AIMC Topic: Drug Development

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Artificial intelligence and cheminformatics tools: a contribution to the drug development and chemical science.

Journal of biomolecular structure & dynamics Jul 11, 2023
In the ever-evolving field of drug discovery, the integration of Artificial Intelligence (AI) and Machine Learning (ML) with cheminformatics has proven to be a powerful combination. Cheminformatics, which combines the principles of computer science a...
Humans Artificial Intelligence Drug Development Cheminformatics Drug Discovery Machine Learning
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ADis-QSAR: a machine learning model based on biological activity differences of compounds.

Journal of computer-aided molecular design Jun 29, 2023
Drug candidates identified by the pharmaceutical industry typically have unique structural characteristics to ensure they interact strongly and specifically with their biological targets. Identifying these characteristics is a key challenge for devel...
Support Vector Machine Quantitative Structure-Activity Relationship Drug Development Neural Networks, Computer Algorithms Machine Learning
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DEDTI versus IEDTI: efficient and predictive models of drug-target interactions.

Scientific reports Jun 7, 2023
Drug repurposing is an active area of research that aims to decrease the cost and time of drug development. Most of those efforts are primarily concerned with the prediction of drug-target interactions. Many evaluation models, from matrix factorizati...
Computer Simulation Drug Development Algorithms Neural Networks, Computer Drug Interactions Drug Repositioning
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Development of a 2D-QSAR Model for Tissue-to-Plasma Partition Coefficient Value with High Accuracy Using Machine Learning Method, Minimum Required Experimental Values, and Physicochemical Descriptors.

European journal of drug metabolism and pharmacokinetics Jun 2, 2023
BACKGROUND: The demand for physiologically based pharmacokinetic (PBPK) model is increasing currently. New drug application (NDA) of many compounds is submitted with PBPK models for efficient drug development. Tissue-to-plasma partition coefficient (...
Plasma Machine Learning Drug Development Quantitative Structure-Activity Relationship Random Forest
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DrugormerDTI: Drug Graphormer for drug-target interaction prediction.

Computers in biology and medicine Apr 23, 2023
Drug-target interactions (DTI) prediction is a crucial task in drug discovery. Existing computational methods accelerate the drug discovery in this respect. However, most of them suffer from low feature representation ability, significantly affecting...
Proteins Drug Interactions Drug Development Neural Networks, Computer Drug Discovery Molecular Docking Simulation
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Explaining Black Box Drug Target Prediction Through Model Agnostic Counterfactual Samples.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
Many high-performance DTA deep learning models have been proposed, but they are mostly black-box and thus lack human interpretability. Explainable AI (XAI) can make DTA models more trustworthy, and allows to distill biological knowledge from the mode...
Neural Networks, Computer Benchmarking Drug Development Humans
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AttentionDTA: Drug-Target Binding Affinity Prediction by Sequence-Based Deep Learning With Attention Mechanism.

IEEE/ACM transactions on computational biology and bioinformatics Apr 3, 2023
The identification of drug-target relations (DTRs) is substantial in drug development. A large number of methods treat DTRs as drug-target interactions (DTIs), a binary classification problem. The main drawback of these methods are the lack of reliab...
Binding Sites Deep Learning Amino Acid Sequence Drug Development
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BiComp-DTA: Drug-target binding affinity prediction through complementary biological-related and compression-based featurization approach.

PLoS computational biology Mar 31, 2023
Drug-target binding affinity prediction plays a key role in the early stage of drug discovery. Numerous experimental and data-driven approaches have been developed for predicting drug-target binding affinity. However, experimental methods highly rely...
Proteins Drug Discovery Amino Acid Sequence Neural Networks, Computer Drug Development
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Co-model for chemical toxicity prediction based on multi-task deep learning.

Molecular informatics Mar 17, 2023
The toxicity of compounds is closely related to the effectiveness and safety of drug development, and accurately predicting the toxicity of compounds is one of the most challenging tasks in medicinal chemistry and pharmacology. In this paper, we cons...
Information Dissemination Algorithms Drug Development Deep Learning
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BCM-DTI: A fragment-oriented method for drug-target interaction prediction using deep learning.

Computational biology and chemistry Mar 5, 2023
The identification of drug-target interaction (DTI) is significant in drug discovery and development, which is usually of high cost in time and money due to large amount of molecule and protein space. The application of deep learning in predicting DT...
Deep Learning Drug Delivery Systems Drug Discovery Proteins Drug Development
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