AIMC Topic: Drug Discovery

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The Role of AI in Drug Discovery.

Chembiochem : a European journal of chemical biology Jun 26, 2024
The emergence of Artificial Intelligence (AI) in drug discovery marks a pivotal shift in pharmaceutical research, blending sophisticated computational techniques with conventional scientific exploration to break through enduring obstacles. This revie...
Drug Repositioning Artificial Intelligence Drug Design Drug Discovery Humans
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Quantum-Informed Molecular Representation Learning Enhancing ADMET Property Prediction.

Journal of chemical information and modeling Jun 25, 2024
We examined pretraining tasks leveraging abundant labeled data to effectively enhance molecular representation learning in downstream tasks, specifically emphasizing graph transformers to improve the prediction of ADMET properties. Our investigation ...
Humans Pharmaceutical Preparations Quantum Theory Machine Learning Drug Discovery
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A Combination of Machine Learning and PBPK Modeling Approach for Pharmacokinetics Prediction of Small Molecules in Humans.

Pharmaceutical research Jun 25, 2024
PURPOSE: Recently, there has been rapid development in model-informed drug development, which has the potential to reduce animal experiments and accelerate drug discovery. Physiologically based pharmacokinetic (PBPK) and machine learning (ML) models ...
Humans Machine Learning Computer Simulation Male Drug Discovery Caco-2 Cells Models, Biological Blood Proteins Pharmacokinetics Area Under Curve Administration, Intravenous Pharmaceutical Preparations
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Deep representation learning of chemical-induced transcriptional profile for phenotype-based drug discovery.

Nature communications Jun 25, 2024
Artificial intelligence transforms drug discovery, with phenotype-based approaches emerging as a promising alternative to target-based methods, overcoming limitations like lack of well-defined targets. While chemical-induced transcriptional profiles ...
Deep Learning Pancreatic Neoplasms Drug Repositioning Gene Expression Profiling Transcriptome Phenotype Drug Discovery Humans Antineoplastic Agents Artificial Intelligence
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Advancing drug discovery with deep attention neural networks.

Drug discovery today Jun 24, 2024
In the dynamic field of drug discovery, deep attention neural networks are revolutionizing our approach to complex data. This review explores the attention mechanism and its extended architectures, including graph attention networks (GATs), transform...
Neural Networks, Computer Humans Drug Design Deep Learning Drug Discovery
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AlphaFold2 structures guide prospective ligand discovery.

Science (New York, N.Y.) Jun 21, 2024
AlphaFold2 (AF2) models have had wide impact but mixed success in retrospective ligand recognition. We prospectively docked large libraries against unrefined AF2 models of the σ and serotonin 2A (5-HT2A) receptors, testing hundreds of new molecules a...
Deep Learning Ligands Receptor, Serotonin, 5-HT2A Drug Design Drug Discovery Protein Folding Serotonin 5-HT2 Receptor Agonists Serotonin 5-HT2 Receptor Antagonists Protein Conformation Cryoelectron Microscopy Small Molecule Libraries Humans Molecular Docking Simulation Receptors, sigma
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From Deep Learning to the Discovery of Promising VEGFR-2 Inhibitors.

ChemMedChem Jun 20, 2024
Vascular endothelial growth factor receptor 2 (VEGFR-2) stands as a prominent therapeutic target in oncology, playing a critical role in angiogenesis, tumor growth, and metastasis. FDA-approved VEGFR-2 inhibitors are associated with diverse side effe...
Drug Screening Assays, Antitumor Structure-Activity Relationship Molecular Structure Cell Line, Tumor Humans Cell Proliferation Drug Discovery Molecular Docking Simulation Dose-Response Relationship, Drug Vascular Endothelial Growth Factor Receptor-2 Antineoplastic Agents Protein Kinase Inhibitors Deep Learning
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Task-Similarity is a Crucial Factor for Few-Shot Meta-Learning of Structure-Activity Relationships.

Chembiochem : a European journal of chemical biology Jun 18, 2024
Machine learning models support computer-aided molecular design and compound optimization. However, the initial phases of drug discovery often face a scarcity of training data for these models. Meta-learning has emerged as a potentially promising str...
Machine Learning Humans Drug Discovery Structure-Activity Relationship
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Artificial intelligence for small molecule anticancer drug discovery.

Expert opinion on drug discovery Jun 18, 2024
INTRODUCTION: The transition from conventional cytotoxic chemotherapy to targeted cancer therapy with small-molecule anticancer drugs has enhanced treatment outcomes. This approach, which now dominates cancer treatment, has its advantages. Despite th...
Drug Discovery Molecular Targeted Therapy Machine Learning Antineoplastic Agents Animals Humans Big Data Deep Learning Neoplasms Artificial Intelligence Drug Development Drug Resistance, Neoplasm
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Harnessing machine learning potential for personalised drug design and overcoming drug resistance.

Journal of drug targeting Jun 13, 2024
Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing comple...
Drug Discovery Antineoplastic Agents Bayes Theorem Drug Resistance, Neoplasm Precision Medicine Neoplasms Drug Design Machine Learning Algorithms Humans
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