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A Comprehensive Review on Deep Synergistic Drug Prediction Techniques for Cancer

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Abstract

Drug combination therapies are successfully used in the treatment of cancer disease. The synergistic drug combinations not only increase the drug efficacy, but also reduce the drug dosage. The exhaustive combination of synergistic drugs makes it more challenging. The deep learning techniques are used to handle this issue. In this paper, a comprehensive review on deep synergistic drug combination is presented. The theoretical aspects of drug synergy are discussed with their mathematical formulation. The deep synergistic drug combinations prediction techniques are also deliberated in detail. The applicability of deep learning tools and software packages in prediction models is investigated. The datasets and performance measures are studied at length. The challenges and future research directions in field of drug synergy are discussed with a view to benefit the young researchers and scientists.

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  1. Computer Science and Engineering Department, National Institute of Technology, Hamirpur, Himachal Pradesh, 177005, India

    Vijay Kumar & Nitin Dogra

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Kumar, V., Dogra, N. A Comprehensive Review on Deep Synergistic Drug Prediction Techniques for Cancer. Arch Computat Methods Eng 29, 1443–1461 (2022). https://doi.org/10.1007/s11831-021-09617-3

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