最新的基于模型的儿童罕见病药物开发方法。

IF 3 3区 医学 Q2 PHARMACOLOGY & PHARMACY
Rajesh Krishna, Amitava Mitra, Matthew L Zierhut, Lilly East, Chandra Durairaj
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引用次数: 0

摘要

由于患者群体小,临床试验设计的伦理约束以及有限的前瞻性自然病史数据,儿科罕见病为药物开发带来了独特的挑战。模型知情药物开发(MIDD)已经成为一种强大的范例,通过利用定量方法来加强药物开发各个阶段的决策,来应对这些挑战。本文综述了应用于儿科罕见病治疗的最先进的MIDD方法,包括传统的药物计量学方法:群体药代动力学/药效学(PK/PD)建模、基于生理的药代动力学(PBPK)建模、疾病进展建模、面向未来的贝叶斯试验设计和现实世界的数据整合。我们强调这些方法如何促进剂量优化,支持从成人或其他儿科数据推断,并实现更有效和道德的临床试验策略。来自最近监管机构提交的案例研究表明,MIDD在儿科罕见疾病背景下的接受度越来越高。最后,我们讨论了推动这一领域向前发展的技术和监管进展,以及扩大MIDD对加速安全有效治疗罕见病儿童的影响的当前限制和未来机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
State-of-the-Art on Model-Informed Drug Development Approaches for Pediatric Rare Diseases.

Pediatric rare diseases present unique challenges for drug development due to small patient populations, ethical constraints on clinical trial design, and limited prospectively defined natural history data. Model-Informed Drug Development (MIDD) has emerged as a powerful paradigm to address these challenges by leveraging quantitative methods to enhance decision-making across all stages of drug development. This paper reviews the state-of-the-art MIDD approaches being applied to pediatric rare disease therapeutics, including the traditional pharmacometrics methodologies of population pharmacokinetic/pharmacodynamic (PK/PD) modeling, physiologically based pharmacokinetic (PBPK) modeling, disease progression modeling, and more future-facing Bayesian trial designs, and real-world data integration. We highlight how these methods facilitate dose optimization, support extrapolation from adult or other pediatric data, and enable more efficient and ethical clinical trial strategies. Case studies from recent regulatory submissions illustrate the growing acceptance of MIDD in pediatric rare disease contexts. Finally, we discuss the technological and regulatory advances driving this field forward, as well as current limitations and future opportunities for expanding the impact of MIDD on accelerating safe and effective treatments for children with rare diseases.

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来源期刊
CiteScore
5.00
自引率
11.40%
发文量
146
审稿时长
8 weeks
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