volume 24 issue 2 publication number e2454

A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology

Jun Zhang 1
K. Takeda 2
Masato Takeuchi 3
Kanji KOMATSU 3
Jing Zhu 1
Yusuke Yamaguchi 2
1
 
Data Science Astellas Pharma China Beijing China
2
 
Data Science Astellas Pharma Global Development, Inc. Northbrook Illinois USA
3
 
Early Development New Technologies Astellas Pharma Inc Tokyo Japan
Publication typeJournal Article
Publication date2024-11-17
scimago Q1
wos Q2
SJR1.074
CiteScore3.2
Impact factor1.4
ISSN15391604, 15391612
PubMed ID:  39551616
Abstract
ABSTRACT

The primary purpose of an oncology dose‐finding trial for novel anticancer agents has been shifting from determining the maximum tolerated dose to identifying an optimal dose (OD) that is tolerable and therapeutically beneficial for subjects in subsequent clinical trials. In 2022, the FDA Oncology Center of Excellence initiated Project Optimus to reform the paradigm of dose optimization and dose selection in oncology drug development and issued a draft guidance. The guidance suggests that dose‐finding trials include randomized dose–response cohorts of multiple doses and incorporate information on pharmacokinetics (PK) in addition to safety and efficacy data to select the OD. Furthermore, PK information could be a quick alternative to efficacy data to predict the minimum efficacious dose and decide the dose assignment. This article proposes a model‐based trial design for dose optimization with a randomization scheme based on PK outcomes in oncology. A simulation study shows that the proposed design has advantages compared to the other designs in the percentage of correct OD selection and the average number of patients assigned to OD in various realistic settings.

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Zhang J. et al. A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology // Pharmaceutical Statistics. 2024. Vol. 24. No. 2. e2454
GOST all authors (up to 50) Copy
Zhang J., Takeda K., Takeuchi M., KOMATSU K., Zhu J., Yamaguchi Y. A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology // Pharmaceutical Statistics. 2024. Vol. 24. No. 2. e2454
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TY - JOUR
DO - 10.1002/pst.2454
UR - https://onlinelibrary.wiley.com/doi/10.1002/pst.2454
TI - A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology
T2 - Pharmaceutical Statistics
AU - Zhang, Jun
AU - Takeda, K.
AU - Takeuchi, Masato
AU - KOMATSU, Kanji
AU - Zhu, Jing
AU - Yamaguchi, Yusuke
PY - 2024
DA - 2024/11/17
PB - Wiley
IS - 2
VL - 24
PMID - 39551616
SN - 1539-1604
SN - 1539-1612
ER -
BibTex
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@article{2024_Zhang,
author = {Jun Zhang and K. Takeda and Masato Takeuchi and Kanji KOMATSU and Jing Zhu and Yusuke Yamaguchi},
title = {A Model‐Based Trial Design With a Randomization Scheme Considering Pharmacokinetics Exposure for Dose Optimization in Oncology},
journal = {Pharmaceutical Statistics},
year = {2024},
volume = {24},
publisher = {Wiley},
month = {nov},
url = {https://onlinelibrary.wiley.com/doi/10.1002/pst.2454},
number = {2},
pages = {e2454},
doi = {10.1002/pst.2454}
}