Lingineni Karthik, Aggarwal Varun, Morales Juan Francisco, Conrado Daniela J, Corey Diane, Vong Camille, Burton Jackson, Larkindale Jane, Romero Klaus, Schmidt Stephan, Kim Sarah
Department of Pharmaceutics, Center for Pharmacometrics and Systems Pharmacology, College of Pharmacy, University of Florida, Orlando, Florida, USA.
Critical Path Institute, Tucson, Arizona, USA.
CPT Pharmacometrics Syst Pharmacol. 2022 Mar;11(3):318-332. doi: 10.1002/psp4.12753. Epub 2022 Jan 3.
Early clinical trials of therapies to treat Duchenne muscular dystrophy (DMD), a fatal genetic X-linked pediatric disease, have been designed based on the limited understanding of natural disease progression and variability in clinical measures over different stages of the continuum of the disease. The objective was to inform the design of DMD clinical trials by developing a disease progression model-based clinical trial simulation (CTS) platform based on measures commonly used in DMD trials. Data were integrated from past studies through the Duchenne Regulatory Science Consortium founded by the Critical Path Institute (15 clinical trials and studies, 1505 subjects, 27,252 observations). Using a nonlinear mixed-effects modeling approach, longitudinal dynamics of five measures were modeled (NorthStar Ambulatory Assessment, forced vital capacity, and the velocities of the following three timed functional tests: time to stand from supine, time to climb 4 stairs, and 10 meter walk-run time). The models were validated on external data sets and captured longitudinal changes in the five measures well, including both early disease when function improves as a result of growth and development and the decline in function in later stages. The models can be used in the CTS platform to perform trial simulations to optimize the selection of inclusion/exclusion criteria, selection of measures, and other trial parameters. The data sets and models have been reviewed by the US Food and Drug Administration and the European Medicines Agency; have been accepted into the Fit-for-Purpose and Qualification for Novel Methodologies pathways, respectively; and will be submitted for potential endorsement by both agencies.
杜氏肌营养不良症（DMD）是一种致命的X连锁儿科遗传病，针对其治疗方法的早期临床试验，是基于对疾病自然进展以及疾病连续统一体不同阶段临床指标变异性的有限理解而设计的。其目的是通过基于DMD试验常用指标开发一个基于疾病进展模型的临床试验模拟（CTS）平台，为DMD临床试验的设计提供信息。数据通过关键路径研究所成立的杜氏监管科学联盟，从过去的研究中整合而来（15项临床试验和研究，1505名受试者，27252条观测数据）。采用非线性混合效应建模方法，对五项指标的纵向动态进行建模（北极星动态评估、用力肺活量，以及以下三项定时功能测试的速度：从仰卧位站立的时间、爬4级楼梯的时间和10米步行-跑步时间）。这些模型在外部数据集上得到了验证，能够很好地捕捉这五项指标的纵向变化，包括因生长发育导致功能改善的疾病早期阶段以及后期功能的下降。这些模型可用于CTS平台进行试验模拟，以优化纳入/排除标准的选择、指标的选择以及其他试验参数。这些数据集和模型已经得到美国食品药品监督管理局和欧洲药品管理局的审查；分别被纳入“适用目的”和“新方法鉴定”途径；并将提交给这两个机构进行潜在认可。
