AIMC Topic: Drug Combinations

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Predicting cell line-specific synergistic drug combinations through a relational graph convolutional network with attention mechanism.

Briefings in bioinformatics Nov 19, 2022
Identifying synergistic drug combinations (SDCs) is a great challenge due to the combinatorial complexity and the fact that SDC is cell line specific. The existing computational methods either did not consider the cell line specificity of SDC, or did...
Drug Combinations Cell Line Neural Networks, Computer
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DTSyn: a dual-transformer-based neural network to predict synergistic drug combinations.

Briefings in bioinformatics Sep 20, 2022
Drug combination therapies are superior to monotherapy for cancer treatment in many ways. Identifying novel drug combinations by screening is challenging for the wet-lab experiments due to the time-consuming process of the enormous search space of po...
Algorithms ROC Curve Computational Biology Drug Combinations Neural Networks, Computer
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Multidrug representation learning based on pretraining model and molecular graph for drug interaction and combination prediction.

Bioinformatics (Oxford, England) Sep 15, 2022
MOTIVATION: Approaches for the diagnosis and treatment of diseases often adopt the multidrug therapy method because it can increase the efficacy or reduce the toxic side effects of drugs. Using different drugs simultaneously may trigger unexpected ph...
Drug Interactions Drug Therapy, Combination Neural Networks, Computer Drug Combinations Leprostatic Agents
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A review of machine learning approaches for drug synergy prediction in cancer.

Briefings in bioinformatics May 13, 2022
Combinational pharmacotherapy with the synergistic/additive effect is a powerful treatment strategy for complex diseases such as malignancies. Identifying synergistic combinations with various compounds and structures requires testing a large number ...
Drug Combinations Drug Synergism Neoplasms Computational Biology Humans Machine Learning
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SynPathy: Predicting Drug Synergy through Drug-Associated Pathways Using Deep Learning.

Molecular cancer research : MCR May 4, 2022
UNLABELLED: Drug combination therapy has become a promising therapeutic strategy for cancer treatment. While high-throughput drug combination screening is effective for identifying synergistic drug combinations, measuring all possible combinations is...
Protein Interaction Maps Computational Biology Humans Deep Learning Drug Therapy, Combination Drug Combinations Drug Synergism
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An enhanced cascade-based deep forest model for drug combination prediction.

Briefings in bioinformatics Mar 10, 2022
Combination therapy has shown an obvious curative effect on complex diseases, whereas the search space of drug combinations is too large to be validated experimentally even with high-throughput screens. With the increase of the number of drugs, artif...
Artificial Intelligence Machine Learning Computational Biology Drug Combinations Neural Networks, Computer
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PRODeepSyn: predicting anticancer synergistic drug combinations by embedding cell lines with protein-protein interaction network.

Briefings in bioinformatics Mar 10, 2022
Although drug combinations in cancer treatment appear to be a promising therapeutic strategy with respect to monotherapy, it is arduous to discover new synergistic drug combinations due to the combinatorial explosion. Deep learning technology holds i...
Drug Combinations Cell Line Machine Learning Protein Interaction Maps Neural Networks, Computer
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DeepDDS: deep graph neural network with attention mechanism to predict synergistic drug combinations.

Briefings in bioinformatics Jan 17, 2022
MOTIVATION: Drug combination therapy has become an increasingly promising method in the treatment of cancer. However, the number of possible drug combinations is so huge that it is hard to screen synergistic drug combinations through wet-lab experime...
Neoplasms Humans Drug Combinations Machine Learning Software Neural Networks, Computer
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Machine learning methods, databases and tools for drug combination prediction.

Briefings in bioinformatics Jan 17, 2022
Combination therapy has shown an obvious efficacy on complex diseases and can greatly reduce the development of drug resistance. However, even with high-throughput screens, experimental methods are insufficient to explore novel drug combinations. In ...
Machine Learning Algorithms Drug Interactions Databases, Factual Drug Combinations
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Effectiveness and safety of elvitegravir/cobicistat/emtricitabine/tenofovir disoproxil fumarate single-tablet combination among HIV-infected patients in Turkey: results from a real world setting.

African health sciences Dec 1, 2021
BACKGROUND: Efficacy of elvitegravir/cobicistat/emtricitabine/tenofovir disoproxil (E/C/F/TDF) in treatment-naïve and experienced patients with HIV infection was demonstrated in phase 3 trials. The primary objective of this study was to evaluate effe...
Cobicistat Emtricitabine Male Tenofovir Turkey HIV Infections Tablets Retrospective Studies Homosexuality, Male Anti-HIV Agents Humans Adult Quinolones Drug Combinations
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