ReviewDrug safety2022
Artificial Intelligence-Based Pharmacovigilance in the Setting of Limited Resources.
Review in Drug safety, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed.
- Using Artificial Intelligence to Identify Patterns and Predictors of Adverse Drug Reactions in Cardiovascular Patients: A Comprehensive Narrative Review.American journal of cardiovascular drugs : drugs, devices, and other interventions · 2026Review
- The economic imperative of artificial intelligence in maternal and neonatal health: a review of evaluation benefits, frameworks, challenges, future perspectives, and limitations.Cost effectiveness and resource allocation : C/E · 2026Review
- Artificial intelligence in pharmacovigilance: a narrative review and practical experience with an expert-defined Bayesian network tool.International journal of clinical pharmacy · 2025Review
- Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.Drug safety · 2025Article
- Characterizing Public Sentiments and Drug Interactions in the COVID-19 Pandemic Using Social Media: Natural Language Processing and Network Analysis.Journal of medical Internet research · 2025Article
- Probing Large Language Model Hidden States for Adverse Drug Reaction Knowledge.medRxiv : the preprint server for health sciences · 2025Article
- Safeguarding Patients in the AI Era: Ethics at the Forefront of Pharmacovigilance.Drug safety · 2025Article
- Pharmacovigilance - Technological Advancements, Recent Developments and Innovations.Current drug safety · 2025Review
- A Review of the Applications, Benefits, and Challenges of Generative AI for Sustainable Toxicology.Current research in toxicology · 2025Review
- Article
- Global Research Landscape of Artificial Intelligence in Urology: A Systematic Analysis of Emerging Trends, Clinical Impact, and Collaborative Networks (1971-2024).Medical journal of the Islamic Republic of Iran · 2025Article
- Evaluating the effectiveness of AI-enhanced "One Body, Two Wings" pharmacovigilance models in China: a nationwide survey on medication safety and risk management.Frontiers in health services · 2025Article
- Article
- Potential Applications of Artificial Intelligence (AI) in Managing Polypharmacy in Saudi Arabia: A Narrative Review.Healthcare (Basel, Switzerland) · 2024Review
- Prescription Precision: A Comprehensive Review of Intelligent Prescription Systems.Current pharmaceutical design · 2024Review
- Enhancing pharmacovigilance for robust drug safety monitoring: addressing underreporting and collaborative solutions.Therapeutic advances in drug safety · 2024Article
- Pharmacovigilance in High-Income Countries: Current Developments and a Review of Literature.Pharmacy (Basel, Switzerland) · 2023Review
- Navigating a transforming landscape: the evolving role of pharmacovigilance physicians in drug development and implications for future challenges and training requirements.Frontiers in drug safety and regulation · 2023Article
- Twenty-First Century Global ADR Management: A Need for Clarification, Redesign, and Coordinated Action.Therapeutic innovation & regulatory science · 2023Article
- Artificial Intelligence and Machine Learning for Safe Medicines.Drug safety · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With the rapid development of artificial intelligence (AI) technologies, and the large amount of pharmacovigilance-related data stored in an electronic manner, data-driven automatic methods need to be urgently applied to all aspects of pharmacovigilance to assist healthcare professionals. However, the quantity and quality of data directly affect the performance of AI, and there are particular challenges to implementing AI in limited-resource settings. Analyzing challenges and solutions for AI-based pharmacovigilance in resource-limited settings can improve pharmacovigilance frameworks and capabilities in these settings. In this review, we summarize the challenges into four categories: establishing a database for an AI-based pharmacovigilance system, lack of human resources, weak AI technology and insufficient government support. This study also discusses possible solutions and future perspectives on AI-based pharmacovigilance in resource-limited settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.