AIMC Topic: Pharmacovigilance

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Artificial Intelligence for Unstructured Healthcare Data: Application to Coding of Patient Reporting of Adverse Drug Reactions.

Clinical pharmacology and therapeutics
Adverse drug reaction (ADR) reporting is a major component of drug safety monitoring; its input will, however, only be optimized if systems can manage to deal with its tremendous flow of information, based primarily on unstructured text fields. The a...

Validating Intelligent Automation Systems in Pharmacovigilance: Insights from Good Manufacturing Practices.

Drug safety
Pharmacovigilance is the science of monitoring the effects of medicinal products to identify and evaluate potential adverse reactions and provide necessary and timely risk mitigation measures. Intelligent automation technologies have a strong potenti...

Leveraging digital media data for pharmacovigilance.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The development of novel drugs in response to changing clinical requirements is a complex and costly method with uncertain outcomes. Postmarket pharmacovigilance is essential as drugs often have under-reported side effects. This study intends to use ...

Artificial Intelligence in Pharmacovigilance: Scoping Points to Consider.

Clinical therapeutics
Artificial intelligence (AI), a highly interdisciplinary science, is an increasing presence in pharmacovigilance (PV). A better understanding of the scope of artificial intelligence in pharmacovigilance (AIPV) may be advantageous to more sharply defi...

Artificial Intelligence, Real-World Automation and the Safety of Medicines.

Drug safety
Despite huge technological advances in the capabilities to capture, store, link and analyse data electronically, there has been some but limited impact on routine pharmacovigilance. We discuss emerging research in the use of artificial intelligence, ...

Enabling pregnant women and their physicians to make informed medication decisions using artificial intelligence.

Journal of pharmacokinetics and pharmacodynamics
The role of artificial intelligence (AI) in healthcare for pregnant women. To assess the role of AI in women's health, discover gaps, and discuss the future of AI in maternal health. A systematic review of English articles using EMBASE, PubMed, and S...

Leveraging Contextual Information in Extracting Long Distance Relations from Clinical Notes.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Relation extraction from biomedical text is important for clinical decision support applications. In post-marketing pharmacovigilance, for example, Adverse Drug Events (ADE) relate medical problems to the drugs that caused them and were the focus of ...

Predicting Adverse Drug-Drug Interactions with Neural Embedding of Semantic Predications.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The identification of drug-drug interactions (DDIs) is important for patient safety; yet, compared to other pharmacovigilance work, a limited amount of research has been conducted in this space. Recent work has successfully applied a method of derivi...

An Application of Machine Learning in Pharmacovigilance: Estimating Likely Patient Genotype From Phenotypical Manifestations of Fluoropyrimidine Toxicity.

Clinical pharmacology and therapeutics
Dihydropyrimidine dehydrogenase (DPD)-deficient patients might only become aware of their genotype after exposure to dihydropyrimidines, if testing is performed. Case reports to pharmacovigilance databases might only contain phenotypical manifestatio...