AIMC Topic: Drug Interactions

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Comprehensive Review of Drug-Drug Interaction Prediction Based on Machine Learning: Current Status, Challenges, and Opportunities.

Journal of chemical information and modeling Dec 22, 2023
Detecting drug-drug interactions (DDIs) is an essential step in drug development and drug administration. Given the shortcomings of current experimental methods, the machine learning (ML) approach has become a reliable alternative, attracting extensi...
Machine Learning Databases, Factual Knowledge Bases Drug Interactions Pharmaceutical Preparations
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Emerging drug interaction prediction enabled by a flow-based graph neural network with biomedical network.

Nature computational science Dec 20, 2023
Drug-drug interactions (DDIs) for emerging drugs offer possibilities for treating and alleviating diseases, and accurately predicting these with computational methods can improve patient care and contribute to efficient drug development. However, man...
Drug Interactions Humans Drug Development Neural Networks, Computer
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Phar-LSTM: a pharmacological representation-based LSTM network for drug-drug interaction extraction.

PeerJ Dec 14, 2023
Pharmacological drug interactions are among the most common causes of medication errors. Many different methods have been proposed to extract drug-drug interactions from the literature to reduce medication errors over the last few years. However, the...
Drug Interactions Machine Learning Learning Neural Networks, Computer
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Computational and artificial intelligence-based approaches for drug metabolism and transport prediction.

Trends in pharmacological sciences Dec 9, 2023
Drug metabolism and transport, orchestrated by drug-metabolizing enzymes (DMEs) and drug transporters (DTs), are implicated in drug-drug interactions (DDIs) and adverse drug reactions (ADRs). Reliable and precise predictions of DDIs and ADRs are crit...
Humans Drug-Related Side Effects and Adverse Reactions Artificial Intelligence Machine Learning Drug Interactions
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An Uncertainty-Guided Deep Learning Method Facilitates Rapid Screening of CYP3A4 Inhibitors.

Journal of chemical information and modeling Dec 6, 2023
Cytochrome P450 3A4 (CYP3A4), a prominent member of the P450 enzyme superfamily, plays a crucial role in metabolizing various xenobiotics, including over 50% of clinically significant drugs. Evaluating CYP3A4 inhibition before drug approval is essent...
Enzyme Inhibitors Cytochrome P-450 Enzyme System Drug Interactions Uncertainty Cytochrome P-450 Enzyme Inhibitors Cytochrome P-450 CYP3A Inhibitors Cytochrome P-450 CYP3A Deep Learning Reproducibility of Results
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A simplified similarity-based approach for drug-drug interaction prediction.

PloS one Nov 9, 2023
Drug-drug interactions (DDIs) are a critical component of drug safety surveillance. Laboratory studies aimed at detecting DDIs are typically difficult, expensive, and time-consuming; therefore, developing in-silico methods is critical. Machine learni...
Retrospective Studies Machine Learning Drug Interactions Neural Networks, Computer Databases, Factual
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Deep learning-enabled natural language processing to identify directional pharmacokinetic drug-drug interactions.

BMC bioinformatics Nov 1, 2023
BACKGROUND: During drug development, it is essential to gather information about the change of clinical exposure of a drug (object) due to the pharmacokinetic (PK) drug-drug interactions (DDIs) with another drug (precipitant). While many natural lang...
Drug Interactions Data Mining Natural Language Processing Deep Learning Language
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Neural Network Models for Predicting Solubility and Metabolism Class of Drugs in the Biopharmaceutics Drug Disposition Classification System (BDDCS).

European journal of drug metabolism and pharmacokinetics Oct 21, 2023
BACKGROUND AND OBJECTIVE: The biopharmaceutics drug disposition classification system (BDDCS) categorizes drugs into four classes on the basis of their solubility and metabolism. This framework allows for the study of the pharmacokinetics of transpor...
Drug Interactions Biopharmaceutics Solubility Neural Networks, Computer Pharmaceutical Preparations
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Predicting Antioxidant Synergism via Artificial Intelligence and Benchtop Data.

Journal of agricultural and food chemistry Oct 5, 2023
Lipid oxidation is a major issue affecting products containing unsaturated fatty acids as ingredients or components, leading to the formation of low molecular weight species with diverse functional groups that impart off-odors and off-flavors. Aiming...
Drug Interactions Oxidation-Reduction Antioxidants Phenols Artificial Intelligence
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MM-GANN-DDI: Multimodal Graph-Agnostic Neural Networks for Predicting Drug-Drug Interaction Events.

Computers in biology and medicine Sep 23, 2023
Personalized treatment of complex diseases relies on combined medication. However, the occurrence of unexpected drug-drug interactions (DDIs) in these combinations can lead to adverse effects or even fatalities. Although recent computational methods ...
Neural Networks, Computer Computational Biology Drug Interactions Humans
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