AIMC Topic: Drug Repositioning

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Artificial intelligence unifies knowledge and actions in drug repositioning.

Emerging topics in life sciences Dec 21, 2021
Drug repositioning aims to reuse existing drugs, shelved drugs, or drug candidates that failed clinical trials for other medical indications. Its attraction is sprung from the reduction in risk associated with safety testing of new medications and th...
Artificial Intelligence Drug Repositioning
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Deep fusion learning facilitates anatomical therapeutic chemical recognition in drug repurposing and discovery.

Briefings in bioinformatics Nov 5, 2021
The advent of large-scale biomedical data and computational algorithms provides new opportunities for drug repurposing and discovery. It is of great interest to find an appropriate data representation and modeling method to facilitate these studies. ...
Proteins Drug Repositioning Databases, Chemical Drug Discovery Models, Chemical Algorithms Deep Learning
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Utilizing graph machine learning within drug discovery and development.

Briefings in bioinformatics Nov 5, 2021
Graph machine learning (GML) is receiving growing interest within the pharmaceutical and biotechnology industries for its ability to model biomolecular structures, the functional relationships between them, and integrate multi-omic datasets - amongst...
Computer Graphics Drug Discovery Drug Development Machine Learning Drug Repositioning Algorithms Models, Molecular Molecular Structure Neural Networks, Computer
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DeepDRK: a deep learning framework for drug repurposing through kernel-based multi-omics integration.

Briefings in bioinformatics Sep 2, 2021
Recent pharmacogenomic studies that generate sequencing data coupled with pharmacological characteristics for patient-derived cancer cell lines led to large amounts of multi-omics data for precision cancer medicine. Among various obstacles hindering ...
Antineoplastic Agents Transcriptome Prognosis Neoplasms Cell Line, Tumor Computational Biology Drug Repositioning Deep Learning Pharmacogenetics Software Precision Medicine Humans Datasets as Topic
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Topological network measures for drug repositioning.

Briefings in bioinformatics Jul 20, 2021
Drug repositioning has received increased attention since the past decade as several blockbuster drugs have come out of repositioning. Computational approaches are significantly contributing to these efforts, of which, network-based methods play a ke...
Computational Biology Drug Repositioning Machine Learning
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GraphDTA: predicting drug-target binding affinity with graph neural networks.

Bioinformatics (Oxford, England) May 23, 2021
SUMMARY: The development of new drugs is costly, time consuming and often accompanied with safety issues. Drug repurposing can avoid the expensive and lengthy process of drug development by finding new uses for already approved drugs. In order to rep...
Neural Networks, Computer Pharmaceutical Preparations Software Proteins Drug Repositioning
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DTI-MLCD: predicting drug-target interactions using multi-label learning with community detection method.

Briefings in bioinformatics May 20, 2021
Identifying drug-target interactions (DTIs) is an important step for drug discovery and drug repositioning. To reduce the experimental cost, a large number of computational approaches have been proposed for this task. The machine learning-based model...
Algorithms Molecular Targeted Therapy Computer Simulation Machine Learning Internet Pharmaceutical Preparations Reproducibility of Results Computational Biology Proteins Drug Repositioning Drug Discovery Protein Binding
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Dr AFC: drug repositioning through anti-fibrosis characteristic.

Briefings in bioinformatics May 20, 2021
Fibrosis is a key component in the pathogenic mechanism of a variety of diseases. These diseases involving fibrosis may share common mechanisms and therapeutic targets, and therefore common intervention strategies and medicines may be applicable for ...
Fibrosis Drug Repositioning Models, Biological Humans Databases, Factual Machine Learning Computational Biology
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Prediction of drug adverse events using deep learning in pharmaceutical discovery.

Briefings in bioinformatics Mar 22, 2021
Traditional machine learning methods used to detect the side effects of drugs pose significant challenges as feature engineering processes are labor-intensive, expert-dependent, time-consuming and cost-ineffective. Moreover, these methods only focus ...
Drug Discovery Deep Learning Drug-Related Side Effects and Adverse Reactions Drug Repositioning Humans Drug Interactions Neural Networks, Computer
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[Potential for Big Data Analysis Using AI in the Field of Clinical Pharmacy].

Yakugaku zasshi : Journal of the Pharmaceutical Society of Japan Jan 1, 2021
Industrial reforms utilizing artificial intelligence (AI) have advanced remarkably in recent years. The application of AI to big data analysis in the medical information field has also been advancing and is expected to be used to find drug adverse ef...
Drug Repositioning Adverse Drug Reaction Reporting Systems Humans Drug Interactions Pharmacy Service, Hospital Artificial Intelligence Drug-Related Side Effects and Adverse Reactions Data Analysis Big Data
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