Literature DB >> 32183578

Design optimization for dose-finding trials: a review.

Jihane Aouni1,2, Jean Noel Bacro2, Gwladys Toulemonde2,3, Pierre Colin1, Loic Darchy1, Bernard Sebastien1.   

Abstract

Dose selection is one of the most difficult and crucial decisions to make during drug development. As a consequence, the dose-finding trial is a major milestone in the drug development plan and should be properly designed. This article will review the most recent methodologies for optimizing the design of dose-finding studies: all of them are based on the modeling of the dose-response curve, which is now the gold standard approach for analyzing dose-finding studies instead of the traditional ANOVA/multiple testing approach. We will address the optimization of both fixed and adaptive designs and briefly outline new methodologies currently under investigation, based on utility functions.

Keywords:  Adaptive trials; design optimization; dose selection; patient allocation; utility functions

Mesh:

Year:  2020        PMID: 32183578     DOI: 10.1080/10543406.2020.1730874

Source DB:  PubMed          Journal:  J Biopharm Stat        ISSN: 1054-3406            Impact factor:   1.051


  1 in total

1.  Optimal adaptive allocation using deep reinforcement learning in a dose-response study.

Authors:  Kentaro Matsuura; Junya Honda; Imad El Hanafi; Takashi Sozu; Kentaro Sakamaki
Journal:  Stat Med       Date:  2021-11-07       Impact factor: 2.497

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.