In silico drug combination discovery for personalized cancer therapy
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 …
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
Objective Synergistic drug combinations are promising therapies for cancer treatment.
However, effective prediction of synergistic drug combinations is quite challenging as …
However, effective prediction of synergistic drug combinations is quite challenging as …
In-silico prediction of synergistic anti-cancer drug combinations using multi-omics data
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 …
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 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
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 …
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 …
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 …
synergistic combinations by purely experimental means is only feasible on small sets of …
Network propagation predicts drug synergy in cancers
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 …
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 …
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 …
treatment. While high-throughput drug combination screening is effective for identifying …