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.

药物联合疗法已成功用于治疗癌症疾病。协同药物组合不仅提高了药效，而且减少了药物剂量。协同药物的详尽组合使其更具挑战性。深度学习技术用于处理这个问题。在本文中，对深度协同药物组合进行了全面综述。药物协同的理论方面与其数学公式进行了讨论。还详细讨论了深度协同药物组合预测技术。研究了深度学习工具和软件包在预测模型中的适用性。对数据集和性能指标进行了详细研究。