Chakrabarty Ankush, Gregory Justin M, Moore L Merkle, Williams Philip E, Farmer Ben, Cherrington Alan D, Lord Peter, Shelton Brian, Cohen Don, Zisser Howard C, Doyle Francis J, Dassau Eyal
Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA.
Vanderbilt University Medical Center, Nashville, TN.
J Process Control. 2019 Apr;76:62-73. doi: 10.1016/j.jprocont.2019.01.002. Epub 2019 Feb 23.
Current artificial pancreas systems (AP) operate via subcutaneous (SC) glucose sensing and SC insulin delivery. Due to slow diffusion and transport dynamics across the interstitial space, even the most sophisticated control algorithms in on-body AP systems cannot react fast enough to maintain tight glycemic control under the effect of exogenous glucose disturbances caused by ingesting meals or performing physical activity. Recent efforts made towards the development of an implantable AP have explored the utility of insulin infusion in the intraperitoneal (IP) space: a region within the abdominal cavity where the insulin-glucose kinetics are observed to be much more rapid than the SC space. In this paper, a series of canine experiments are used to determine the dynamic association between IP insulin boluses and plasma glucose levels. Data from these experiments are employed to construct a new mathematical model and to formulate a closed-loop control strategy to be deployed on an implantable AP. The potential of the proposed controller is demonstrated via experiments on an FDA-accepted benchmark cohort: the proposed design significantly outperforms a previous controller designed using artificial data (time in clinically acceptable glucose range: 97.3±1.5% vs. 90.1±5.6%). Furthermore, the robustness of the proposed closed-loop system to delays and noise in the measurement signal (for example, when glucose is sensed subcutaneously) and deleterious glycemic changes (such as sudden glucose decline due to physical activity) is investigated. The proposed model based on experimental canine data leads to the generation of more effective control algorithms and is a promising step towards fully automated and implantable artificial pancreas systems.
当前的人工胰腺系统（AP）通过皮下（SC）葡萄糖传感和皮下胰岛素输注来运行。由于跨组织间隙的扩散和传输动力学缓慢，即使是体内AP系统中最复杂的控制算法，在因进食或进行体育活动引起的外源性葡萄糖干扰影响下，也无法快速做出反应以维持严格的血糖控制。最近在可植入AP开发方面所做的努力探索了在腹腔内（IP）空间进行胰岛素输注的效用：腹腔内的一个区域，在该区域观察到胰岛素 - 葡萄糖动力学比皮下空间快得多。在本文中，通过一系列犬类实验来确定腹腔内胰岛素推注与血浆葡萄糖水平之间的动态关联。这些实验的数据被用于构建一个新的数学模型，并制定一种闭环控制策略，以部署在可植入的AP上。通过在一个美国食品药品监督管理局（FDA）认可的基准队列上进行实验，证明了所提出控制器的潜力：所提出的设计显著优于使用人工数据设计的先前控制器（临床可接受葡萄糖范围内的时间：97.3±1.5%对90.1±5.6%）。此外，还研究了所提出的闭环系统对测量信号中的延迟和噪声（例如，当皮下传感葡萄糖时）以及有害血糖变化（如因体育活动导致的突然血糖下降）的鲁棒性。基于犬类实验数据提出的模型导致生成更有效的控制算法，是朝着全自动和可植入人工胰腺系统迈出的有希望的一步。
