ArticleDatabase : the journal of biological databases and curation2022
Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers.
Article in Database : the journal of biological databases and curation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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
10 citing papers in PubMed.
- Disproportionality Analysis of Adverse Events Associated with IL-1 Inhibitors in the FDA Adverse Event Reporting System (FAERS).Pharmaceuticals (Basel, Switzerland) · 2025Article
- Effectiveness of Transformer-Based Large Language Models in Identifying Adverse Drug Reaction Relations from Unstructured Discharge Summaries in Singapore.Drug safety · 2025Article
- Leveraging Natural Language Processing and Machine Learning Methods for Adverse Drug Event Detection in Electronic Health/Medical Records: A Scoping Review.Drug safety · 2025Article
- Pharmacovigilance - Technological Advancements, Recent Developments and Innovations.Current drug safety · 2025Review
- The Value of Social Media Analysis for Adverse Events Detection and Pharmacovigilance: Scoping Review.JMIR public health and surveillance · 2024Article
- Layered Double Hydroxides: Recent Progress and Promising Perspectives Toward Biomedical Applications.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Review
- Social Media Posts on Statins: What Can We Learn About Patient Experiences and Perspectives?Journal of the American Heart Association · 2024Article
- Optimizing Medication Querying Using Ontology-Driven Approach with OMOP: with an application to a large-scale COVID-19 EHR dataset.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- The Role of Social Media for Identifying Adverse Drug Events Data in Pharmacovigilance: Protocol for a Scoping Review.JMIR research protocols · 2023Article
- Biomedical relation extraction with knowledge base-refined weak supervision.Database : the journal of biological databases and curation · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage of this life cycle, and stakeholders have a strong interest in applying text mining and artificial intelligence (AI) methods to manage the ever-increasing volume of this information. Recognizing the importance of these applications and the role of challenge evaluations to drive progress in text mining, the organizers of BioCreative VII (Critical Assessment of Information Extraction in Biology) convened a panel of experts to explore 'Challenges in Mining Drug Adverse Reactions'. This article is an outgrowth of the panel; each panelist has highlighted specific text mining application(s), based on their research and their experiences in organizing text mining challenge evaluations. While these highlighted applications only sample the complexity of this problem space, they reveal both opportunities and challenges for text mining to aid in the complex process of drug discovery, testing, marketing and post-market surveillance. Stakeholders are eager to embrace natural language processing and AI tools to help in this process, provided that these tools can be demonstrated to add value to stakeholder workflows. This creates an opportunity for the BioCreative community to work in partnership with regulatory agencies, pharma and the text mining community to identify next steps for future challenge evaluations.
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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.