AIMC Topic: Pharmacovigilance
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Pharmacovigilance in the digital age: gaining insight from social media data.
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...
Artificial Intelligence: Applications in Pharmacovigilance Signal Management.
Pharmaceutical medicine
Apr 21, 2025
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...
The EU project Real4Reg: unlocking real-world data with AI.
Health research policy and systems
Feb 27, 2025
BACKGROUND: The use of real-world data is established in post-authorization regulatory processes such as pharmacovigilance of drugs and medical devices, but is still frequently challenged in the pre-authorization phase of medicinal products. In addit...
Artificial intelligence (AI) in pharmacovigilance: A systematic review on predicting adverse drug reactions (ADR) in hospitalized patients.
Research in social & administrative pharmacy : RSAP
Feb 12, 2025
INTRODUCTION: Adverse drug reactions (ADRs) significantly impact healthcare systems, leading to increased hospitalization rates and costs. With the growing adoption of artificial intelligence (AI) in healthcare, machine learning (ML) models offer pro...
Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.
Drug safety
Jan 9, 2025
BACKGROUND: Natural language processing (NLP) and machine learning (ML) techniques may help harness unstructured free-text electronic health record (EHR) data to detect adverse drug events (ADEs) and thus improve pharmacovigilance. However, evidence ...
Applying AI to Structured Real-World Data for Pharmacovigilance Purposes: Scoping Review.
Journal of medical Internet research
Dec 30, 2024
BACKGROUND: Artificial intelligence (AI) applied to real-world data (RWD; eg, electronic health care records) has been identified as a potentially promising technical paradigm for the pharmacovigilance field. There are several instances of AI approac...
Automated redaction of names in adverse event reports using transformer-based neural networks.
BMC medical informatics and decision making
Dec 23, 2024
BACKGROUND: Automated recognition and redaction of personal identifiers in free text can enable organisations to share data while protecting privacy. This is important in the context of pharmacovigilance since relevant detailed information on the cli...
Safeguarding Patients in the AI Era: Ethics at the Forefront of Pharmacovigilance.
Drug safety
Sep 27, 2024
Artificial intelligence is increasingly being used in pharmacovigilance. However, the use of artificial intelligence in pharmacovigilance raises ethical concerns related to fairness, non-discrimination, compliance, and responsibility as the central e...
A real-world pharmacovigilance study on cardiovascular adverse events of tisagenlecleucel using machine learning approach.
Scientific reports
Jun 13, 2024
Chimeric antigen receptor T-cell (CAR-T) therapies are a paradigm-shifting therapeutic in patients with hematological malignancies. However, some concerns remain that they may cause serious cardiovascular adverse events (AEs), for which data are scar...
A Pilot, Predictive Surveillance Model in Pharmacovigilance Using Machine Learning Approaches.
Advances in therapy
May 5, 2024
INTRODUCTION: The identification of a new adverse event (AE) caused by a drug product is one of the key activities in the pharmaceutical industry to ensure the safety profile of a drug product. Machine learning (ML) has the potential to assist with s...
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