AIMC Topic: Pharmaceutical Preparations

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Multimodal Drug Target Binding Affinity Prediction Using Graph Local Substructure.

IEEE journal of biomedical and health informatics Mar 6, 2025
Predicting the binding affinity of drug target is essential to reduce drug development costs and cycles. Recently, several deep learning-based methods have been proposed to utilize the structural or sequential information of drugs and targets to pred...
Proteins Pharmaceutical Preparations Algorithms Drug Discovery Protein Binding Computational Biology Deep Learning Humans
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Prediction of Drug-Target Interactions With High- Quality Negative Samples and a Network-Based Deep Learning Framework.

IEEE journal of biomedical and health informatics Mar 6, 2025
Identification of drug-target interactions (DTIs) plays a crucial role in drug discovery. Compared to traditional experimental methods, computer-based methods for predicting DTIs can significantly reduce the time and financial burdens of drug develop...
Humans Neural Networks, Computer Drug Discovery Proteins Deep Learning Pharmaceutical Preparations Gene Ontology Computational Biology
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Discriminating High from Low Energy Conformers of Druglike Molecules: An Assessment of Machine Learning Potentials and Quantum Chemical Methods.

Chemphyschem : a European journal of chemical physics and physical chemistry Feb 27, 2025
Accurate and efficient prediction of high energy ligand conformations is important in structure-based drug discovery for the exclusion of unrealistic structures in docking-based virtual screening and de novo design approaches. In this work, we constr...
Molecular Conformation Thermodynamics Machine Learning Quantum Theory Density Functional Theory Pharmaceutical Preparations Ligands
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Drug target affinity prediction based on multi-scale gated power graph and multi-head linear attention mechanism.

PloS one Feb 21, 2025
For the purpose of developing new drugs and repositioning existing ones, accurate drug-target affinity (DTA) prediction is essential. While graph neural networks are frequently utilized for DTA prediction, it is difficult for existing single-scale gr...
Algorithms Humans Pharmaceutical Preparations Neural Networks, Computer
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Application of machine learning approach to estimate the solubility of some solid drugs in supercritical CO.

Scientific reports Feb 12, 2025
Accurate estimation of the solubility of solid drugs (SDs) in the supercritical carbon dioxide (SC-CO) plays an essential role in the related technologies. In this study, artificial intelligence models (AIMs) by gene expression programming (GEP) and ...
Fuzzy Logic Pharmaceutical Preparations Machine Learning Carbon Dioxide Solubility
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A novel neural network-based nearest neighbor approach for drug function prediction from chemical structures.

European journal of pharmacology Feb 11, 2025
Drug function prediction is a crucial task in drug discovery, design, and development, which involves the prediction of the biological functions of a drug molecule based on its chemical structure. Misleading drug function is a common reason for adver...
Molecular Structure Pharmaceutical Preparations Neural Networks, Computer Drug Discovery Humans
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Circular RNA-Drug Association Prediction Based on Multi-Scale Convolutional Neural Networks and Adversarial Autoencoders.

International journal of molecular sciences Feb 11, 2025
The prediction of circular RNA (circRNA)-drug associations plays a crucial role in understanding disease mechanisms and identifying potential therapeutic targets. Traditional methods often struggle to cope with the complexity of heterogeneous network...
RNA, Circular Humans Neural Networks, Computer Computational Biology Pharmaceutical Preparations Autoencoder Algorithms Convolutional Neural Networks
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Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.

Pharmaceutical research Feb 10, 2025
INTRODUCTION: The unbound brain-to-plasma partition coefficient (K) is an essential parameter for predicting central nervous system (CNS) drug disposition using physiologically-based pharmacokinetic (PBPK) modeling. K values for specific compounds ar...
Central Nervous System Agents Quantitative Structure-Activity Relationship Models, Biological Biological Transport Brain Blood-Brain Barrier Machine Learning Rats Animals Algorithms Pharmaceutical Preparations
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Machine Learning for Prediction of Drug Concentrations: Application and Challenges.

Clinical pharmacology and therapeutics Feb 3, 2025
With the advancements in algorithms and increased accessibility of multi-source data, machine learning in pharmacokinetics is gaining interest. This review summarizes studies on machine learning-based pharmacokinetics analysis up to September 2024, i...
Models, Biological Pharmacokinetics Humans Neural Networks, Computer Algorithms Pharmaceutical Preparations Machine Learning
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Highly Sensitive and Interference-Free Detection of Multiple Drug Molecules in Serum Using Dual-Modified SERS Substrates Combined with AI Algorithm Analysis.

Analytical chemistry Feb 3, 2025
Surface-enhanced Raman spectroscopy (SERS) technology has shown broad potential in drug concentration detection, but its application in blood drug monitoring faces significant challenges. The primary difficulty lies in overcoming the interference cau...
Humans Artificial Intelligence Gold Metal Nanoparticles Limit of Detection Algorithms Spectrum Analysis, Raman Surface Properties Silver Pharmaceutical Preparations
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