AIMC Topic: Drug-Related Side Effects and Adverse Reactions
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Circulating Biomarkers Instead of Genotyping to Establish Metabolizer Phenotypes.
Annual review of pharmacology and toxicology
Aug 16, 2023
Pharmacogenomics (PGx) enables personalized treatment for the prediction of drug response and to avoid adverse drug reactions. Currently, PGx mainly relies on the genetic information of absorption, distribution, metabolism, and excretion (ADME) targe...
A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies.
Chemical research in toxicology
Aug 10, 2023
Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have historically relied on animal models to evaluate toxicity, recent advances in deep-learning approaches hav...
Application of Artificial Intelligence in Drug-Drug Interactions Prediction: A Review.
Journal of chemical information and modeling
Jul 17, 2023
Drug-drug interactions (DDI) are a critical aspect of drug research that can have adverse effects on patients and can lead to serious consequences. Predicting these events accurately can significantly improve clinicians' ability to make better decisi...
Will the future of pharmacovigilance be more automated?
Expert opinion on drug safety
Jul 12, 2023
INTRODUCTION: Artificial intelligence (AI) based tools offer new opportunities for pharmacovigilance (PV) activities. Nevertheless, their contribution to PV needs to be tailored to preserve and strengthen medical and pharmacological expertise in drug...
Automatic Extraction of Comprehensive Drug Safety Information from Adverse Drug Event Narratives in the Korea Adverse Event Reporting System Using Natural Language Processing Techniques.
Drug safety
Jun 17, 2023
INTRODUCTION: Concerns have been raised over the quality of drug safety information, particularly data completeness, collected through spontaneous reporting systems (SRS), although regulatory agencies routinely use SRS data to guide their pharmacovig...
Developing an Artificial Intelligence-Guided Signal Detection in the Food and Drug Administration Adverse Event Reporting System (FAERS): A Proof-of-Concept Study Using Galcanezumab and Simulated Data.
Drug safety
Jun 10, 2023
INTRODUCTION: Time- and resource-demanding activities related to processing individual case safety reports (ICSRs) include manual procedures to evaluate individual causality with the final goal of dismissing false-positive safety signals. Eminent exp...
A deep learning predictive model for public health concerns and hesitancy toward the COVID-19 vaccines.
Scientific reports
Jun 6, 2023
Throughout the pandemic era, COVID-19 was one of the remarkable unexpected situations over the past few years, but with the decentralization and globalization of efforts and knowledge, a successful vaccine-based control strategy was efficiently desig...
Predicting drug adverse effects using a new Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD).
Scientific reports
Apr 28, 2023
Electrical data could be a new source of big-data for training artificial intelligence (AI) for drug discovery. A Gastro-Intestinal Pacemaker Activity Drug Database (GIPADD) was built using a standardized methodology to test drug effects on electrica...
DeepSide: A Deep Learning Approach for Drug Side Effect Prediction.
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2023
Drug failures due to unforeseen adverse effects at clinical trials pose health risks for the participants and lead to substantial financial losses. Side effect prediction algorithms have the potential to guide the drug design process. LINCS L1000 dat...
Artificial Intelligence and Data Mining for the Pharmacovigilance of Drug-Drug Interactions.
Clinical therapeutics
Jan 31, 2023
Despite increasing mechanistic understanding, undetected and underrecognized drug-drug interactions (DDIs) persist. This elusiveness relates to an interwoven complexity of increasing polypharmacy, multiplex mechanistic pathways, and human biological ...
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