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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…

Methodology · Statistics 2023-09-13 Ying Yuan , Heng Zhou , Suyu Liu

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…

Methodology · Statistics 2022-11-04 Liyun Jiang , Ying Yuan

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…

Methodology · Statistics 2024-06-04 Yuhan Li , Yiding Zhang , Gu Mi , Ji Lin

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…

Methodology · Statistics 2025-08-22 Shuqi Wang , Ying Yuan , Suyu Liu

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…

Methodology · Statistics 2023-09-28 Jason J. Z. Liao , Ekaterine Asatiani , Qingyang Liu , Kevin Hou

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,…

Applications · Statistics 2025-04-22 Rebecca B. Silva , Bin Cheng , Shing M. Lee

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…

Applications · Statistics 2023-04-14 Zhenghao Jiang , Gu Mi , Ji Lin , Christelle Lorenzato , Yuan Ji

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)…

Methodology · Statistics 2022-09-07 Beibei Guo , Ying Yuan

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…

Methodology · Statistics 2018-07-17 Pavel Mozgunov , Thomas Jaki

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…

Methodology · Statistics 2024-11-11 Yixuan Zhao , Rachael Liu , Jianchang Lin , Ying Yuan

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…

Applications · Statistics 2024-12-12 Cong Chen , Mo Huang , Xuekui Zhang

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…

Methodology · Statistics 2024-10-07 Shuqi Wang , Peter F. Thall , Kentaro Takeda , Ying Yuan

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…

Applications · Statistics 2026-03-24 Xuemin Gu , Cong Xu , Lei Xu , Ying Yu

The primary objective of Phase I oncology trials is to assess the safety and tolerability of novel therapeutics. Conventional dose escalation methods identify the maximum tolerated dose (MTD) based on dose-limiting toxicity (DLT). However,…

Methodology · Statistics 2024-09-02 Yunlong Yang , Ying Yuan

The primary objective of phase I cancer clinical trials is to evaluate the safety of a new experimental treatment and to find the maximum tolerated dose (MTD). We show that the MTD estimation problem can be regarded as a level set…

Machine Learning · Statistics 2025-04-15 Keiichiro Seno , Kota Matsui , Shogo Iwazaki , Yu Inatsu , Shion Takeno , Shigeyuki Matsui

Model-assisted designs have garnered significant attention in recent years due to their high accuracy in identifying the maximum tolerated dose (MTD) and their operational simplicity. To identify the MTD, they employ estimated dose limiting…

Applications · Statistics 2025-08-19 Rentaro Wakayama , Tomotaka Momozaki , Shuji Ando

Background: Phase I trials desire to identify the maximum tolerated dose (MTD) early and proceed quickly to an expansion cohort or phase II trial for efficacy. We propose an early completion method based on multiple dosages to accelerate…

Quantitative Methods · Quantitative Biology 2021-10-04 Masahiro Kojima

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…

Applications · Statistics 2026-01-13 Kyong Ju Lee , Yuan Ji

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,…

Applications · Statistics 2024-06-19 Shijie Yuan , Zhanbo Huang , Jiaxin Liu , Yuan Ji

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…

Applications · Statistics 2023-01-12 Rebecca B. Silva , Bin Cheng , Richard D. Carvajal , Shing M. Lee
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