TY - JOUR
T1 - Dose Optimization for Novel Oncology Agents
T2 - Design Options and Strategies
AU - Dejardin, David
AU - Huang, Bo
AU - Yuan, Ying
AU - Beyer, Ulrich
AU - Fridlyand, Jane
AU - Zhu, Jiawen
N1 - Publisher Copyright:
© 2024 American Statistical Association.
PY - 2024
Y1 - 2024
N2 - Over the past decade, drug development in oncology has shifted from cytotoxic agents to drugs with new mechanisms of action, such as cancer immunotherapies, targeted therapeutics, T-cell engagers and others. The conventional maximum tolerated dose (MTD) based dose-finding paradigm is not suitable for the development of these new agents. Further, health authorities, especially the FDA, are requesting more thorough dose optimization prior to the initiation of pivotal trials, and initiatives such as the FDA’s project Optimus have been launched to accelerate this paradigm shift. Dose optimization is more complicated than finding the MTD and requires consideration of complex mechanisms of action, schedule optimization, long-term drug tolerability, and possibly novel pharmacodynamic endpoints. Thus, thoughtful study designs, translational data, and statistical modeling play an increasingly important role to achieve the goal of dose optimization. This article captures opinions from the 2022 ASA biophamaceutical section regulatory-industry statistics workshop session “Dose finding and optimization for novel oncology agents—the new challenges and novel technologies.” We present general design options for dose optimization. Pros and cons of these design options are discussed, and a real-world case study is provided to illustrate a strategy of dose optimization. Discussions focused on practical considerations are included.
AB - Over the past decade, drug development in oncology has shifted from cytotoxic agents to drugs with new mechanisms of action, such as cancer immunotherapies, targeted therapeutics, T-cell engagers and others. The conventional maximum tolerated dose (MTD) based dose-finding paradigm is not suitable for the development of these new agents. Further, health authorities, especially the FDA, are requesting more thorough dose optimization prior to the initiation of pivotal trials, and initiatives such as the FDA’s project Optimus have been launched to accelerate this paradigm shift. Dose optimization is more complicated than finding the MTD and requires consideration of complex mechanisms of action, schedule optimization, long-term drug tolerability, and possibly novel pharmacodynamic endpoints. Thus, thoughtful study designs, translational data, and statistical modeling play an increasingly important role to achieve the goal of dose optimization. This article captures opinions from the 2022 ASA biophamaceutical section regulatory-industry statistics workshop session “Dose finding and optimization for novel oncology agents—the new challenges and novel technologies.” We present general design options for dose optimization. Pros and cons of these design options are discussed, and a real-world case study is provided to illustrate a strategy of dose optimization. Discussions focused on practical considerations are included.
KW - Dose optimization
KW - Oncology
KW - Project optimus
KW - Study design
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U2 - 10.1080/19466315.2024.2308856
DO - 10.1080/19466315.2024.2308856
M3 - Article
AN - SCOPUS:85186631392
SN - 1946-6315
JO - Statistics in Biopharmaceutical Research
JF - Statistics in Biopharmaceutical Research
ER -