Statistical tools can not only cut through the noise in large pharmacovigilance databases. They can also help identify more clinically meaningful patterns in the data. Uppsala Monitoring Centre’s Jim Barrett and Joe Mitchell explain how vigiGroup, a novel clustering algorithm, can bring value to signal detection. Tune in to find out: What the limits of traditional disproportionality analysis areHow clustering algorithms can improve current signal detection practicesHow vigiGroup has helped monitor the safety of COVID-19 vaccines so far Want to know more? By applying vigiGroup to COVID-19 vaccine reports in VigiBase, our Research team was able to identify a number of potential safety signals. Find out more in this poster or in this presentation. Details on how the vigiGroup method was developed and tested can be found in the original publication in Artificial Intelligence in Medicine.Appendicitis was one of the possible safety signals for the COVID-19 vaccines identified with vigiGroup.For more on signal detection at Uppsala Monitoring Centre, visit the Signal Work section on our website or listen to this interview with Helena Sköld and Annette Rudolph on vaccine pharmacovigilance. Join the conversation on social media Follow us on Twitter, Facebook or LinkedIn, and share your thoughts about the show with the hashtag #DrugSafetyMatters. Got a story to share? We’re always looking for new content and interesting people to interview. If you have a great idea for a show, get in touch! About UMC Read more about Uppsala Monitoring Centre and how we work to make medicines safer for patients.