In 2018, the "Ateliers de Giens" (Giens Workshops) devoted a workshop to artificial intelligence (AI) and led its experts to confirm the potential contribution and theoretical benefit of AI in clinical research, pharmacovigilance, and in improving th...
Despite increasing mechanistic understanding, undetected and underrecognized drug-drug interactions (DDIs) persist. This elusiveness relates to an interwoven complexity of increasing polypharmacy, multiplex mechanistic pathways, and human biological ...
To reduce adverse drug events (ADEs), hospitals need a system to support them in monitoring ADE occurrence routinely, rapidly, and at scale. Natural language processing (NLP), a computerized approach to analyze text data, has shown promising results ...
INTRODUCTION: Concerns have been raised over the quality of drug safety information, particularly data completeness, collected through spontaneous reporting systems (SRS), although regulatory agencies routinely use SRS data to guide their pharmacovig...
INTRODUCTION: Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to preserve and strengthen medical and pharmacological expertise in drug...
European journal of clinical pharmacology
37566133
PURPOSE: Recently, there has been a growing interest in using ChatGPT for various applications in Medicine. We evaluated the interest of OpenAI chatbot (GPT 4.0) for drug information activities at Toulouse Pharmacovigilance Center.
Pharmacovigilance (PV) deals with the detection, collection, assessment, understanding, and prevention of adverse effects associated with drugs. The objective of PV is to ensure the safety of the medicines and patients by monitoring and reporting all...