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Traditional dose selection for oncology registration trials typically employs a one- or two-step single maximum tolerated dose (MTD) approach. However, this approach may not be appropriate for molecularly targeted therapy that tends to have…

统计方法学 · 统计学 2023-09-28 Jason J. Z. Liao , Ekaterine Asatiani , Qingyang Liu , Kevin Hou

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

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

Project Optimus, an initiative by the FDA's Oncology Center of Excellence, seeks to reform the dose-optimization and dose-selection paradigm in oncology. We propose a dose-optimization design that considers plateau efficacy profiles,…

应用统计 · 统计学 2025-04-22 Rebecca B. Silva , Bin Cheng , Shing M. Lee

The conventional more-is-better dose selection paradigm, which targets the maximum tolerated dose (MTD), is not suitable for the development of targeted therapies and immunotherapies as the efficacy of these novel therapies may not increase…

统计方法学 · 统计学 2023-08-31 Peng Yang , Daniel Li , Ruitao Lin , Bo Huang , Ying Yuan

The traditional more-is-better dose selection paradigm, developed based on cytotoxic chemotherapeutics, is often problematic When applied to the development of novel molecularly targeted agents (e.g., kinase inhibitors, monoclonal…

统计方法学 · 统计学 2022-11-04 Liyun Jiang , Ying Yuan

Phase I dose escalation trials in oncology generally aim to find the maximum tolerated dose (MTD). However, with the advent of molecular targeted therapies and antibody drug conjugates, dose limiting toxicities are less frequently observed,…

统计方法学 · 统计学 2025-08-19 Ayon Mukherjee , Jonathan L. Moscovici , Zheng Liu

We consider a dose-optimization design for first-in-human oncology trial that aims to identify a suitable dose for late-phase drug development. The proposed approach, called the Pharmacometrics-Enabled DOse OPtimization (PEDOOP) design,…

应用统计 · 统计学 2024-06-19 Shijie Yuan , Zhanbo Huang , Jiaxin Liu , Yuan Ji

The U.S. Food and Drug Administration (FDA) launched Project Optimus to shift the objective of dose selection from the maximum tolerated dose to the optimal biological dose (OBD), optimizing the benefit-risk tradeoff. One approach…

统计方法学 · 统计学 2025-08-22 Shuqi Wang , Ying Yuan , Suyu Liu

The Project Optimus initiative by the FDA's Oncology Center of Excellence is widely viewed as a groundbreaking effort to change the $\textit{status quo}$ of conventional dose-finding strategies in oncology. Unlike in other therapeutic areas…

应用统计 · 统计学 2023-04-14 Zhenghao Jiang , Gu Mi , Ji Lin , Christelle Lorenzato , Yuan Ji

One common approach for dose optimization is a two-stage design, which initially conducts dose escalation to identify the maximum tolerated dose (MTD), followed by a randomization stage where patients are assigned to two or more doses to…

统计方法学 · 统计学 2024-11-11 Yixuan Zhao , Rachael Liu , Jianchang Lin , Ying Yuan

With the development of novel therapies such as molecularly targeted agents and immunotherapy, the maximum tolerated dose paradigm that "more is better" does not necessarily hold anymore. In this context, doses and schedules of novel…

统计方法学 · 统计学 2025-11-24 Anaïs Andrillon , Sandrine Micallef , Moreno Ursino , Pavel Mozgunov , Marie-Karelle Riviere

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

The US Food and Drug Administration (FDA) launched Project Optimus and issued guidance to reform dose-finding and selection trials, shifting the paradigm from identifying the maximum tolerable dose (MTD) to determining the optimal…

统计方法学 · 统计学 2025-09-16 Kai Chen , Yixuan Zhao , Kentaro Takeda , Ying Yuan

Phase I oncology trials aim to identify a safe dose - often the maximum tolerated dose (MTD) - for subsequent studies. Conventional designs focus on population-level toxicity modeling, with recent attention on leveraging pharmacokinetic…

应用统计 · 统计学 2026-01-13 Kyong Ju Lee , Yuan Ji

Phase I dose-finding trials in oncology seek to find the maximum tolerated dose (MTD) of a drug under a specific schedule. Evaluating drug-schedules aims at improving treatment safety while maintaining efficacy. However, while we can…

We propose Locally Optimal Restricted Designs (LORDs) for phase I/II dose-finding studies that focus on both efficacy and toxicity outcomes. As an illustrative application, we find various LORDs for a 4-parameter continuation-ratio (CR)…

统计方法学 · 统计学 2025-09-09 Oleksandr Sverdlov , Yevgen Ryeznik , Weng Kee Wong

This paper proposes a novel criterion for the allocation of patients in Phase~I dose-escalation clinical trials aiming to find the maximum tolerated dose (MTD). Conventionally, using a model-based approach the next patient is allocated to…

统计方法学 · 统计学 2018-07-17 Pavel Mozgunov , Thomas Jaki

Optimizing doses for multiple indications is challenging. The pooled approach of finding a single optimal biological dose (OBD) for all indications ignores that dose-response or dose-toxicity curves may differ between indications, resulting…

统计方法学 · 统计学 2024-10-07 Shuqi Wang , Peter F. Thall , Kentaro Takeda , Ying Yuan

Dose optimization is a hallmark of Project Optimus for oncology drug development. The number of doses to include in a dose optimization study depends on the totality of evidence, which is often unclear in early-phase development. With equal…

统计方法学 · 统计学 2026-01-29 Linda Sun , Yixin Ren , Cong Chen
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