Harnessing machine learning to find synergistic combinations for FDA-approved cancer drugs

Combination therapy is a fundamental strategy in cancer chemotherapy. It involves administering two or more anti-cancer agents to increase efficacy and overcome multidrug resistance compared to monotherapy. However, drug combinations can exhibit synergy, additivity, or antagonism. This study present...

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Vydáno v:	Scientific reports Ročník 14; číslo 1; s. 2428 - 23
Hlavní autoři:	Abd El-Hafeez, Tarek, Shams, Mahmoud Y., Elshaier, Yaseen A. M. M., Farghaly, Heba Mamdouh, Hassanien, Aboul Ella
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	London Nature Publishing Group UK 29.01.2024 Nature Publishing Group Nature Portfolio
Témata:	631/154 631/337 631/532 631/67 639/705/1046 639/705/117 639/705/258 692/699 692/700 Antagonism Antitumor agents Cancer therapies Chemotherapy Colorectal cancer Colorectal carcinoma Data collection DNA damage Drug interaction Drug interactions Gemcitabine Histone deacetylase Humanities and Social Sciences Inhibitors Learning algorithms Lung carcinoma Machine learning Melanoma multidisciplinary Multidrug resistance Prostate carcinoma Regression analysis Science Science (multidisciplinary) Synergism TOR protein
ISSN:	2045-2322, 2045-2322
On-line přístup:	Získat plný text
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