Deep learning-based multi-drug synergy prediction model for individually tailored anti-cancer therapies

ABSTRACT: While synergistic drug combinations are more effective at fighting tumors with complex pathophysiology, preference compensating mechanisms, and drug resistance, the identification of novel synergistic drug combinations, especially complex higher-order combinations, remains challenging due to the size of combination space. Even though certain computational methods have been used to identify synergistic drug combinations in lieu of traditional in vitro and in vivo screening tests, the majority of previously published work has focused on predicting synergistic drug pairs for specific types of cancer and paid little attention to the sophisticated high-order combinations. The main objective of this study is to develop a deep learning-based approach that integrated multi-omics data to predict no

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PROVIDER: S-EPMC9797718 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature