Towards precision pharmacovigilance

Signal detection / 01 May 2019

Photo: UMC

Precision medicine has garnered increasing attention from the scientific community in recent years. The term most often refers to approaches where genetic information is used to predict which patients will respond better to a given medicine. But individual risk factors, including genetic ones, can also be used to predict which patients will most likely experience an adverse drug reaction.

Our Research team at Uppsala Monitoring Centre has recently embraced this approach in its signal detection efforts. Our first attempt was performed in 2014, when we screened VigiBase, the WHO global database of individual case safety reports, for signals of adverse drug reactions in children. Another screening in 2017 aimed for the first time at identifying groups of patients at higher risk for certain adverse drug reactions. 

The results are promising so far, suggesting we could soon be ushering in a new era of “precision pharmacovigilance”.

The risk factor screening

Current signal detection methods in pharmacovigilance often use statistics to highlight potential safety issues, followed by manual review of case reports. Statistical screening methods usually focus on the drug and the adverse event, and the patient is not considered until the manual case review step, when the problem is examined in detail and potential risk factors are identified. However, in a signal detection effort in 2017, our UMC Research team decided to focus on the patient in the first step. We first screened VigiBase, the WHO global database of individual case safety reports, for safety issues in specific groups of patients: people of a certain age, gender, or body mass index; affected by a given disease; or from a specific geographical area.

 

Paediatric signal sprint in action. Photo: UMC.

Paediatric signal sprint in action. Photo: UMC.

We were able to pinpoint drug–adverse event combinations that appeared more often than expected in specific groups of patients, but that would have gone unnoticed in the entire population.

With this approach, we were able to pinpoint drug–adverse event combinations that appeared more often than expected in specific groups of patients, but that would have gone unnoticed in the entire population. For example, aseptic meningitis (an inflammation of the central nervous system) was reported more frequently in men taking the antibiotic amoxicillin than in women. Routine statistical screening of the entire database would not have high­lighted this local pattern, but focusing on subsets of data did. Potential risk factors highlighted ahead of the manual review were then useful in directing subsequent investigations.

Altogether, our screening flagged seven additional safety issues and related risk factors. We have communicated all of these to national pharmacovigilance centres in the WHO Programme for International Drug Monitoring, and they will be available to the public over time via the WHO Pharmaceuticals Newsletter.

Read about the signals

WHO Pharmaceuticals Newsletter, 6, 2018

  • "Aflibercept and deep vein thrombosis/pulmonary embolism" (p.12)
  • "Ceftriaxone and hepatitis in patients 75 and older" (p.24)

WHO Pharmaceuticals Newsletter, 1, 2019

Lovisa Sandberg
Research Pharmacist, UMC

You may also like


Keeping vaccines safe – New podcast on COVID-19 vaccine surveillance

UMC experts discuss how real-time vaccine surveillance works during a pandemic and the role of VigiBase in helping to ensure public safety.

Signal detection / 29 June 2021

Vaccine surveillance systems explained – new podcast episode

Ever wondered how safety surveillance differs between vaccines and drugs? Find out in the latest episode of the Drug Safety Matters podcast.

Signal detection / 25 August 2022

Record growth pushes VigiBase past 28 million reports

After decades of slow but steady growth, VigiBase has recently entered a new phase of accelerating expansion, driven by a range of converging forces.

Signal detection / 16 September 2021

Our website uses cookies

Cookies are small text files held on your computer. They allow us to give you the best browsing experience possible and mean that we can understand how you use our site. Some cookies have already been set. You can delete and block cookies but parts of our site won't work without them. By using our website you accept our use of cookies.

Find out more