在原区域已获批上市的新药往往会被要求重复整个药物研发过程以评价该药对于新区域人群的有效性和安全性，这样不仅造成大量资源浪费，也导致新区域有需求的患者不能及时得到有效治疗。国际多区域临床研究MRCT是要证明新药在总体人群上的有效性和安全性并在此基础上外推至各参与区域人群，期望同时满足多个国家或地区的注册需求，实现该药物的全球同步上市。由于目前MRCT的评价体系还很不完善，如何在有限样本量的情况下，充分利用MRCT 数据科学合理的评价新药在目标区域人群中的有效性和安全性已成为当前迫切需要解决的重要问题之一。本项目借助于折扣因子这一概念，将MRCT转化为虚拟试验，从新的角度利用贝叶斯层次模型，探讨MRCT中目标区域人群药物疗效评价的科学性和可行性，研究重点集中在基于折扣因子的贝叶斯层次模型构建、折扣因子的最优化选择等关键点，从我国的实际情况出发构建完善的MRCT评价体系。

The new drug which has been approved in the original area will often be asked to repeat the entire drug development process to evaluate the efficacy and safety in the new areas. However, the repeated drug development process not only caused a large number of resources waste, but also made the patients in new areas can not get the effective treatment in time. Multiple regional clinical trial (MRCT) aims to prove the efficacy and safety of the new drug in the general population, extrapolate the trial results to each regional population and realize the drug registered in each participating region at the same time. Because MRCT evaluation system is much poor at present, in which there are no sufficient theoretical foundation and concrete technical guidelines. How to make full use of MRCT data to evaluate the efficacy and safety of the new drug in the target area population scientifically and reasonably with limited sample size has become an urgent issue to be solved. This project aims to develop innovative and feasible evaluation system for the target region in MRCT, by converting MRCT into a virtual trial with a discount factor and using bayesian methods. The research will focus on the construction of bayesian hierarchical model based on the discount factor, discount factor optimization selection and so on.