临床药理学
药理学
药物开发
选择(遗传算法)
医学
临床肿瘤学
内科学
肿瘤科
药品
癌症
计算机科学
人工智能
作者
Ningyuan Zhang,Yufeng Li,Wenbin Cui,Xiangqing Yu,Ying Huang
出处
期刊:Xenobiotica
[Informa]
日期:2024-08-08
卷期号:54 (7): 420-423
标识
DOI:10.1080/00498254.2024.2377577
摘要
The selection of appropriate starting dose and suitable method to predict an efficacious dose for novel oncology drug in the early clinical development stage poses significant challenges. The traditional methods of using body surface area transformation from toxicology studies to predict the first-in human (FIH) starting dose, or simply selecting the maximum tolerated dose (MTD) or maximum administered dose (MAD) as efficacious dose or recommended phase 2 dose (RP2D), are usually inadequate and risky for novel oncology drugs.Due to the regulatory efforts aimed at improving dose optimisation in oncology drug development, clinical dose selection is now shifting away from these traditional methods towards a comprehensive benefit/risk assessment-based approach. Quantitative pharmacology analysis (QPA) plays a crucial role in this new paradigm. This mini-review summarises the use of QPA in selecting the starting dose for oncology FIH studies and potential efficacious doses for expansion or phase 2 trials. QPA allows for a more rational and scientifically based approach to dose selection by integrating information across studies and development phases.In conclusion, the application of QPA in oncology drug development has the potential to significantly enhance the success rates of clinical trials and ultimately support clinical decision-making, particularly in dose selection.
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