Kansal Anuraag R, Tafazzoli Ali, Ishak K Jack, Krotneva Stanmira
Modeling and Simulation, Evidera, Bethesda, MD, USA.
Modeling and Simulation, Evidera, St-Laurent, Quebec, Canada.
Alzheimers Dement (N Y). 2018 Feb 16;4:76-88. doi: 10.1016/j.trci.2018.01.001. eCollection 2018.
Several advances have been made in Alzheimer's Disease (AD) modeling, however, there remains a need for a simulator that represents the full scope of disease progression and can be used to study new disease-modifying treatments for early-stage and even prodromal AD.
We developed AD Archimedes condition-event simulator, a patient-level simulator with a focus on simulating the effects of early interventions through changes in biomarkers of AD. The simulator incorporates interconnected predictive equations derived from longitudinal data sets.
The results of external validations on AD Archimedes condition-event simulator showed that it provides reasonable estimates once compared to literature results on transition to dementia AD, institutionalization, and mortality. A case study comparing a disease-modifying treatment and a symptomatic treatment also showcases the benefits of early treatment.
The AD Archimedes condition-event simulator is designed to perform economic evaluation on various interventions through close tracking of disease progression and the related clinical outcomes.
阿尔茨海默病（AD）建模已取得多项进展，然而，仍需要一种模拟器，能够呈现疾病进展的全貌，并可用于研究针对早期甚至前驱期AD的新型疾病修饰疗法。
我们开发了AD阿基米德条件-事件模拟器，这是一种患者水平的模拟器，重点通过AD生物标志物的变化来模拟早期干预的效果。该模拟器纳入了从纵向数据集中推导出来的相互关联的预测方程。
对AD阿基米德条件-事件模拟器的外部验证结果表明，与关于向痴呆性AD转变、入住机构和死亡率的文献结果相比，它能提供合理的估计。一项比较疾病修饰疗法和对症治疗的案例研究也展示了早期治疗的益处。
AD阿基米德条件-事件模拟器旨在通过密切跟踪疾病进展和相关临床结果，对各种干预措施进行经济评估。
