AIMC Topic: Drug Development

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Predictive Modelling in pharmacokinetics: from in-silico simulations to personalized medicine.

Expert opinion on drug metabolism & toxicology Mar 20, 2024
INTRODUCTION: Pharmacokinetic parameters assessment is a critical aspect of drug discovery and development, yet challenges persist due to limited training data. Despite advancements in machine learning and in-silico predictions, scarcity of data hamp...
Humans Artificial Intelligence Precision Medicine Reproducibility of Results Machine Learning Computer Simulation Models, Molecular Pharmaceutical Preparations Models, Biological Pharmacokinetics Pharmacogenetics Drug Development Drug Design Drug Discovery
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Deep-NCA: A deep learning methodology for performing noncompartmental analysis of pharmacokinetic data.

CPT: pharmacometrics & systems pharmacology Mar 11, 2024
Noncompartmental analysis (NCA) is a model-independent approach for assessing pharmacokinetics (PKs). Although the existing NCA algorithms are very well-established and widely utilized, they suffer from low accuracies in the setting of sparse PK samp...
Computer Simulation Deep Learning Humans Algorithms Models, Biological Pharmacokinetics Drug Development Pharmaceutical Preparations
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Drug target prediction through deep learning functional representation of gene signatures.

Nature communications Feb 29, 2024
Many machine learning applications in bioinformatics currently rely on matching gene identities when analyzing input gene signatures and fail to take advantage of preexisting knowledge about gene functions. To further enable comparative analysis of O...
Humans Machine Learning Drug Development Deep Learning Computational Biology
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Transforming drug development with synthetic biology and AI.

Trends in biotechnology Feb 20, 2024
The COVID-19 pandemic has thrust RNA as a platform for drug development into the spotlight. However, identifying promising drug candidates is challenging. With advances in synthetic biology and artificial intelligence (AI) models, we can overcome thi...
Humans Artificial Intelligence Pandemics COVID-19 COVID-19 Drug Treatment SARS-CoV-2 Synthetic Biology Drug Development
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Where Might Artificial Intelligence Be Going in Pharmaceutical Development?

Molecular pharmaceutics Feb 20, 2024
Artificial Intelligence Algorithms Drug Development
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Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

European journal of medicinal chemistry Feb 19, 2024
Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and li...
Drug Development Structure-Activity Relationship Peptides Deep Learning Technology
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Computational drug development for membrane protein targets.

Nature biotechnology Feb 15, 2024
The application of computational biology in drug development for membrane protein targets has experienced a boost from recent developments in deep learning-driven structure prediction, increased speed and resolution of structure elucidation, machine ...
Cryoelectron Microscopy Membrane Proteins Drug Development Computational Biology Machine Learning
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Potential of Artificial Intelligence to Accelerate Drug Development for Rare Diseases.

Pharmaceutical medicine Feb 5, 2024
The growth in breadth and depth of artificial intelligence (AI) applications has been fast, running hand in hand with the increasing amount of digital data available. Here, we comment on the application of AI in the field of drug development, with a ...
Drug Development Rare Diseases Humans Artificial Intelligence Drug Discovery
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SMGCN: Multiple Similarity and Multiple Kernel Fusion Based Graph Convolutional Neural Network for Drug-Target Interactions Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Feb 5, 2024
Accurately identifying potential drug-target interactions (DTIs) is a critical step in accelerating drug discovery. Despite many studies that have been conducted over the past decades, detecting DTIs remains a highly challenging and complicated proce...
Drug Development Databases, Factual Drug Interactions Drug Discovery Neural Networks, Computer
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Prediction of Drug-Disease Associations Based on Multi-Kernel Deep Learning Method in Heterogeneous Graph Embedding.

IEEE/ACM transactions on computational biology and bioinformatics Feb 5, 2024
Computational drug repositioning can identify potential associations between drugs and diseases. This technology has been shown to be effective in accelerating drug development and reducing experimental costs. Although there has been plenty of resear...
Drug Development Computer Simulation Drug Repositioning Deep Learning
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