A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions

TN Jarada, JG Rokne, R Alhajj - Journal of cheminformatics, 2020 - Springer
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs
and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an …

Concepts of artificial intelligence for computer-assisted drug discovery

X Yang, Y Wang, R Byrne, G Schneider… - Chemical …, 2019 - ACS Publications
Artificial intelligence (AI), and, in particular, deep learning as a subcategory of AI, provides
opportunities for the discovery and development of innovative drugs. Various machine …

Predicting drug–disease associations through layer attention graph convolutional network

Z Yu, F Huang, X Zhao, W Xiao… - Briefings in …, 2021 - academic.oup.com
Background: Determining drug–disease associations is an integral part in the process of
drug development. However, the identification of drug–disease associations through wet …

Drug repurposing: progress, challenges and recommendations

S Pushpakom, F Iorio, PA Eyers, KJ Escott… - Nature reviews Drug …, 2019 - nature.com
Given the high attrition rates, substantial costs and slow pace of new drug discovery and
development, repurposing of'old'drugs to treat both common and rare diseases is …

Drug repurposing from the perspective of pharmaceutical companies

Y Cha, T Erez, IJ Reynolds, D Kumar… - British journal of …, 2018 - Wiley Online Library
Drug repurposing holds the potential to bring medications with known safety profiles to new
patient populations. Numerous examples exist for the identification of new indications for …

A survey of current trends in computational drug repositioning

J Li, S Zheng, B Chen, AJ Butte… - Briefings in …, 2016 - academic.oup.com
Computational drug repositioning or repurposing is a promising and efficient tool for
discovering new uses from existing drugs and holds the great potential for precision …

Label propagation prediction of drug-drug interactions based on clinical side effects

P Zhang, F Wang, J Hu, R Sorrentino - Scientific reports, 2015 - nature.com
Drug-drug interaction (DDI) is an important topic for public health and thus attracts attention
from both academia and industry. Here we hypothesize that clinical side effects (SEs) …

Data-driven prediction of drug effects and interactions

NP Tatonetti, PP Ye, R Daneshjou… - Science translational …, 2012 - science.org
Adverse drug events remain a leading cause of morbidity and mortality around the world.
Many adverse events are not detected during clinical trials before a drug receives approval …

Predicting drug-disease associations by using similarity constrained matrix factorization

W Zhang, X Yue, W Lin, W Wu, R Liu, F Huang, F Liu - BMC bioinformatics, 2018 - Springer
Background Drug-disease associations provide important information for the drug discovery.
Wet experiments that identify drug-disease associations are time-consuming and expensive …

In silico methods for drug repurposing and pharmacology

RA Hodos, BA Kidd, K Shameer… - … Systems Biology and …, 2016 - Wiley Online Library
Data in the biological, chemical, and clinical domains are accumulating at ever‐increasing
rates and have the potential to accelerate and inform drug development in new ways …