Detection of potential safety signals related to the use of remdesivir and tocilizumab in the COVID era during pregnancy, resorting to open data from the FDA adverse event reporting system (FAERS) - Romão, Beatriz Marinho Silva; Duval, Felipe Vieira; Lima, Elisângela Costa; Silva, Fabrício Alves Barbosa da; Matos, Guacira Correa de (Frontiers in Pharmacology, 2024)
The in-hospital treatment for COVID-19 may include medicines from various therapeutic classes, such as antiviral remdesivir and immunosuppressant tocilizumab. Safety data for these medicines are based on controlled clinical trials and case reports, limiting the knowledge about less frequent, rare or unique population adverse events excluded from clinical trials. Objective: This study aims at analyzing the reports of Adverse Drug Events (ADEs) related to these two medicines, focusing on events in pregnant women and foetuses. Methods: Data from the open-access FDA Adverse Event Reporting System (FAERS) from 2020 to 2022 were used to create a dashboard on the Grafana platform to ease querying and analyzing report events. Potential safety signals were generated using the ROR disproportionality measure. Results: Remdesivir was notified as the primary suspect in 7,147 reports and tocilizumab in 19,602. Three hundred and three potential safety signals were identified for remdesivir, of which six were related to pregnant women and foetuses (including abortion and foetal deaths). Tocilizumab accumulated 578 potential safety signals, and three of them were associated with this population (including neonatal death). Discussion: None of the possible signals generated for this population were found in the product labels. According to the NIH and the WHO protocols, both medicines are recommended for pregnant women hospitalized with COVID-19. Conclusions: Despite the known limitations of working with open data from spontaneous reporting systems (e.g., absence of certain clinical data, underreporting, a tendency to report severe events and recent medicines) and disproportionality analysis, the findings suggest concerning associations that need to be confirmed or rejected in subsequent clinical studies.