AIMC Topic: Drug Discovery

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Titania: an integrated tool for in silico molecular property prediction and NAM-based modeling.

Molecular diversity Apr 23, 2025
Advances in drug discovery and material design rely heavily on in silico analysis of extensive compound datasets and accurate assessment of their properties and activities through computational methods. Efficient and reliable prediction of molecular ...
Computer Simulation Drug Design Models, Molecular Titanium Software Drug Discovery
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Advancing antimalarial drug discovery: ensemble machine learning models for predicting PfPK6 inhibitor activity.

Molecular diversity Apr 22, 2025
Malaria is a significant global health challenge, causing high morbidity and mortality. The rise of drug resistance highlights the urgent need for new antimalarial agents. This study focuses on predictive modeling of 104 Plasmodium falciparum protein...
Algorithms Antimalarials Drug Discovery Protozoan Proteins Support Vector Machine Neural Networks, Computer Protein Kinase Inhibitors Machine Learning Plasmodium falciparum
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DrugGen enhances drug discovery with large language models and reinforcement learning.

Scientific reports Apr 18, 2025
Traditional drug design faces significant challenges due to inherent chemical and biological complexities, often resulting in high failure rates in clinical trials. Deep learning advancements, particularly generative models, offer potential solutions...
Deep Learning Large Language Models Drug Design Humans Ligands Drug Discovery Algorithms
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Advances in artificial intelligence-envisioned technologies for protein and nucleic acid research.

Drug discovery today Apr 17, 2025
Artificial intelligence (AI) and machine learning (ML) have revolutionized pharmaceutical research, particularly in protein and nucleic acid studies. This review summarizes the current status of AI and ML applications in the pharmaceutical sector, fo...
Nucleic Acids Drug Development Proteins Machine Learning Precision Medicine Animals Drug Discovery Humans Artificial Intelligence
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Artificial intelligence in preclinical research: enhancing digital twins and organ-on-chip to reduce animal testing.

Drug discovery today Apr 17, 2025
Artificial intelligence (AI) is reshaping preclinical drug research offering innovative alternatives to traditional animal testing. Advanced techniques, including machine learning (ML), deep learning (DL), AI-powered digital twins (DTs), and AI-enhan...
Humans Animals Drug Discovery Drug Development Artificial Intelligence Machine Learning Lab-On-A-Chip Devices Drug Evaluation, Preclinical Animal Testing Alternatives
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Ligand-Based Drug Discovery Leveraging State-of-the-Art Machine Learning Methodologies Exemplified by Cdr1 Inhibitor Prediction.

Journal of chemical information and modeling Apr 16, 2025
Artificial intelligence (AI) is revolutionizing drug discovery with unprecedented speed and efficiency. In computer-aided drug design, structure-based and ligand-based methodologies are the main driving forces for innovation. In cases where no experi...
Bayes Theorem Ligands Humans Machine Learning Drug Discovery
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Addressing Imbalanced Classification Problems in Drug Discovery and Development Using Random Forest, Support Vector Machine, AutoGluon-Tabular, and H2O AutoML.

Journal of chemical information and modeling Apr 15, 2025
The classification models built on class imbalanced data sets tend to prioritize the accuracy of the majority class, and thus, the minority class generally has a higher misclassification rate. Different techniques are available to address the class i...
Random Forest Drug Discovery Drug Development Machine Learning Support Vector Machine Algorithms
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Artificial intelligence in central-peripheral interaction organ crosstalk: the future of drug discovery and clinical trials.

Pharmacological research Apr 10, 2025
Drug discovery before the 20th century often focused on single genes, molecules, cells, or organs, failing to capture the complexity of biological systems. The emergence of protein-protein interaction network studies in 2001 marked a turning point an...
Drug Discovery Clinical Trials as Topic Central Nervous System Artificial Intelligence Animals Humans
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AI drug development's data problem.

Science (New York, N.Y.) Apr 10, 2025
The future of drug discovery may be artificial intelligence (AI), but its present is not. AI is in its infancy in the field. To help AI mature, developers need nonproprietary, open, large, high-quality datasets to train and validate models, managed b...
Humans Machine Learning Drug Discovery Artificial Intelligence Drug Development Datasets as Topic
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Pre-trained molecular representations enable antimicrobial discovery.

Nature communications Apr 10, 2025
The rise in antimicrobial resistance poses a worldwide threat, reducing the efficacy of common antibiotics. Determining the antimicrobial activity of new chemical compounds through experimental methods remains time-consuming and costly. While compoun...
Staphylococcus aureus Deep Learning Microbial Sensitivity Tests Anti-Bacterial Agents Drug Discovery Humans
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