Research graph
References from Role of AI in predicting drug efficacy and toxicity. Local targets link to admitted publications; unresolved targets remain external evidence.
Mass-spectrometric exploration of proteome structure and function
10.1038/nature19949 · 2016 · External reference
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data
10.1016/j.drudis.2020.11.037 · 2021 · External reference
Cancer drug response profile scan (CDRscan): a deep learning model that predicts drug effectiveness from cancer genomic signature
10.1038/s41598-018-27214-6 · 2018 · External reference
Deep learning–based multi-omics integration for cancer survival prediction
2018 · External reference
Leveraging big data to transform target selection and drug discovery
10.1002/cpt.318 · 2016 · External reference
Has drug design augmented by artificial intelligence become a reality?
10.1016/j.tips.2019.09.004 · 2019 · External reference
The rise of deep learning in drug discovery
10.1016/j.drudis.2018.01.039 · 2018 · External reference
FDA-approved drug labeling for the study of drug-induced liver injury
10.1016/j.drudis.2011.05.007 · 2011 · External reference
Applications of artificial intelligence in drug development using real-world data
10.1016/j.drudis.2020.12.013 · 2021 · External reference
Artificial intelligence in drug discovery: Applications and techniques
10.1093/bib/bbab430 · 2022 · External reference
The next era: deep learning in pharmaceutical research
10.1007/s11095-016-2029-7 · 2016 · External reference
Exploiting machine learning for end-to-end drug discovery and development
10.1038/s41563-019-0338-z · 2019 · External reference
Synthesis of small molecules targeting multiple DNA structures using click chemistry
10.1002/cmdc.201200060 · 2012 · External reference
Tox21 challenge to build predictive models of nuclear receptor and stress response pathways as mediated by exposure to environmental chemicals and drugs
10.3389/fenvs.2015.00085 · 2016 · External reference
Bidirectional RNN for medical event detection in electronic health records
2016 · External reference
DeepSite: protein-binding site predictor using 3D-convolutional neural networks
10.1093/bioinformatics/btx350 · 2018 · External reference
Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines
10.1016/j.drudis.2013.11.005 · 2014 · External reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · 2021 · External reference
druGAN: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico
10.1021/acs.molpharmaceut.7b00346 · 2017 · External reference
PubChem substance and compound databases
10.1093/nar/gkaa971 · 2019 · External reference
Machine learning applications in cancer prognosis and prediction
10.1016/j.csbj.2014.11.005 · 2015 · External reference
The SIDER database of drugs and side effects
10.1093/nar/gkv1075 · 2016 · External reference
Integrating multi-omics data for drug response prediction using deep learning
2020 · External reference
Deep learning-based prediction of drug response in cancer
10.1093/bib/bbz171 · 2021 · External reference
Assessment of an in silico mechanistic model for proarrhythmia risk prediction under the CiPA initiative
10.1002/cpt.1184 · 2019 · External reference
VigiBase, the WHO global ICSR database system: basic facts
10.1177/009286150804200501 · 2008 · External reference
Lost in translation: animal models and clinical trials in cancer treatment
2014 · External reference
DeepTox: toxicity prediction using deep learning
2016 · External reference
ChEMBL: towards direct deposition of bioassay data
10.1093/nar/gky1075 · 2019 · External reference
Deep learning for healthcare: review, opportunities and challenges
10.1093/bib/bbx044 · 2018 · External reference
GraphDTA: predicting drug–target binding affinity with graph neural networks
10.1093/bioinformatics/btaa921 · 2021 · External reference
Molecular de novo design through deep reinforcement learning
10.1186/s13321-017-0235-x · 2017 · External reference
DeepDTA: deep drug–target binding affinity prediction
10.1093/bioinformatics/bty593 · 2018 · External reference
How to improve R&D productivity: the pharmaceutical industry’s grand challenge
10.1038/nrd3078 · 2010 · External reference
Better prediction of the local concentration–effect relationship: The role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development
10.1016/j.drudis.2019.05.016 · 2019 · External reference
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
10.1038/s41551-018-0195-0 · 2018 · External reference
Machine learning approaches and their applications in drug discovery and design
10.1111/cbdd.14057 · 2022 · External reference
Drug repurposing: progress, challenges and recommendations
10.1038/nrd.2018.168 · 2019 · External reference
Machine learning in medicine
10.1056/nejmra1814259 · 2019 · External reference
DeepChem: a deep learning platform for drug discovery
2017 · External reference
Pharmacogenomics in the clinic
10.1038/nature15817 · 2015 · External reference
ToxCast chemical landscape: paving the road to 21st century toxicology
10.1021/acs.chemrestox.6b00135 · 2016 · External reference
Utilizing social media data for pharmacovigilance: a review
10.1016/j.jbi.2015.02.004 · 2015 · External reference
Artificial intelligence and machine learning in clinical development: a translational perspective
10.1038/s41746-019-0148-3 · 2019 · External reference
The sequencing quality control (SEQC) project: a comprehensive assessment of RNA-seq accuracy, reproducibility and information content
2016 · External reference
PreSS/MD: predictor of hERG-mediated cardiotoxicity using machine learning
2018 · External reference
Deep learning for molecular design—A review of the state of the art
2019 · External reference
Deep learning-based de novo design of antibiotics
10.1016/j.cell.2020.01.021 · 2020 · External reference
Recent advances of deep learning in bioinformatics and computational biology
10.3389/fgene.2019.00214 · 2019 · External reference
Data-driven prediction of drug effects and interactions
10.1126/scitranslmed.3003377 · 2012 · External reference
High-performance medicine: the convergence of human and artificial intelligence
10.1038/s41591-018-0300-7 · 2019 · External reference
Best practices for QSAR model development, validation, and exploitation
10.1002/minf.201000061 · 2010 · External reference
Open TG-GATES: a large-scale transcriptomics database for predicting drug-induced liver toxicity
2016 · External reference
Applications of machine learning in drug discovery and development
10.1038/s41573-019-0024-5 · 2019 · External reference
Drug–drug interaction through molecular structure similarity analysis
10.1136/amiajnl-2012-000935 · 2012 · External reference
Drug–drug interaction through molecular structure similarity analysis
10.1136/amiajnl-2012-000935 · 2012 · External reference
AtomNet: a deep convolutional neural network for bioactivity prediction in structure-based drug discovery
2015 · External reference
Predicting drug-induced liver injury by machine learning
2016 · External reference
An analysis of the attrition of drug candidates from four major pharmaceutical companies
10.1038/nrd4609 · 2015 · External reference
The CompTox chemistry dashboard: a community data resource for environmental chemistry
10.1186/s13321-017-0247-6 · 2017 · External reference
Deep learning for toxicity prediction in drug development
10.1021/acs.jcim.5b00238 · 2015 · External reference
Deep learning for drug-induced toxicity prediction
2021 · External reference
Implementation of deep learning in drug design
10.1002/mef2.18 · 2022 · External reference
Analyzing learned molecular representations for property prediction
10.1021/acs.jcim.9b00237 · 2019 · External reference
A pipeline to extract drug–adverse event pairs from multiple data sources for pharmacovigilance
2014 · External reference
Artificial intelligence in healthcare
10.1038/s41551-018-0305-z · 2018 · External reference
Machine learning for pharmacogenomics and precision medicine
2021 · External reference
deepDR: A network-based deep learning approach to in silico drug repositioning
10.1093/bioinformatics/btz418 · 2019 · External reference
Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity
10.1038/tpj.2013.39 · 2014 · External reference
Unresolved reference
2020 · External reference
Artificial intelligence for drug discovery, biomarker development, and generation of novel chemistry
10.1021/acs.molpharmaceut.8b00930 · 2018 · External reference
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
10.1038/s41587-019-0224-x · 2019 · External reference
Artificial intelligence in drug design
10.1007/s11427-018-9342-2 · 2018 · External reference
Deep learning in drug discovery: Challenges and opportunities
2020 · External reference
Modeling polypharmacy side effects with graph convolutional networks
10.1093/bioinformatics/bty294 · 2018 · External reference
Synthesis of small molecules targeting multiple DNA structures using click chemistry
10.1002/cmdc.201200060 · ExternalCitation · doi-reference
Assessment of an in silico mechanistic model for proarrhythmia risk prediction under the CiPA initiative
10.1002/cpt.1184 · ExternalCitation · doi-reference
Leveraging big data to transform target selection and drug discovery
10.1002/cpt.318 · ExternalCitation · doi-reference
Implementation of deep learning in drug design
10.1002/mef2.18 · ExternalCitation · doi-reference
Best practices for QSAR model development, validation, and exploitation
10.1002/minf.201000061 · ExternalCitation · doi-reference
The next era: deep learning in pharmaceutical research
10.1007/s11095-016-2029-7 · ExternalCitation · doi-reference
Artificial intelligence in drug design
10.1007/s11427-018-9342-2 · ExternalCitation · doi-reference
Deep learning-based de novo design of antibiotics
10.1016/j.cell.2020.01.021 · ExternalCitation · doi-reference
Machine learning applications in cancer prognosis and prediction
10.1016/j.csbj.2014.11.005 · ExternalCitation · doi-reference
FDA-approved drug labeling for the study of drug-induced liver injury
10.1016/j.drudis.2011.05.007 · ExternalCitation · doi-reference
Toward better drug repositioning: prioritizing and integrating existing methods into efficient pipelines
10.1016/j.drudis.2013.11.005 · ExternalCitation · doi-reference
The rise of deep learning in drug discovery
10.1016/j.drudis.2018.01.039 · ExternalCitation · doi-reference
Better prediction of the local concentration–effect relationship: The role of physiologically based pharmacokinetics and quantitative systems pharmacology and toxicology in the evolution of model-informed drug discovery and development
10.1016/j.drudis.2019.05.016 · ExternalCitation · doi-reference
Artificial intelligence in drug discovery: what is realistic, what are illusions? Part 2: a discussion of chemical and biological data
10.1016/j.drudis.2020.11.037 · ExternalCitation · doi-reference
Applications of artificial intelligence in drug development using real-world data
10.1016/j.drudis.2020.12.013 · ExternalCitation · doi-reference
Utilizing social media data for pharmacovigilance: a review
10.1016/j.jbi.2015.02.004 · ExternalCitation · doi-reference
Has drug design augmented by artificial intelligence become a reality?
10.1016/j.tips.2019.09.004 · ExternalCitation · doi-reference
ToxCast chemical landscape: paving the road to 21st century toxicology
10.1021/acs.chemrestox.6b00135 · ExternalCitation · doi-reference
Deep learning for toxicity prediction in drug development
10.1021/acs.jcim.5b00238 · ExternalCitation · doi-reference
Analyzing learned molecular representations for property prediction
10.1021/acs.jcim.9b00237 · ExternalCitation · doi-reference
druGAN: an advanced generative adversarial autoencoder model for de novo generation of new molecules with desired molecular properties in silico
10.1021/acs.molpharmaceut.7b00346 · ExternalCitation · doi-reference
Artificial intelligence for drug discovery, biomarker development, and generation of novel chemistry
10.1021/acs.molpharmaceut.8b00930 · ExternalCitation · doi-reference
Pharmacogenomics in the clinic
10.1038/nature15817 · ExternalCitation · doi-reference
Mass-spectrometric exploration of proteome structure and function
10.1038/nature19949 · ExternalCitation · doi-reference
Drug repurposing: progress, challenges and recommendations
10.1038/nrd.2018.168 · ExternalCitation · doi-reference
How to improve R&D productivity: the pharmaceutical industry’s grand challenge
10.1038/nrd3078 · ExternalCitation · doi-reference
An analysis of the attrition of drug candidates from four major pharmaceutical companies
10.1038/nrd4609 · ExternalCitation · doi-reference
Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning
10.1038/s41551-018-0195-0 · ExternalCitation · doi-reference
Artificial intelligence in healthcare
10.1038/s41551-018-0305-z · ExternalCitation · doi-reference
Exploiting machine learning for end-to-end drug discovery and development
10.1038/s41563-019-0338-z · ExternalCitation · doi-reference
Applications of machine learning in drug discovery and development
10.1038/s41573-019-0024-5 · ExternalCitation · doi-reference
Highly accurate protein structure prediction with AlphaFold
10.1038/s41586-021-03819-2 · ExternalCitation · doi-reference
Deep learning enables rapid identification of potent DDR1 kinase inhibitors
10.1038/s41587-019-0224-x · ExternalCitation · doi-reference
High-performance medicine: the convergence of human and artificial intelligence
10.1038/s41591-018-0300-7 · ExternalCitation · doi-reference
Cancer drug response profile scan (CDRscan): a deep learning model that predicts drug effectiveness from cancer genomic signature
10.1038/s41598-018-27214-6 · ExternalCitation · doi-reference
Artificial intelligence and machine learning in clinical development: a translational perspective
10.1038/s41746-019-0148-3 · ExternalCitation · doi-reference
Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity
10.1038/tpj.2013.39 · ExternalCitation · doi-reference
Machine learning in medicine
10.1056/nejmra1814259 · ExternalCitation · doi-reference
Artificial intelligence in drug discovery: Applications and techniques
10.1093/bib/bbab430 · ExternalCitation · doi-reference
Deep learning for healthcare: review, opportunities and challenges
10.1093/bib/bbx044 · ExternalCitation · doi-reference
Deep learning-based prediction of drug response in cancer
10.1093/bib/bbz171 · ExternalCitation · doi-reference
GraphDTA: predicting drug–target binding affinity with graph neural networks
10.1093/bioinformatics/btaa921 · ExternalCitation · doi-reference
DeepSite: protein-binding site predictor using 3D-convolutional neural networks
10.1093/bioinformatics/btx350 · ExternalCitation · doi-reference
Modeling polypharmacy side effects with graph convolutional networks
10.1093/bioinformatics/bty294 · ExternalCitation · doi-reference
DeepDTA: deep drug–target binding affinity prediction
10.1093/bioinformatics/bty593 · ExternalCitation · doi-reference
deepDR: A network-based deep learning approach to in silico drug repositioning
10.1093/bioinformatics/btz418 · ExternalCitation · doi-reference
PubChem substance and compound databases
10.1093/nar/gkaa971 · ExternalCitation · doi-reference
The SIDER database of drugs and side effects
10.1093/nar/gkv1075 · ExternalCitation · doi-reference
ChEMBL: towards direct deposition of bioassay data
10.1093/nar/gky1075 · ExternalCitation · doi-reference
Machine learning approaches and their applications in drug discovery and design
10.1111/cbdd.14057 · ExternalCitation · doi-reference
Data-driven prediction of drug effects and interactions
10.1126/scitranslmed.3003377 · ExternalCitation · doi-reference
Drug–drug interaction through molecular structure similarity analysis
10.1136/amiajnl-2012-000935 · ExternalCitation · doi-reference
VigiBase, the WHO global ICSR database system: basic facts
10.1177/009286150804200501 · ExternalCitation · doi-reference
Molecular de novo design through deep reinforcement learning
10.1186/s13321-017-0235-x · ExternalCitation · doi-reference
The CompTox chemistry dashboard: a community data resource for environmental chemistry
10.1186/s13321-017-0247-6 · ExternalCitation · doi-reference
Tox21 challenge to build predictive models of nuclear receptor and stress response pathways as mediated by exposure to environmental chemicals and drugs
10.3389/fenvs.2015.00085 · ExternalCitation · doi-reference
Recent advances of deep learning in bioinformatics and computational biology
10.3389/fgene.2019.00214 · ExternalCitation · doi-reference
