Rieger Theodore R, Allen Richard J, Musante Cynthia J
Quantitative Systems Pharmacology, Early Clinical Development, Pfizer Inc, Cambridge, MA, United States.
Front Pharmacol. 2022 Jul 19;13:910789. doi: 10.3389/fphar.2022.910789. eCollection 2022.
Non-alcoholic fatty liver disease is a metabolic and inflammatory disease that afflicts many people worldwide and presently has few treatment options. To enhance the preclinical to clinical translation and the design of early clinical trials for novel therapeutics, we developed a Quantitative Systems Pharmacology model of human hepatocyte lipid metabolism. The intended application of the model is for simulating anti-steatotic therapies for reversing fatty liver. We parameterized the model using literature data from humans with both normal and elevated liver fat. We assessed that the model construct was sufficient to generate a virtual population of NAFLD patients that matched relevant statistics of a published clinical cohort, and then validated the model response to treatment by simulating pioglitazone and diet intervention in the virtual population. Finally, a sensitivity analysis was performed to determine the best points of intervention for reducing hepatic steatosis. Analysis of the model suggests the most potent method for reducing hepatic steatosis is by limiting non-esterified fatty acid flux from the adipose to the liver.
非酒精性脂肪性肝病是一种代谢性和炎症性疾病，困扰着全球许多人，目前治疗选择有限。为了加强临床前到临床的转化以及新型疗法早期临床试验的设计，我们开发了一种人类肝细胞脂质代谢的定量系统药理学模型。该模型的预期应用是模拟抗脂肪变性疗法以逆转脂肪肝。我们使用来自肝脏脂肪正常和升高的人类的文献数据对模型进行参数化。我们评估该模型构建足以生成一个与已发表临床队列的相关统计数据相匹配的非酒精性脂肪性肝病患者虚拟群体，然后通过在虚拟群体中模拟吡格列酮和饮食干预来验证模型对治疗的反应。最后，进行敏感性分析以确定减少肝脂肪变性的最佳干预点。对模型的分析表明，减少肝脂肪变性的最有效方法是限制从脂肪组织到肝脏的非酯化脂肪酸通量。
