AIMC Topic: Pharmacovigilance

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Will artificial intelligence chatbots replace clinical pharmacologists? An exploratory study in clinical practice.

European journal of clinical pharmacology
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.

Will the future of pharmacovigilance be more automated?

Expert opinion on drug safety
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...

Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques.

Drug safety
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...

Artificial Intelligence and Data Mining for the Pharmacovigilance of Drug-Drug Interactions.

Clinical therapeutics
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 ...

Exploratory pharmacovigilance with machine learning in big patient data: A focused scoping review.

Basic & clinical pharmacology & toxicology
BACKGROUND: Machine learning can operationalize the rich and complex data in electronic patient records for exploratory pharmacovigilance endeavours.

Adverse drug event detection using natural language processing: A scoping review of supervised learning methods.

PloS one
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 ...

Developing a deep learning natural language processing algorithm for automated reporting of adverse drug reactions.

Journal of biomedical informatics
The detection of adverse drug reactions (ADRs) is critical to our understanding of the safety and risk-benefit profile of medications. With an incidence that has not changed over the last 30 years, ADRs are a significant source of patient morbidity, ...

What place for intelligent automation and artificial intelligence to preserve and strengthen vigilance expertise in the face of increasing declarations?

Therapie
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...