithm to identify those AEs most mentioned with Levothyrox®. The 100 most mentioned verbatims were then manually reviewed and classified into categories by a pharmacovigilance expert (cf. Table 1). This manual step generated an association list (verbatim -> Category) that we used as a reference to generate the following statistics over the whole collection: the number of posts per category, the number of posts per AE in each category, and the evolution over time of the number of posts per AE and per category and a time-series analysis using change-point analysis method (CPA) [5].Results: As for July 2018, the studied website contained over 900 thousand posts published since 2001. The evolution of the number of AE mentions associated to Levothyrox® from June 2005 to July 2018 shows no particular rise was present before the first declaration to the pharmacovigilance network. The qualitative analysis of the categories selected for this study resulted in: 25% of General AE, 25% of Levothyrox® indication, 18% of neurological and psychiatric effects, 7% of seriousness description ("emergency", "consultation", "crisis") and 5% of cardiovascular effects. The main AEs associated to general effects are "tiredness", "weight gain" and "pain". The CPA method shows a change point one month before the beginning of the crisis.Conclusion and perspectives: To our knowledge, this study is the first retrospective analysis of social media data following a drug health crisis. It concerns a new formulation of a drug used by more than 3 million people in France, leading to thousands of patients' complaints about ADRs. Most of the collected AEs were expected, some of them may be difficult to classify and a human evaluation is still required. The detected change point corresponds to a low variation and further investigations need to be performed.