Ramkissoon Charrise M, Aufderheide Brian, Bequette B Wayne, Palerm Cesar C
Department of Process Engineering, University of Trinidad and Tobago, Trinidad W.I.
Department of Chemical & Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.
J Diabetes Sci Technol. 2014 May;8(3):529-42. doi: 10.1177/1932296813517323. Epub 2014 Feb 9.
Type 1 diabetes mellitus (T1DM) complications are significantly reduced when normoglycemic levels are maintained via intensive therapy. The artificial pancreas is designed for intensive glycemic control; however, large postprandial excursions after a meal result in poor glucose regulation. Pramlintide, a synthetic analog of the hormone amylin, reduces the severity of postprandial excursions by reducing appetite, suppressing glucagon release, and slowing the rate of gastric emptying. The goal of this study is to create a glucose-insulin-pramlintide physiological model that can be employed into a controller to improve current control approaches used in the artificial pancreas. A model of subcutaneous (SC) pramlintide pharmacokinetics (PK) was developed by revising an intravenous (IV) pramlintide PK model and adapting SC insulin PK from a glucose-insulin model. Gray-box modeling and least squares optimization were used to obtain parameter estimates. Pharmacodynamics (PD) were obtained by choosing parameters most applicable to pramlintide mechanisms and then testing using a proportional PD effect using least squares optimization. The model was fit and validated using 27 data sets, which included placebo, PK, and PD data. SC pramlintide PK root mean square error values range from 1.98 to 10.66 pmol/L. Pramlintide PD RMSE values range from 10.48 to 42.76 mg/dL. A new in silico model of the glucose-insulin-pramlintide regulatory system is presented. This model can be used as a platform to optimize dosing of both pramlintide and insulin as a combined therapy for glycemic regulation, and in the development of an artificial pancreas as the kernel for a model-based controller.
通过强化治疗维持正常血糖水平时,1型糖尿病(T1DM)并发症会显著减少。人工胰腺旨在实现强化血糖控制;然而,餐后较大的血糖波动会导致血糖调节不佳。普兰林肽是一种激素胰淀素的合成类似物,它通过减少食欲、抑制胰高血糖素释放和减缓胃排空速率来降低餐后血糖波动的严重程度。本研究的目的是创建一个葡萄糖 - 胰岛素 - 普兰林肽生理模型,该模型可应用于控制器,以改进人工胰腺中目前使用的控制方法。通过修改静脉注射普兰林肽的药代动力学(PK)模型并从葡萄糖 - 胰岛素模型中改编皮下胰岛素PK,建立了皮下(SC)普兰林肽PK模型。采用灰箱建模和最小二乘法优化来获得参数估计值。通过选择最适用于普兰林肽作用机制的参数,然后使用最小二乘法优化的比例PD效应进行测试,获得药效学(PD)数据。使用包括安慰剂、PK和PD数据在内的27个数据集对模型进行拟合和验证。SC普兰林肽PK均方根误差值范围为1.98至10.66 pmol/L。普兰林肽PD均方根误差值范围为10.48至42.76 mg/dL。本文提出了一种新的葡萄糖 - 胰岛素 - 普兰林肽调节系统的计算机模拟模型。该模型可作为一个平台,用于优化普兰林肽和胰岛素联合治疗血糖调节的给药方案,并用于开发人工胰腺,作为基于模型的控制器的核心。