Weeding out duplicates to better detect side-effects – New podcast episode

Research / 26 August 2024

Duplicate reports are a big problem when it comes to signal detection, but with the help of machine learning and new ways of comparing reports, we may more effectively detect them.


In this episode, Jim Barrett, Senior Data Scientist at UMC and Fredrik Brounéus discuss algorithms: specifically, the duplicate detection algorithm and its use in VigiBase, and generally on different approaches to creating algorithms and the challenges in evaluating their performance.

This episode is part of the Uppsala Reports Long Reads series – the most topical stories from UMC’s pharmacovigilance news site, brought to you in audio format. Find the original article here. Subscribe by visiting the Drug Safety Matters website.

You may also like


Looking beyond age to understand adverse reaction risk in older patients

When it comes to pharmacovigilance in older patients, age alone is insufficient as a measure of adverse reaction risk. Here is what we should consider instead.

Research / 13 May 2024

Updating our approach to study adverse reactions

The traditional “drug-event combination” approach is too simplistic for complex side effects such as behavioural changes. We must adjust our methodology to address this intricacy.

Research / 29 May 2024

Mind the gap: Preventing medication errors after hospital discharge

Medication errors are a key pharmacovigilance issue, especially as patients transition between secondary and primary care as they readjust to life outside of hospital.

Research / 09 September 2024