Kaddi Chanchala, Tao Mengdi, Bergeler Silke, George Kelly, Geerts Hugo, van der Graaf Piet H, Batista Julie L, Foster Meredith, Ortemann-Renon Catherine, Zaher Atef, An Haack Kristina, Zaph Susana
Translational Disease Modeling, Translational Medicine and Early Development, Sanofi, Cambridge, Massachusetts, USA.
Translational Disease Modeling, Translational Medicine and Early Development, Sanofi, Bridgewater, New Jersey, USA.
Clin Pharmacol Ther. 2025 Feb;117(2):579-588. doi: 10.1002/cpt.3498. Epub 2024 Dec 4.
Pompe disease is a rare, progressive neuromuscular disease caused by deficient lysosomal glycogen degradation, and includes both late-onset (LOPD) and severe infantile-onset (IOPD) phenotypes. Due to very small patient numbers in IOPD and the high phenotypic heterogeneity observed in this population, a quantitative systems pharmacology (QSP)-based "digital twin" approach was developed to perform an in silico comparison of the efficacy of avalglucosidase alfa vs. the standard of care, in a virtual population of IOPD patients. A QSP model was developed that represents key elements of Pompe disease pathophysiology, including tissue glycogen accumulation and the elevation of the biomarker urine Hex4 in both LOPD and IOPD patients. In this approach, the QSP model was used to generate digital twins of each IOPD patient enrolled in the avalglucosidase alfa clinical program, considering their respective disease burden, demographics, and treatment history. This virtual cohort supplemented clinical observations by simulating and comparing tissue glycogen and urine Hex4 following avalglucosidase alfa treatment vs. the standard of care. The digital twin analysis supports the interpretation that the enhanced reduction in urine Hex4 observed following avalglucosidase alfa treatment is attributable to greater tissue glycogen clearance. Overall, this study provides mechanism-based insight into avalglucosidase alfa efficacy across the phenotypic spectrum of Pompe disease and demonstrates the value of applying a QSP-based digital twin analysis to support rare disease drug development.
庞贝病是一种罕见的进行性神经肌肉疾病,由溶酶体糖原降解缺陷引起,包括晚发型(LOPD)和严重婴儿型(IOPD)表型。由于IOPD患者数量极少且该人群存在高度表型异质性,因此开发了一种基于定量系统药理学(QSP)的“数字孪生”方法,以在虚拟的IOPD患者群体中对阿伐糖苷酶α与标准治疗的疗效进行计算机模拟比较。开发了一个QSP模型,该模型代表了庞贝病病理生理学的关键要素,包括LOPD和IOPD患者的组织糖原积累以及生物标志物尿Hex4的升高。在这种方法中,QSP模型用于为参与阿伐糖苷酶α临床项目的每位IOPD患者生成数字孪生,同时考虑他们各自的疾病负担、人口统计学特征和治疗史。这个虚拟队列通过模拟和比较阿伐糖苷酶α治疗与标准治疗后的组织糖原和尿Hex4,补充了临床观察结果。数字孪生分析支持了这样的解释,即阿伐糖苷酶α治疗后观察到的尿Hex4的更大幅度降低归因于更大程度的组织糖原清除。总体而言,本研究为庞贝病整个表型谱中阿伐糖苷酶α的疗效提供了基于机制的见解,并证明了应用基于QSP的数字孪生分析来支持罕见病药物开发的价值。