On the use of RWD in support of regulatory submission in drug development.

IF 1.2 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Shein-Chung Chow, Peijin Wang
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引用次数: 0

Abstract

For the approval of a drug product, the United States Food and Drug Administration requires substantial evidence (SE) regarding effectiveness and safety of the test drug to be provided. In recent years, the use of real-world data in support of regulatory submission of pharmaceutical development has received much attention, and real-world evidence (RWE) is treated as complementary to SE by evaluating the real-world performance of the test treatment. In this article, we start by summarizing current regulatory perspectives on drug evaluation and some potential challenges in using RWE. To test for superiority in co-primary endpoints, a two-stage hybrid RCT/RWS adaptive design that combines randomized control trial for providing SE and real-world study for generating RWE is proposed. We use superiority in effectiveness and non-inferiority in safety as an example to illustrate how to implement this design. Numerical studies have shown that the proposed design has merits in reducing the required sample size compared with traditional co-primary endpoint tests while maintaining statistical power and controlling type I error inflation. The proposed design can be implemented in drug development considering co-primary endpoints, especially for oncology and rare disease drug development.

使用 RWD 支持药物开发的监管申请。
美国食品和药物管理局在审批药品时,要求提供有关试验药物有效性和安全性的实质性证据(SE)。近年来,使用真实世界数据来支持药品开发的监管申请受到了广泛关注,真实世界证据(RWE)通过评估试验疗法在真实世界中的表现,被视为实质性证据(SE)的补充。在本文中,我们首先总结了当前监管部门对药物评价的看法,以及使用 RWE 可能面临的一些挑战。为了测试共同主要终点的优越性,我们提出了一种两阶段混合 RCT/RWS 适应性设计,它将提供 SE 的随机对照试验与产生 RWE 的真实世界研究相结合。我们以有效性优和安全性非劣为例,说明如何实施这种设计。数值研究表明,与传统的共同主要终点测试相比,建议的设计在减少所需样本量方面具有优势,同时还能保持统计功率和控制 I 型误差膨胀。建议的设计可以在考虑共主要终点的药物开发中实施,尤其是在肿瘤和罕见病药物开发中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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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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