寻找抗癌药物的协同剂量组合。

Yin Zuojing, Deng Zeliang, Zhao Wenyan, Cao Zhiwei

Shanghai Tenth People's Hospital, School of Life Sciences and Technology, Tongji University, Shanghai, China.

Front Pharmacol. 2018 May 22;9:535. doi: 10.3389/fphar.2018.00535. eCollection 2018.

Recent development has enabled synergistic drugs in treating a wide range of cancers. Being highly context-dependent, however, identification of successful ones often requires screening of combinational dose on different testing platforms in order to gain the best anticancer effects. To facilitate the development of effective computational models, we reviewed the latest strategy in searching optimal dose combination from three perspectives: (1) mainly experimental-based approach; (2) Computational-guided experimental approach; and (3) mainly computational-based approach. In addition to the introduction of each strategy, critical discussion of their advantages and disadvantages were also included, with a strong focus on the current applications and future improvements.

近年来的发展使得协同药物可用于治疗多种癌症。然而，由于高度依赖具体情况，确定成功的协同药物通常需要在不同测试平台上筛选联合剂量，以获得最佳抗癌效果。为了促进有效计算模型的开发，我们从三个角度回顾了寻找最佳剂量组合的最新策略：（1）主要基于实验的方法；（2）计算指导的实验方法；（3）主要基于计算的方法。除了介绍每种策略外，还对其优缺点进行了批判性讨论，重点关注当前应用和未来改进。