In silico drug combination discovery for personalized cancer therapy

M Jeon, S Kim, S Park, H Lee, J Kang - BMC systems biology, 2018 - Springer
Background Drug combination therapy, which is considered as an alternative to single drug
therapy, can potentially reduce resistance and toxicity, and have synergistic efficacy. As drug …

Prediction of synergistic anti-cancer drug combinations based on drug target network and drug induced gene expression profiles

X Li, Y Xu, H Cui, T Huang, D Wang, B Lian, W Li… - Artificial intelligence in …, 2017 - Elsevier
Objective Synergistic drug combinations are promising therapies for cancer treatment.
However, effective prediction of synergistic drug combinations is quite challenging as …

In-silico prediction of synergistic anti-cancer drug combinations using multi-omics data

R Celebi, O Bear Don't Walk IV, R Movva, S Alpsoy… - Scientific Reports, 2019 - nature.com
Chemotherapy is a routine treatment approach for early-stage cancers, but the effectiveness
of such treatments is often limited by drug resistance, toxicity, and tumor heterogeneity …

Predictive approaches for drug combination discovery in cancer

SA Madani Tonekaboni, L Soltan Ghoraie… - Briefings in …, 2018 - academic.oup.com
Drug combinations have been proposed as a promising therapeutic strategy to overcome
drug resistance and improve efficacy of monotherapy regimens in cancer. This strategy aims …

Drug combination sensitivity scoring facilitates the discovery of synergistic and efficacious drug combinations in cancer

A Malyutina, MM Majumder, W Wang… - PLoS computational …, 2019 - journals.plos.org
High-throughput drug screening has facilitated the discovery of drug combinations in cancer.
Many existing studies adopted a full matrix design, aiming for the characterization of drug …

A novel network based linear model for prioritization of synergistic drug combinations

J Li, H Xu, RA McIndoe - PloS one, 2022 - journals.plos.org
Drug combination therapies can improve drug efficacy, reduce drug dosage, and overcome
drug resistance in cancer treatments. Current research strategies to determine which drug …

Predicting synergism of cancer drug combinations using NCI-ALMANAC data

P Sidorov, S Naulaerts, J Ariey-Bonnet… - Frontiers in …, 2019 - frontiersin.org
Drug combinations are of great interest for cancer treatment. Unfortunately, the discovery of
synergistic combinations by purely experimental means is only feasible on small sets of …

Network propagation predicts drug synergy in cancers

H Li, T Li, D Quang, Y Guan - Cancer research, 2018 - AACR
Combination therapies are commonly used to treat patients with complex diseases that
respond poorly to single-agent therapies. In vitro high-throughput drug screening is a …

A review of machine learning approaches for drug synergy prediction in cancer

A Torkamannia, Y Omidi… - Briefings in Bioinformatics, 2022 - academic.oup.com
Combinational pharmacotherapy with the synergistic/additive effect is a powerful treatment
strategy for complex diseases such as malignancies. Identifying synergistic combinations …

SynPathy: Predicting drug synergy through drug-associated pathways using deep learning

YC Tang, A Gottlieb - Molecular Cancer Research, 2022 - AACR
Drug combination therapy has become a promising therapeutic strategy for cancer
treatment. While high-throughput drug combination screening is effective for identifying …