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Related papers: ROSE: Randomized Optimal Selection Design for Dose…

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An individualized dose rule recommends a dose level within a continuous safe dose range based on patient level information such as physical conditions, genetic factors and medication histories. Traditionally, personalized dose finding…

Methodology · Statistics 2020-07-21 Liangyu Zhu , Wenbin Lu , Michael R. Kosorok , Rui Song

The Randomized Controlled Trial (RCT) or A/B testing is considered the gold standard method for estimating causal effects. Fisher famously advocated randomly allocating experiment units into treatment and control groups to preclude…

Methodology · Statistics 2024-04-17 Deddy Jobson , Li Yilin , Naoki Nishimura , Yang Jie , Koya Ohashi , Takeshi Matsumoto

We propose to use Bayesian optimization (BO) to improve the efficiency of the design selection process in clinical trials. BO is a method to optimize expensive black-box functions, by using a regression as a surrogate to guide the search.…

Methodology · Statistics 2021-05-20 Jakob Richter , Tim Friede , Jörg Rahnenführer

The treatment assignment mechanism in a randomized clinical trial can be optimized for statistical efficiency within a specified class of randomization mechanisms. Optimal designs of this type have been characterized in terms of the…

Methodology · Statistics 2025-09-03 Wei Zhang , Zhiwei Zhang , Aiyi Liu

Immunotherapies and targeted therapies have gained popularity due to their promising therapeutic effects across multiple treatment areas. The focus of early phase dose-finding clinical trials has shifted from finding the maximum tolerated…

Methodology · Statistics 2023-12-27 Hao Sun , Jieqi Tu

We consider the optimal design problem for identifying effective dose combinations within drug combination studies where the effect of the combination of two drugs is investigated. Drug combination studies are becoming increasingly…

We consider robust optimal experimental design (ROED) for nonlinear Bayesian inverse problems governed by partial differential equations (PDEs). An optimal design is one that maximizes some utility quantifying the quality of the solution of…

Numerical Analysis · Mathematics 2026-05-01 Abhijit Chowdhary , Ahmed Attia , Alen Alexanderian

In a sequential multiple-assignment randomized trial (SMART), a sequence of treatments is given to a patient over multiple stages. In each stage, randomization may be done to allocate patients to different treatment groups. Even though…

Methodology · Statistics 2024-01-09 Rik Ghosh , Bibhas Chakraborty , Inbal Nahum-Shani , Megan E. Patrick , Palash Ghosh

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)…

Methodology · Statistics 2025-09-09 Oleksandr Sverdlov , Yevgen Ryeznik , Weng Kee Wong

Development and optimization of biopharmaceutical production processes with cell cultures is cost- and time-consuming and often performed rather empirically. Efficient optimization of multiple-objectives like process time, viable cell…

Machine Learning · Computer Science 2022-05-09 Tanja Hernández Rodríguez , Anton Sekulic , Markus Lange-Hegermann , Björn Frahm

Allocating patients to treatment arms during a trial based on the observed responses accumulated prior to the decision point, and sequential adaptation of this allocation,, could minimize the expected number of failures or maximize total…

Methodology · Statistics 2022-09-01 Zhongying Xu , Andriy I. Bandos , Tianzhou Ma , Lu Tang , Victor B. Talisa , Chung-Chou H. Chang

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…

Methodology · Statistics 2016-01-06 Holger Dette , Katrin Kettelhake , Kirsten Schorning , Weng Kee Wong , Frank Bretz

Minimizing the number of patients exposed to potentially harmful drugs in early onco logical trials is a major concern during planning. Adaptive designs account for the inherent uncertainty about the true effect size by determining the…

Applications · Statistics 2016-05-03 Kevin Kunzmann , Meinhard Kieser

Group sequential designs (GSDs) are well established and the most commonly used adaptive design in confirmatory clinical trials with interim analyses. However, they remain underutilised, and their implementation involves unique theoretical…

Methodology · Statistics 2025-09-09 Zhangyi He , Suzie Cro , Laurent Billot

Recently, the strategy for dose optimization in oncology has shifted to conduct Phase 2 randomized controlled trials with multiple doses. Optimal biologic dose selection from Phase 1 trial data to determine candidate doses for Phase 2…

Methodology · Statistics 2023-02-14 Masahiro Kojima

Effective disease treatment often requires precise control of the release of the active pharmaceutical ingredient (API). In this work, we present a computational inverse design approach to determine the optimal drug composition that yields…

Computational Engineering, Finance, and Science · Computer Science 2025-07-23 Rabia Altunay , Jarkko Suuronen , Eero Immonen , Lassi Roininen , Jari Hämäläinen

In phase I dose escalation studies for dual-agent combinations, at least one drug often has an established monotherapy dose. Consequently, substantial prior clinical safety data often exist for one or more monotherapies, allowing the study…

Methodology · Statistics 2026-05-07 Yuxuan Chen , Haiming Zhou , Keiko Nakajima , Philip He

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…

Applications · Statistics 2024-04-03 Cheng-Han Yang , Peter F. Thall , Ruitao Lin

The Finite Selection Model (FSM) was developed by Carl Morris in the 1970s for the design of the RAND Health Insurance Experiment (HIE) (Morris 1979, Newhouse et al. 1993), one of the largest and most comprehensive social science…

Methodology · Statistics 2023-07-06 Ambarish Chattopadhyay , Carl N. Morris , Jose R. Zubizarreta

In this paper, the tools provided by the theory of Optimal Experimental Design are applied to a nonlinear calibration model. This is motivated by the need of estimating radiation doses using radiochromic films for radiotherapy purposes. The…

Applications · Statistics 2020-05-20 Jesús López-Fidalgo , Mariano Amo-Salas