临床前实验的样本量减少:贝叶斯顺序决策框架。

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Jizhou Kang, Theodoro Koulis, Tony Pourmohamad
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引用次数: 0

摘要

当动物被用于临床前实验时,可能会出现有关动物福利的伦理问题。3r原则的制定是为了指导更人道的动物研究实践。本文专门讨论了3r的减少方面。在我们提出的框架下,临床前实验是依次进行的,在实验的每个阶段,我们都会检查结果,并决定是否为了有效或无效而提前停止。与文献中通常只检查功效的传统方法相比,该方法有可能进一步减少实验所需的动物数量。所提出的设计要求在实验的每个阶段指定损失函数。这些功能可能与进行研究的实际成本直接相关,或者可以校准以反映药物将有效的先验信念。决策是基于最小化后验期望损失。我们通过模拟研究来评估设计方法,该研究涉及具有二元或连续终点的双臂实验。此外,我们还提供了取自真实临床前实验的例子。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sample size reduction in preclinical experiments: A Bayesian sequential decision-making framework.

When animals are used in a preclinical experiment, ethical concerns may arise regarding animal welfare. The 3Rs principles were developed to guide more humane animal research practices. This article specifically addresses the reduction aspect of the 3Rs. Under our proposed framework, the preclinical experiment is conducted sequentially, and at every stage of the experiment we examine the outcome and decide whether to stop early for efficacy or futility. Compared to traditional methods in the literature, which typically only check for efficacy, the proposed method has the potential to further reduce the number of animals needed in an experiment. The proposed design requires specifying loss functions at every stage of the experiment. These functions may be directly related to the actual cost of conducting the study or can be calibrated to reflect the prior belief that the drug will be effective. Decisions are made based on minimizing the posterior expected loss. We evaluate the design methodology through simulation studies that involve two-arm experiments with either binary or continuous endpoints. Additionally, we also provide examples taken from real preclinical experiments.

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来源期刊
Journal of Biopharmaceutical Statistics
Journal of Biopharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.50
自引率
18.20%
发文量
71
审稿时长
6-12 weeks
期刊介绍: The Journal of Biopharmaceutical Statistics, a rapid publication journal, discusses quality applications of statistics in biopharmaceutical research and development. Now publishing six times per year, it includes expositions of statistical methodology with immediate applicability to biopharmaceutical research in the form of full-length and short manuscripts, review articles, selected/invited conference papers, short articles, and letters to the editor. Addressing timely and provocative topics important to the biostatistical profession, the journal covers: Drug, device, and biological research and development; Drug screening and drug design; Assessment of pharmacological activity; Pharmaceutical formulation and scale-up; Preclinical safety assessment; Bioavailability, bioequivalence, and pharmacokinetics; Phase, I, II, and III clinical development including complex innovative designs; Premarket approval assessment of clinical safety; Postmarketing surveillance; Big data and artificial intelligence and applications.
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