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 …
A computational approach for identifying synergistic drug combinations
KM Gayvert, O Aly, J Platt, MW Bosenberg… - PLoS computational …, 2017 - journals.plos.org
A promising alternative to address the problem of acquired drug resistance is to rely on
combination therapies. Identification of the right combinations is often accomplished through …
combination therapies. Identification of the right combinations is often accomplished through …
Machine learning approaches for drug combination therapies
B Güvenç Paltun, S Kaski… - Briefings in …, 2021 - academic.oup.com
Drug combination therapy is a promising strategy to treat complex diseases such as cancer
and infectious diseases. However, current knowledge of drug combination therapies …
and infectious diseases. However, current knowledge of drug combination therapies …
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 …
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 …
Artificial intelligence and machine learning methods in predicting anti-cancer drug combination effects
Drug combinations have exhibited promising therapeutic effects in treating cancer patients
with less toxicity and adverse side effects. However, it is infeasible to experimentally screen …
with less toxicity and adverse side effects. However, it is infeasible to experimentally screen …
Integrated network pharmacology approach for drug combination discovery: a multi-cancer case study
Simple Summary Current treatments for complex diseases, including cancer, are generally
characterized by high toxicity due to their low selectivity for target cells. Moreover, patients …
characterized by high toxicity due to their low selectivity for target cells. Moreover, patients …
Systems biology approaches for advancing the discovery of effective drug combinations
KA Ryall, AC Tan - Journal of cheminformatics, 2015 - Springer
Complex diseases like cancer are regulated by large, interconnected networks with many
pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer …
pathways affecting cell proliferation, invasion, and drug resistance. However, current cancer …
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 …
Prediction of drug combinations by integrating molecular and pharmacological data
Combinatorial therapy is a promising strategy for combating complex disorders due to
improved efficacy and reduced side effects. However, screening new drug combinations …
improved efficacy and reduced side effects. However, screening new drug combinations …