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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

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 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 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 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 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

In the era of targeted therapy, there has been increasing concern about the development of oncology drugs based on the "more is better" paradigm, developed decades ago for chemotherapy. Recently, the US Food and Drug Administration (FDA)…

统计方法学 · 统计学 2022-09-07 Beibei Guo , Ying Yuan

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

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

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

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design require knowledge of operating characteristics of competing…

统计计算 · 统计学 2025-03-11 Michael Sweeting , Daniel Slade , Dan Jackson , Kristian Brock

Conventionally, a first-in-human phase I trial in healthy volunteers aims to confirm the safety of a drug in humans. In such situations, volunteers should not suffer from any safety issues and simple algorithm-based dose-escalation schemes…

Identification of optimal dose combinations in early phase dose-finding trials is challenging, due to the trade-off between precisely estimating the many parameters required to flexibly model the possibly non-monotonic dose-response…

统计方法学 · 统计学 2024-02-13 James Willard , Shirin Golchi , Erica E. M. Moodie , Bruno Boulanger , Bradley P. Carlin

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

The FDA's Project Optimus initiative emphasizes patient-centered dose selection in oncology that balances efficacy and safety. We develop a framework for randomized dose optimization studies that uses clinically interpretable utility scores…

应用统计 · 统计学 2026-03-24 Xuemin Gu , Cong Xu , Lei Xu , Ying Yu

An important objective in the development of targeted therapies is to identify the populations where the treatment under consideration has positive benefit risk balance. We consider pivotal clinical trials, where the efficacy of a treatment…

Nonlinear regression models addressing both efficacy and toxicity outcomes are increasingly used in dose-finding trials, such as in pharmaceutical drug development. However, research on related experimental design problems for corresponding…

统计方法学 · 统计学 2016-01-06 Holger Dette , Katrin Kettelhake , Kirsten Schorning , Weng Kee Wong , Frank Bretz

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

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

Phase 1-2 designs provide a methodological advance over phase 1 designs for dose finding by using both clinical response and toxicity. A phase 1-2 trial still may fail to select a truly optimal dose. because early response is not a perfect…

应用统计 · 统计学 2024-04-03 Cheng-Han Yang , Peter F. Thall , Ruitao Lin
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