Fouzia Lghoul

Assistant Professor, LACDR

Fouzia Lghoul-Oulad Saïd is an assistant professor at the Leiden Academic Centre for Drug Research (LACDR), part of Leiden University. Her work focuses on pharmacy education and pharmacoepidemiological research, with a particular interest in drug safety and medication-related hospital admissions.

In 2017, she started her PhD research at the Erasmus Medical Centre and the University of Groningen. Her dissertation, titled "Potentially Preventable Hospital Admissions Related to Medication: Stable, but shifting", investigated trends and determinants of preventable medication-related admissions. The work showed that while the prevalence of such admissions remained stable over time, their causes shifted. It also found that risk factors such as older age and female sex were consistently associated with increased risk. The research further identified areas where guideline adherence could be improved.

After completing her PhD in 2023, she continued working at LACDR, contributing to research and teaching. Her recent work focuses on using real-world data to explore the prediction of drug-related side effects, with the goal of improving individual risk assessment and supporting safer pharmacotherapy.

In addition to her research activities, she is involved in coordinating and teaching several courses in the Pharmacy curriculum, with a strong focus on chronic diseases and elderly.  In 2019, she was selected as Teacher of the Year by student associations at Leiden University.

Her current work combines data-driven research on medication safety with undergraduate education in pharmacy.

Presentation: Adverse drug events: HARMful to HARMless

Hospital admissions related to medication (HARMs) are among the most serious adverse drug events, second only to death. These events have been extensively studied worldwide, and in my thesis, we collaborated with the Ministry of Health to examine their prevalence, underlying causes, and potential strategies for prevention. Yet, despite decades of research, a comprehensive solution remains elusive.

In my talk, I will present both my earlier work and my current research, which uses pharmacovigilance data to identify potential predictors of side effects. I will also share my perspective on how we can leverage existing data to better understand and predict individual risk, moving towards a future of precision pharmacovigilance.

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