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Mozgunov, Pavel ; Cro, Suzie ; Lingford‐Hughes, Anne ; Paterson, Louise M. ; Jaki, Thomas

A dose‐finding design for dual‐agent trials with patient‐specific doses for one agent with application to an opiate detoxification trial

Mozgunov, Pavel, Cro, Suzie, Lingford‐Hughes, Anne, Paterson, Louise M. and Jaki, Thomas (2021) A dose‐finding design for dual‐agent trials with patient‐specific doses for one agent with application to an opiate detoxification trial. Pharmaceutical Statistics 21 (2), pp. 476-495.

Date of publication of this fulltext: 30 Sep 2025 05:55
Article
DOI to cite this document: 10.5283/epub.77858


Abstract

There is a growing interest in early phase dose-finding clinical trials studying combinations of several treatments. While the majority of dose finding designs for such setting were proposed for oncology trials, the corresponding designs are also essential in other therapeutic areas. Furthermore, there is increased recognition of recommending the patient-specific doses/combinations, rather than a ...

There is a growing interest in early phase dose-finding clinical trials studying combinations of several treatments. While the majority of dose finding designs for such setting were proposed for oncology trials, the corresponding designs are also essential in other therapeutic areas. Furthermore, there is increased recognition of recommending the patient-specific doses/combinations, rather than a single target one that would be recommended to all patients in later phases regardless of their characteristics. In this paper, we propose a dose-finding design for a dual-agent combination trial motivated by an opiate detoxification trial. The distinguishing feature of the trial is that the (continuous) dose of one compound is defined externally by the clinicians and is individual for every patient. The objective of the trial is to define the dosing function that for each patient would recommend the optimal dosage of the second compound. Via a simulation study, we have found that the proposed design results in high accuracy of individual dose recommendation and is robust to the model misspecification and assumptions on the distribution of externally defined doses.



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Details

Item typeArticle
Journal or Publication TitlePharmaceutical Statistics
Publisher:Wiley
Open Access Type:CC-License
Volume:21
Number of Issue or Book Chapter:2
Page Range:pp. 476-495
Date10 December 2021
InstitutionsInformatics and Data Science > Department Machine Learning & Data Science > Lehrstuhl für Computational Statistics (Prof. Dr. Thomas Jaki)
Identification Number
ValueType
10.1002/pst.2181DOI
Keywordsbaclofen combination trial dose individualisation dose-finding methadone opiate detoxification
Dewey Decimal Classification000 Computer science, information & general works > 004 Computer science
StatusPublished
RefereedYes, this version has been refereed
Created at the University of RegensburgNo
URN of the UB Regensburgurn:nbn:de:bvb:355-epub-778589
Item ID77858

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