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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…

In a recent paper Dette et al. (2014) introduced optimal design problems for dose fnding studies with an active control. These authors concentrated on regression models with normal distributed errors (with known variance) and the problem of…

Methodology · Statistics 2014-11-03 Holger Dette , Katrin Kettelhake , Frank Bretz

We consider design issues for toxicology studies when we have a continuous response and the true mean response is only known to be a member of a class of nested models. This class of non-linear models was proposed by toxicologists who were…

Statistics Theory · Mathematics 2010-11-29 Holger Dette , Andrey Pepelyshev , Piter Shpilev , Weng Kee Wong

An important tool to evaluate the performance of any design is an optimal benchmark proposed by O'Quigley and others (2002, Biostatistics 3(1), 51-56) that provides an upper bound on the performance of a design under a given scenario. The…

Statistics Theory · Mathematics 2018-03-06 Pavel Mozgunov , Thomas Jaki , Xavier Paoletti

The issue of determining not only an adequate dose but also a dosing frequency of a drug arises frequently in Phase II clinical trials. This results in the comparison of models which have some parameters in common. Planning such studies…

Methodology · Statistics 2017-11-16 Kirsten Schorning , Maria Konstantinou

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

We construct optimal designs for estimating fetal malformation rate, prenatal death rate and an overall toxicity index in a toxicology study under a broad range of model assumptions. We use Weibull distributions to model these rates and…

Methodology · Statistics 2009-02-10 Holger Dette , Andrey Pepelyshev , Weng Kee Wong

In Phase I/II dose-finding trials, the objective is to find the Optimal Biological Dose (OBD), a dose that is both safe and efficacious that maximises some optimality criterion based on safety and efficacy. This is further complicated when…

Applications · Statistics 2022-03-31 Helen Barnett , Oliver Boix , Dimitris Kontos , Thomas Jaki

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 purpose of a phase I dose-finding clinical trial is to investigate the toxicity profiles of various doses for a new drug and identify the maximum tolerated dose. Over the past three decades, various dose-finding designs have been…

Methodology · Statistics 2021-11-25 Yunshan Duan , Shijie Yuan , Yuan Ji , Peter Mueller

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…

Computation · Statistics 2025-03-11 Michael Sweeting , Daniel Slade , Dan Jackson , Kristian Brock

A common problem in Phase II clinical trials is the comparison of dose response curves corresponding to different treatment groups. If the effect of the dose level is described by parametric regression models and the treatments differ in…

Statistics Theory · Mathematics 2016-03-16 Chrystel Feller , Kirsten Schorning , Holger Dette , Georgina Bermann , Björn Bornkamp

In the development of new cancer treatment, an essential step is to determine the maximum tolerated dose (MTD) via phase I clinical trials. Generally speaking, phase I trial designs can be classified as either model-based or algorithm-based…

Applications · Statistics 2022-03-02 Huaqing Jin , Wenbin Du , Guosheng Yin

We consider the problem of constructing optimal designs for population pharmacokinetics which use random effect models. It is common practice in the design of experiments in such studies to assume uncorrelated errors for each subject. In…

Applications · Statistics 2010-11-16 Holger Dette , Andrey Pepelyshev , Tim Holland-Letz

We propose a Bayesian optimal phase 2 design for jointly monitoring efficacy and toxicity, referred to as BOP2-TE, to improve the operating characteristics of the BOP2 design proposed by Zhou et al. (2017). BOP2-TE utilizes a…

Methodology · Statistics 2024-08-13 Kai Chen , Heng Zhou , J. Jack Lee , Ying Yuan

In this article, we propose a phase I-II design in two stages for the combination of molecularly targeted therapies. The design is motivated by a published case study that combines a MEK and a PIK3CA inhibitors; a setting in which higher…

Methodology · Statistics 2025-05-21 José L. Jiménez , Mourad Tighiouart

Many chemical and biological experiments involve multiple treatment factors and often it is convenient to fit a nonlinear model in these factors. This nonlinear model can be mechanistic, empirical or a hybrid of the two. Motivated by…

Computation · Statistics 2018-10-09 Yuanzhi Huang , Steven Gilmour , Kalliopi Mylona , Peter Goos

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…

Methodology · Statistics 2017-12-20 Haitao Pan , Ruitao Lin , Ying Yuan

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

We propose a computational approach to constructing exact designs on finite design spaces that are optimal for multiresponse regression experiments under a combination of the standard linear and specific 'sparsity' constraints. The linear…

Methodology · Statistics 2026-02-13 Lenka Filová , Pál Somogyi , Radoslav Harman
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