Adverse drug reactions (ADRs) remain a major, yet largely preventable, global public health challenge, causing significant morbidity, mortality, and healthcare costs. This review synthesises evidence on the global burden, pharmacovigilance systems, a...
Large language models (LLMs) are useful tools with the capacity for performing specific types of knowledge work at an effective scale. However, LLM deployments in high-risk and safety-critical domains pose unique challenges, notably the issue of "hal...
Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also play a role. However, their specific risks and mechanisms remain inadequately studied. Disproportiona...
Experimental biology and medicine (Maywood, N.J.)
May 27, 2025
Pharmacovigilance is essential for protecting patient health by monitoring and managing medication-related risks. Traditional methods like spontaneous reporting systems and clinical trials are valuable for identifying adverse drug events, but face de...
Pharmacovigilance is the science of collection, detection, and assessment of adverse events associated with pharmaceutical products for the ongoing monitoring and understanding of those products' safety profiles. Part of this process, signal manageme...
Signal management, defined as the set of activities from signal detection to recommendations for action, is conducted using different data sources and leveraging data from spontaneous reporting databases (SRDs), which represent the cornerstone of pha...
INTRODUCTION: Manual identification of case narratives with specific relevant information can be challenging when working with large numbers of adverse event reports (case series). The process can be supported with a search engine, but building searc...
BACKGROUND: The US Food and Drug Administration (FDA) has raised concerns about a potential link between trimethoprim/sulfamethoxazole (TMP-SMX) and an increased risk of acute respiratory failure/acute respiratory distress syndrome (ARF/ARDS) in heal...
INTRODUCTION: Transformer-based large language models (LLMs) have transformed the field of natural language processing and led to significant advancements in various text processing tasks. However, the applicability of these LLMs in identifying relat...
IEEE journal of biomedical and health informatics
Feb 10, 2025
The medical community has grappled with the challenge of analysis and early detection of severe and unknown adverse drug reactions (ADRs) from Spontaneous Reporting Systems (SRSs) like the FDA Adverse Event Reporting System (FAERS), which often lack ...
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