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Clinical trials are vital for evaluation of safety and efficacy of new treatments. However, clinical trials are resource-intensive, time-consuming and expensive to conduct, where errors in trial design, reduced efficacy, and safety events…

人工智能 · 计算机科学 2025-05-19 Trisha Das , Afrah Shafquat , Beigi Mandis , Jacob Aptekar , Jimeng Sun

In recent years, basket trials, which allow the evaluation of an experimental therapy across multiple tumor types within a single protocol, have gained prominence in early-phase oncology development. Unlike traditional trials, which…

应用统计 · 统计学 2025-07-18 Haiming Zhou , Rex Shen , Sutan Wu , Philip He

In oncology phase I trials, model-assisted designs have been increasingly adopted because they enable adaptive yet operationally simple dose adjustment based on accumulating safety data, leading to a paradigm shift in dose-escalation…

统计方法学 · 统计学 2026-02-23 Kana Yamada , Hisato Sunami , Kentaro Takeda , Keisuke Hanada , Masahiro Kojima

Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this paper, we extend the key ideas to disease areas outside of oncology, developing a…

统计方法学 · 统计学 2020-06-01 Haiyan Zheng , James M. S. Wason

With the advancement of precision medicine there is an increasing need for design and analysis methods in clinical trials with the objective of investigating effect heterogeneity and estimating subgroup effects. As this requires precise…

统计方法学 · 统计学 2026-03-12 Shirin Golchi , Satoshi Morita

This paper introduces a new Phase I design aimed at enhancing the performance of existing methods, including algorithm-based, model-based, and model-assisted designs. The design, developed by integrating the concept of Fisher information,…

应用统计 · 统计学 2024-12-11 Xiaojun Zhu

Motivation: Drug repurposing is a viable solution for reducing the time and cost associated with drug development. However, thus far, the proposed drug repurposing approaches still need to meet expectations. Therefore, it is crucial to…

机器学习 · 计算机科学 2024-05-21 Ali Gharizadeh , Karim Abbasi , Amin Ghareyazi , Mohammad R. K. Mofrad , Hamid R. Rabiee

Broadening eligibility criteria in cancer trials has been advocated to represent the true patient population more accurately. While the advantages are clear in terms of generalizability and recruitment, novel dose-finding designs are needed…

应用统计 · 统计学 2023-01-12 Rebecca B. Silva , Bin Cheng , Richard D. Carvajal , Shing M. Lee

The keyboard design is a novel phase I dose-finding method that is simple and has good operating characteristics. This paper studies theoretical properties of the keyboard design, including the optimality of its decision rules, coherence in…

统计方法学 · 统计学 2017-12-20 Haitao Pan , Ruitao Lin , Ying Yuan

The optimization of composition and processing to obtain materials that exhibit desirable characteristics has historically relied on a combination of scientist intuition, trial and error, and luck. We propose a methodology that can…

机器学习 · 统计学 2017-07-20 Julia Ling , Max Hutchinson , Erin Antono , Sean Paradiso , Bryce Meredig

We propose a data-dependent early completion of dose finding trials for drug-combination. The early completion is determined when a beta-binomial probability for dose retainment with the trial data and the number of remaining patients is…

统计方法学 · 统计学 2022-02-10 Masahiro Kojima

When incorporating historical control data into the analysis of current randomized controlled trial data, it is critical to account for differences between the datasets. When the cause of the difference is an unmeasured factor and…

统计方法学 · 统计学 2025-09-10 Tomohiro Ohigashi , Kazushi Maruo , Takashi Sozu , Masahiko Gosho

Use of historical control data to augment a small internal control arm in a randomized control trial (RCT) can lead to significant improvement of the efficiency of the trial. It introduces the risk of potential bias, since the historical…

统计方法学 · 统计学 2022-10-05 Jixian Wang , Hongtao Zhang , Ram Tiwari

An early phase clinical trial is the first step in evaluating the effects in humans of a potential new anti-disease agent or combination of agents. Usually called "phase I" or "phase I/II" trials, these experiments typically have the…

统计方法学 · 统计学 2010-12-01 Peter F. Thall

FDA's Project Optimus initiative for oncology drug development emphasizes selecting a dose that optimizes both efficacy and safety. When an inferentially adaptive Phase 2/3 design with dose selection is implemented to comply with the…

应用统计 · 统计学 2024-12-12 Cong Chen , Mo Huang , Xuekui Zhang

An important task in drug development is to identify patients, which respond better or worse to an experimental treatment. Identifying predictive covariates, which influence the treatment effect and can be used to define subgroups of…

统计方法学 · 统计学 2018-11-27 Marius Thomas , Björn Bornkamp , Katja Ickstadt

Bayesian clinical trials can benefit of available historical information through the elicitation of informative prior distributions. Concerns are however often raised about the potential for prior-data conflict and the impact of Bayes test…

统计方法学 · 统计学 2022-12-01 Silvia Calderazzo , Annette Kopp-Schneider

The US FDA's Project Optimus initiative that emphasizes dose optimization prior to marketing approval represents a pivotal shift in oncology drug development. It has a ripple effect for rethinking what changes may be made to conventional…

统计方法学 · 统计学 2024-06-04 Yuhan Li , Yiding Zhang , Gu Mi , Ji Lin

There is currently a focus on statistical methods which can use external trial information to help accelerate the discovery, development and delivery of medicine. Bayesian methods facilitate borrowing which is "dynamic" in the sense that…

统计方法学 · 统计学 2024-08-09 Sophia Axillus , Alex Lewin , Darren Scott

The US Food and Drug Administration launched Project Optimus with the aim of shifting the paradigm of dose-finding and selection towards identifying the optimal biological dose that offers the best balance between benefit and risk, rather…

统计方法学 · 统计学 2023-09-13 Ying Yuan , Heng Zhou , Suyu Liu