报告人： 赵赛骏

报告题目： Precision generalized phase I-II designs

时间： 2026年11月20日（周五）09:00—09:40

地点： 线上腾讯会议（会议号：201-824-402）

报告摘要：

A new family of precision Bayesian dose optimization designs, PGen I-II, based on early efficacy, early toxicity, and long-term time to treatment failure is proposed. A PGen I-II design refines a Gen I-II design by accounting for patient heterogeneity characterized by subgroups that may be defined by prognostic levels, disease subtypes, or biomarker categories. The design makes subgroup-specific decisions, which may be to drop an unacceptably toxic or inefficacious dose, randomize patients among acceptable doses, or identify a best dose in terms of treatment success defined in terms of time to failure over long-term follow-up. A piecewise exponential distribution for failure time is assumed, including subgroup-specific effects of dose, response, and toxicity. Latent variables are used to adaptively cluster subgroups found to have similar dose-outcome distributions, with the model simplified to borrow strength between subgroups in the same cluster. Guidelines and user-friendly computer software for implementing the design are provided. A simulation study is reported that shows the PGen I-II design is superior to similarly structured designs that either assume patient homogeneity or conduct separate trials within subgroups.

报告人简介：

赵赛骏现为美国印第安纳大学医学院生物统计与健康数据科学系博士后，分别于 2018 年和 2023 年获中国科学技术大学统计学学士和博士学位。研究方向包括贝叶斯自适应临床试验设计、精准剂量优化、历史数据借用、纵向数据分析和因果中介分析。他的临床试验研究关注如何结合早期疗效、毒性和长期结局，为不同患者亚组选择合适剂量，并探索如何借用历史数据提高试验效率。他以第一作者在 Biometrics、The Annals of Applied Statistics 和 Structural Equation Modeling 发表论文。本次报告介绍的论文获 2025 年国际贝叶斯分析学会（ISBA）生物制药分会最佳研究论文奖和印第安纳大学医学院计算生物学与生物信息学中心（CCBB）年度研讨会最佳论文报告奖。