AIMC Topic: United States Food and Drug Administration
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Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.
Journal of biomedical informatics
Jun 1, 2018
INTRODUCTION: The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifying unlabeled adverse events (AEs) in a drug or biologic drug product's postmarketing phase. Many AE reports must be reviewed by drug safety experts to ...
Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.
Scientific reports
Dec 11, 2017
Drug-induced liver injury (DILI) presents a significant challenge to drug development and regulatory science. The FDA's Liver Toxicity Knowledge Base (LTKB) evaluated >1000 drugs for their likelihood of causing DILI in humans, of which >700 drugs wer...
Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.
Scientific reports
Oct 9, 2017
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...
Adverse Events in Robotic Surgery: A Retrospective Study of 14 Years of FDA Data.
PloS one
Apr 20, 2016
BACKGROUND: Use of robotic systems for minimally invasive surgery has rapidly increased during the last decade. Understanding the causes of adverse events and their impact on patients in robot-assisted surgery will help improve systems and operationa...
Edoxaban vs warfarin in patients with nonvalvular atrial fibrillation in the US Food and Drug Administration approval population: An analysis from the Effective Anticoagulation with Factor Xa Next Generation in Atrial Fibrillation-Thrombolysis in Myocardial Infarction 48 (ENGAGE AF-TIMI 48) trial.
American heart journal
Dec 1, 2015
BACKGROUND: Edoxaban is a specific anti-Xa inhibitor that, in comparison to warfarin, has been found to be noninferior for the prevention of stroke or systemic embolism (SSE) and to reduce bleeding significantly in patients with nonvalvular atrial fi...
Thiazoles
Factor Xa
Factor Xa Inhibitors
Myocardial Infarction
Atrial Fibrillation
Pyridines
Drug Approval
Male
Humans
Warfarin
United States Food and Drug Administration
Thrombolytic Therapy
Blood Coagulation
Female
United States
Stroke
Anticoagulants
Double-Blind Method
Aged
Dose-Response Relationship, Drug
Assessment of drug induced hyperuricemia and gout risk using the FDA adverse event reporting system.
Scientific reports
Jul 2, 2025
Hyperuricemia, the key pathological basis of gout, is increasingly prevalent worldwide. While lifestyle factors contribute, various medications also play a role. However, their specific risks and mechanisms remain inadequately studied. Disproportiona...
BoostDILI: Extreme Gradient Boost-Powered Drug-Induced Liver Injury Prediction and Structural Alerts Generation.
Chemical research in toxicology
May 19, 2025
Over the past 60 years, drug-induced liver injury (DILI) has played a key role in the withdrawal of marketed drugs due to safety concerns. Early prediction of DILI is crucial for developing safer pharmaceuticals, yet current and testing methods are...
Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.
Journal of biomolecular structure & dynamics
May 1, 2025
Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifical...
FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine.
JAMA
Jan 21, 2025
IMPORTANCE: Advances in artificial intelligence (AI) must be matched by efforts to better understand and evaluate how AI performs across health care and biomedicine as well as develop appropriate regulatory frameworks. This Special Communication revi...
A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.
The western journal of emergency medicine
Jan 1, 2025
INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe devices include many ubiquitous items in emergency care, such as vascular access devices, ventilators, infusion pumps, video laryngoscopes, pulse oxim...
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