Anticancer drug synergy prediction in understudied tissues using transfer learning.
Drug combination screening has advantages in identifying cancer treatment options with higher efficacy without degradation in terms of safety. A key challenge is that the accumulated number of observations in in-vitro drug responses varies greatly among different cancer types, where some tissues are more understudied than the others. Thus, we aim to develop a drug synergy prediction model for understudied tissues as a way of overcoming data scarcity problems.
Author(s): Kim, Yejin, Zheng, Shuyu, Tang, Jing, Jim Zheng, Wenjin, Li, Zhao, Jiang, Xiaoqian
DOI: 10.1093/jamia/ocaa212