Wang Boqian, Warden Antony R, Ding Xianting
Institute for Personalized Medicine, State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China.
Institute for Personalized Medicine, State Key Laboratory of Oncogenes and Related Genes, School of Biomedical Engineering, Shanghai Jiao Tong University, 1954 Huashan Road, Shanghai 200030, PR China.
Drug Discov Today. 2021 Nov;26(11):2646-2659. doi: 10.1016/j.drudis.2021.07.023. Epub 2021 Jul 28.
Designing optimal combinatorial drug therapies is challenging, because the drug interactions depend not only on the drugs involved, but also on their doses. With recent advances, combinatorial drug therapy is closer than ever to clinical application. Herein, we summarize approaches and advances over the past decade for identifying and optimizing drug combination therapies, with innovations across research fields, covering physical laboratory platforms for combination screening to computational models and algorithms designed for synergism prediction and optimization. By comparing different types of approach, we detail a three-step workflow that could maximize the overall optimization efficiency, thus enabling the application of personalized optimization of combinatorial drug therapy.
设计最佳的联合药物疗法具有挑战性，因为药物相互作用不仅取决于所涉及的药物，还取决于它们的剂量。随着最近的进展，联合药物疗法比以往任何时候都更接近临床应用。在此，我们总结了过去十年中用于识别和优化联合药物疗法的方法和进展，这些创新跨越了各个研究领域，涵盖了用于联合筛选的物理实验室平台，以及为协同作用预测和优化而设计的计算模型和算法。通过比较不同类型的方法，我们详细介绍了一个三步工作流程，该流程可以最大限度地提高整体优化效率，从而实现联合药物疗法个性化优化的应用。
