Quantitative Pharmacology and Pharmacometrics, Merck & Co., Inc., Boston, Massachusetts, USA.
InSysBio, Moscow, Russia.
CPT Pharmacometrics Syst Pharmacol. 2022 Nov;11(11):1399-1429. doi: 10.1002/psp4.12852. Epub 2022 Aug 17.
Age-related central neurodegenerative diseases, such as Alzheimer's and Parkinson's disease, are a rising public health concern and have been plagued by repeated drug development failures. The complex nature and poor mechanistic understanding of the etiology of neurodegenerative diseases has hindered the discovery and development of effective disease-modifying therapeutics. Quantitative systems pharmacology models of neurodegeneration diseases may be useful tools to enhance the understanding of pharmacological intervention strategies and to reduce drug attrition rates. Due to the similarities in pathophysiological mechanisms across neurodegenerative diseases, especially at the cellular and molecular levels, we envision the possibility of structural components that are conserved across models of neurodegenerative diseases. Conserved structural submodels can be viewed as building blocks that are pieced together alongside unique disease components to construct quantitative systems pharmacology (QSP) models of neurodegenerative diseases. Model parameterization would likely be different between the different types of neurodegenerative diseases as well as individual patients. Formulating our mechanistic understanding of neurodegenerative pathophysiology as a mathematical model could aid in the identification and prioritization of drug targets and combinatorial treatment strategies, evaluate the role of patient characteristics on disease progression and therapeutic response, and serve as a central repository of knowledge. Here, we provide a background on neurodegenerative diseases, highlight hallmarks of neurodegeneration, and summarize previous QSP models of neurodegenerative diseases.
与年龄相关的中枢神经退行性疾病，如阿尔茨海默病和帕金森病，是一个日益严重的公共卫生问题，并且一直受到药物开发失败的困扰。神经退行性疾病病因的复杂性和对其机制的理解不足，阻碍了有效疾病修饰疗法的发现和开发。神经退行性疾病的定量系统药理学模型可能是增强对药理干预策略的理解和降低药物淘汰率的有用工具。由于神经退行性疾病在生理病理机制上存在相似性，特别是在细胞和分子水平上，我们设想在神经退行性疾病模型中存在保守的结构成分的可能性。保守的结构子模型可以被视为构建神经退行性疾病定量系统药理学（QSP）模型的积木，与独特的疾病成分一起拼接。模型参数化在不同类型的神经退行性疾病以及个体患者之间可能有所不同。将我们对神经退行性病理生理学的机制理解形式化成为一个数学模型，可以帮助确定和优先考虑药物靶点和组合治疗策略，评估患者特征对疾病进展和治疗反应的影响，并作为知识的中心存储库。在这里，我们提供了神经退行性疾病的背景知识，强调了神经退行性变的特征，并总结了以前的神经退行性疾病的 QSP 模型。
