ArticleP & T : a peer-reviewed journal for formulary management2018
Big Data and Pharmacovigilance: Data Mining for Adverse Drug Events and Interactions.
Article in P & T : a peer-reviewed journal for formulary management, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 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
41 citing papers in PubMed.
- Exploring Risks of Adverse Drug Events From Single Drug to Three-Drug Combination.Clinical and translational science · 2026Article
- Review
- Design Principles for Interactive Dashboards in Drug Safety Surveillance: Design Science Research.JMIR medical informatics · 2026Article
- Closing the loop: human-augmented, mechanistically enhanced AI for proactive management of drug-drug interactions.Frontiers in pharmacology · 2026Article
- Ranking the Diabetes-related Safety Profile of Different Statin Drugs.Current pharmaceutical design · 2026Article
- A Dose-Aware Model for Revealing Dose-Risk Relationship of Drug-Drug Interaction.CPT: pharmacometrics & systems pharmacology · 2025Article
- Post-marketing Safety Assessment of CAR T-cell Therapies: Analysis of Individual Case Safety Reports in the VigiBase.Therapeutic innovation & regulatory science · 2025Article
- Bridging the Regulatory Divide: A Dual-Pathway Framework Using SRA Approvals and AI Evaluation to Ensure Drug Quality in Developing Countries.Pharmaceuticals (Basel, Switzerland) · 2025Review
- Pharmacovigilance processes in low- and middle-income countries: moving from data collection to data analysis and interpretation.Therapeutic advances in drug safety · 2025Article
- Artificial intelligence in pharmacovigilance: advancing drug safety monitoring and regulatory integration.Therapeutic advances in drug safety · 2025Review
- Prostaglandin analogues signal detection by data mining in the FDA Adverse Event Reporting System database.BMJ open ophthalmology · 2024Article
- An innovative method to strengthen evidence for potential drug safety signals using Electronic Health Records.Journal of medical systems · 2024Article
- Identifying the most at-risk age-group and longitudinal trends of drug allergy labeling amongst 7.3 million individuals in Hong Kong.BMC medicine · 2024Article
- High-Throughput Computing to Automate Population-Based Studies to Detect the 30-Day Risk of Adverse Outcomes After New Outpatient Medication Use in Older Adults with Chronic Kidney Disease: A Clinical Research Protocol.Canadian journal of kidney health and disease · 2024Article
- A real-world pharmacovigilance study of abaloparatide based on the FDA Adverse Event Reporting System (FAERS).Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA · 2023Article
- Challenges and opportunities of big data analytics in healthcare.Health care science · 2023Review
- Use of Electronic Health Record Data for Drug Safety Signal Identification: A Scoping Review.Drug safety · 2023Article
- Multiple sampling schemes and deep learning improve active learning performance in drug-drug interaction information retrieval analysis from the literature.Journal of biomedical semantics · 2023Article
- Opportunities and challenges in application of artificial intelligence in pharmacology.Pharmacological reports : PR · 2023Review
- Impact of Regulatory Approval Status on CADTH Reimbursement of Oncology Drugs and Role of Real-World Evidence on Conditional Approvals from 2019 to 2021.Current oncology (Toronto, Ont.) · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Adverse drug events (ADEs), including drug interactions, have a tremendous impact on patient health and generate substantial health care costs. A "big data" approach to pharmacovigilance involves the identification of drug-ADE associations by data mining various electronic sources, including: adverse event reports, the medical literature, electronic health records, and social media. This approach has been useful in assisting the Food and Drug Administration and other regulatory agencies in monitoring and decision-making regarding drug safety. Data mining can also assist pharmaceutical companies in drug safety surveillance efforts, adhering to risk management plans, and gathering real-world evidence to supplement clinical trial data. The use of data mining for pharmacovigilance purposes provides many unique benefits; however, it also presents many challenges. This paper explores the methods and sources of "big data" and how this is contributing to pharmacovigilance efforts.
Identifiers
29896033PMC5969211What 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.