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Research Article


DESIGN STRATEGY AND CONSIDERATION FOR ONCOLOGY DOSE-OPTIMIZATION: AN INDUSTRY
PERSPECTIVE

Rong Liua Regeneron Pharmaceuticals, New York,
NYCorrespondencerong.liu@regeneron.com
View further author information
,
Ying Yuanb The University of Texas MD Anderson Cancer Center, Houston,
TXhttps://orcid.org/0000-0003-3163-480XView further author information
,
Suman Senc Novartis Pharmaceuticals Corp, East Hanover, NJView further author
information
,
Olga Marchenkod Bayer, Whippany, NJView further author information
,
Qi Jiange Seagen Biotechnology Research, Bothell, WAView further author
information
,
Hong Tianf BeiGene, Emeryville, CAView further author information
,
Xiaoyun Lif BeiGene, Emeryville, CAView further author information
,
Ruitao Linb The University of Texas MD Anderson Cancer Center, Houston, TXView
further author information
,
Cindy Lug AstraZeneca Plc, Wilmington, DEView further author information
&
Heng Zhouh Merck & Co, Rahway, NJView further author information
show all
Received 01 Feb 2023, Accepted 06 Mar 2024, Published online: 14 May 2024
 * Cite this article
 * https://doi.org/10.1080/19466315.2024.2332650
 * CrossMark


 

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ABSTRACT

The conventional more-is-better dose selection paradigm is often inappropriate
for novel molecularly targeted agents. In response, the US Food and Drug
Administration (FDA) initiated Project Optimus to reform the dose optimization
and dose selection paradigm in oncology drug development. Furthermore, the FDA
recently also published draft guidance “Optimizing the dosage of human
prescription drugs and biological products for the treatment of oncologic
diseases guidance for industry,” providing overviews on the rationale,
importance, and principles of dose optimization from the regulatory perspective.
However, detailed guidance on how to design dose optimization trials is still
lacking; it is a key issue faced by drug developers. The article discusses
statistical and design strategies of dose optimization in oncology by sharing
current industry practice on dose-finding, delineating key statistical
components for dose optimization trials, describing available design strategies,
and providing recommendations and future directions. This article is a joint
work of the Statistical Methods in Oncology Scientific Working Group
(Dose-Optimization Workstream) of the American Statistical Association
Biopharmaceutical Section.

KEYWORDS:

 * Industry perspective
 * Oncology
 * Project optimus




SUPPLEMENTARY MATERIALS

Appendix 1: List of software commonly used in the context of dose optimization.


DISCLOSURE STATEMENT

No potential conflict of interest was reported by the author(s).


ADDITIONAL INFORMATION


FUNDING

The author(s) reported there is no funding associated with the work featured in
this article.





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