ArticleBMC bioinformatics2019
Study of serious adverse drug reactions using FDA-approved drug labeling and MedDRA.
Article in BMC bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed.
- Effect and Safety of Hydroxysafflor Yellow A for Injection in Patients with Acute Ischemic Stroke of Blood Stasis Syndrome: A Phase II, Multicenter, Randomized, Double-Blind, Multiple-Dose, Active-Controlled Clinical Trial.Chinese journal of integrative medicine · 2020Trial
- Adverse Reactions Identified after Approval of Novel Medicines: Analysis of 339 New Molecular Entities and Therapeutic Biologics.Clinical pharmacology and therapeutics · 2026Article
- Assessing the Completeness of Adverse Event Reporting in Clinical Trials of Psoriasis Treatments: A Registry-Publication Comparison Study.Clinical drug investigation · 2026Article
- Mechanistic insights into taxane-induced psychiatric adverse events: a global pharmacovigilance and experimental investigation.Molecular psychiatry · 2026Article
- An interpretable machine learning framework for adverse drug reaction prediction from drug-target interactions.PloS one · 2026Article
- A Vanished Association Between Proton Pump Inhibitors and Clostridioides Difficile Infection After Minimizing Bias.Journal of clinical medicine · 2025Article
- Leveraging FDA Labeling Documents and Large Language Model to Enhance Annotation, Profiling, and Classification of Drug Adverse Events with AskFDALabel.Drug safety · 2025Article
- Investigating the Benefit-Risk Profile of Drugs: From Spontaneous Reporting Systems to Real-World Data for Pharmacovigilance.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Prediction of adverse drug reactions using demographic and non-clinical drug characteristics in FAERS data.Scientific reports · 2024Article
- Automatic text classification of drug-induced liver injury using document-term matrix and XGBoost.Frontiers in artificial intelligence · 2024Article
- A pharmacovigilance study of chronic kidney disease in diabetes mellitus patients with statin treatment by using the US Food and Drug Administration adverse event reporting system.Frontiers in pharmacology · 2024Article
- Analysis of tirzepatide in the US FDA adverse event reporting system (FAERS): a focus on overall patient population and sex-specific subgroups.Frontiers in pharmacology · 2024Article
- Incidence and Severity of Adverse Drug Reactions in Medical Intensive Care Unit.Current drug safety · 2024Article
- Analysis of the association between Janus kinase inhibitors and malignant skin tumors using the Food and Drug Administration Adverse Event Reporting System.International journal of clinical pharmacy · 2023Article
- RxBERT: Enhancing drug labeling text mining and analysis with AI language modeling.Experimental biology and medicine (Maywood, N.J.) · 2023Article
- Classifying Free Texts Into Predefined Sections Using AI in Regulatory Documents: A Case Study with Drug Labeling Documents.Chemical research in toxicology · 2023Article
- Reporting of Drug-Induced Myopathies Associated with the Combination of Statins and Daptomycin: A Disproportionality Analysis Using the US Food and Drug Administration Adverse Event Reporting System.Journal of clinical medicine · 2023Article
- Article
- Agranulocytosis and secondary infection related to JAK inhibitors and IL-6 receptor blockers: a disproportionality analysis using the US Food and drug administration adverse event reporting system.Frontiers in pharmacology · 2023Article
- Real-world safety of PCSK9 inhibitors: A pharmacovigilance study based on spontaneous reports in FAERS.Frontiers in pharmacology · 2022Article
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAdverse Drug Reactions (ADRs) are of great public health concern. FDA-approved drug labeling summarizes ADRs of a drug product mainly in three sections, i.e., Boxed Warning (BW), Warnings and Precautions (WP), and Adverse Reactions (AR), where the severity of ADRs are intended to decrease in the order of BW > WP > AR. Several reported studies have extracted ADRs from labeling documents, but most, if not all, did not discriminate the severity of the ADRs by the different labeling sections. Such a practice could overstate or underestimate the impact of certain ADRs to the public health. In this study, we applied the Medical Dictionary for Regulatory Activities (MedDRA) to drug labeling and systematically analyzed and compared the ADRs from the three labeling sections with a specific emphasis on analyzing serious ADRs presented in BW, which is of most drug safety concern.
resultsThis study investigated New Drug Application (NDA) labeling documents for 1164 single-ingredient drugs using Oracle Text search to extract MedDRA terms. We found that only a small portion of MedDRA Preferred Terms (PTs), 3819 out of 21,920 or 17.42%, were observed in a whole set of documents. In detail, 466/3819 (12.0%) PTs were in BW, 2023/3819 (53.0%) were in WP, and 2961/3819 (77.5%) were in AR sections. We also found a higher overlap of top 20 occurring BW PTs with WP sections compared to AR sections. Within the MedDRA System Organ Class levels, serious ADRs (sADRs) from BW were prevalent in Nervous System disorders and Vascular disorders. A Hierarchical Cluster Analysis (HCA) revealed that drugs within the same therapeutic category shared the same ADR patterns in BW (e.g., nervous system drug class is highly associated with drug abuse terms such as dependence, substance abuse, and respiratory depression).
conclusionsThis study demonstrated that combining MedDRA standard terminologies with data mining techniques facilitated computer-aided ADR analysis of drug labeling. We also highlighted the importance of labeling sections that differ in seriousness and application in drug safety. Using sADRs primarily related to BW sections, we illustrated a prototype approach for computer-aided ADR monitoring and studies which can be applied to other public health documents.
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