Publications by authors named "S L Verweij"
Article Synopsis
- - There’s a rising trend in drug development to incorporate real-world evidence (RWE) during the pre-marketing phase, influenced by initiatives like DARWIN EU® and regulator-initiated observational studies.
- - An expert meeting held by the Regulatory Science Network Netherlands in 2022 addressed key aspects of these studies, including transparency, independence, and engagement with stakeholders.
- - The authors stress the significance of reproducibility and collaborative efforts among stakeholders to effectively implement regulator-initiated studies for a better European RWE framework in regulatory decisions.
Background: In 2021, a novel group of Chlamydia strains in wild birds was classified as avian Chlamydia abortus, with unknown zoonotic potential. We report relevant features of avian C abortus infections from a Dutch family cluster and unrelated historical cases using clinical, epidemiological, and microbiological data.
Methods: An outbreak of avian C abortus started in the Netherlands in December, 2022.
Background: Randomized controlled trials are considered the gold standard in regulatory decision making, as observational studies are known to have important methodological limitations. However, real-world evidence may be helpful in specific situations. This review investigates how the effect estimates obtained from randomized controlled trials compare to those obtained from observational studies, using drug therapy for relapsing-remitting multiple sclerosis as an example.
View Article and Find Full Text PDFWithin the European Union, the European Medicines Agency's (EMA's) European Public Assessment Report (EPAR) is an important source of information for healthcare professionals and patients that allows them to understand important risks and uncertainties associated with the use of a medicine. However, the EPAR sections describing such important uncertainties can differ substantially in wording, length, and detail, thereby potentially limiting understanding. In this study, we therefore present a natural language processing approach to cluster sentences extracted from the sections on uncertainties in EPARs of centrally authorized medicines, as a steppingstone to harmonization of text describing uncertainties.
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