Use of Real-World Data and Real-World Evidence in Rare Disease Drug Development: A Statistical Perspective

IF 5.5 2区 医学 Q1 PHARMACOLOGY & PHARMACY Clinical Pharmacology & Therapeutics Pub Date : 2025-02-14 DOI:10.1002/cpt.3576
Jie Chen, Susan Gruber, Hana Lee, Haitao Chu, Shiowjen Lee, Haijun Tian, Yan Wang, Weili He, Thomas Jemielita, Yang Song, Roy Tamura, Lu Tian, Yihua Zhao, Yong Chen, Mark van der Laan, Lei Nie
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Abstract

Real-world data (RWD) and real-world evidence (RWE) have been increasingly used in medical product development and regulatory decision-making, especially for rare diseases. After outlining the challenges and possible strategies to address the challenges in rare disease drug development (see the accompanying paper), the Real-World Evidence (RWE) Scientific Working Group of the American Statistical Association Biopharmaceutical Section reviews the roles of RWD and RWE in clinical trials for drugs treating rare diseases. This paper summarizes relevant guidance documents and frameworks by selected regulatory agencies and the current practice on the use of RWD and RWE in natural history studies and the design, conduct, and analysis of rare disease clinical trials. A targeted learning roadmap for rare disease trials is described, followed by case studies on the use of RWD and RWE to support a natural history study and marketing applications in various settings.

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使用真实世界的数据和真实世界的证据在罕见病药物开发:一个统计的角度。
真实世界数据(RWD)和真实世界证据(RWE)越来越多地用于医疗产品开发和监管决策,特别是罕见疾病。在概述了罕见病药物开发面临的挑战和应对挑战的可能策略(见随文)之后,美国统计协会生物制药部门的真实世界证据(RWE)科学工作组审查了RWD和RWE在罕见病药物临床试验中的作用。本文总结了部分监管机构的相关指导文件和框架,以及RWD和RWE在博物学研究和罕见病临床试验设计、实施和分析中的应用现状。介绍了罕见病试验的目标学习路线图,然后介绍了利用RWD和RWE支持自然历史研究和在各种情况下的营销应用的案例研究。
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来源期刊
CiteScore
12.70
自引率
7.50%
发文量
290
审稿时长
2 months
期刊介绍: Clinical Pharmacology & Therapeutics (CPT) is the authoritative cross-disciplinary journal in experimental and clinical medicine devoted to publishing advances in the nature, action, efficacy, and evaluation of therapeutics. CPT welcomes original Articles in the emerging areas of translational, predictive and personalized medicine; new therapeutic modalities including gene and cell therapies; pharmacogenomics, proteomics and metabolomics; bioinformation and applied systems biology complementing areas of pharmacokinetics and pharmacodynamics, human investigation and clinical trials, pharmacovigilence, pharmacoepidemiology, pharmacometrics, and population pharmacology.
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