Identification and Control of Pharmacokinetic/Physiological Systems by Closed-Loop IPFM Drug Injection

通过闭环 IPFM 药物注射识别和控制药代动力学/生理系统

• 批准号: 8705574
• 负责人: Robert Northrop
• 金额: $ 17.36万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 1987
• 资助国家: 美国
• 起止时间: 1987-09-01 至 1990-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=8705574&HistoricalAwards=false
• 关键词: Identification; Control; Pharmacokinetic; Physiological; Systems

The pharmacological treatment of disease becomes more effective when the concentration of the administered drug in the body is held constant. This action provides for the renewed support of a research project in which the discrete algorithms for the closed-loop control of in vivo drug concentration or some physiological parameter has been developed. These algorithms are based on Integral Pulse Frequency Modulation (IPFM), in which control is in the form of small, bolus injections of the drug. Accurate and rapid identification means to estimate the parameters of various controlled plants (the plant dynamics relate drug concentration or regulated physiological parameter to drug input rate) while the closed-loop system is operating will be developed. Continuous estimates of the pharmacokinetic plant's parameters will be used to tune the controller, detect side-effects of the drug, and form a data base for particular drug's behavior in the body. An improved, finer grained nonlinear model of glucose metabolism will be developed in order to adapt the nonlinear IPFM controller previously designed to run effectively with a peripheral compartment glucose sensor. Futhermore, models will be developed for the dynamics of deep pain in humans, including neurophysiological and psychological factors, and the pharmacokinetics of opioid drugs for analgesia. A non-linear, adaptive, demand-analgesia controller will be designed for safe and efficient self-administration of analgesic drugs. The Principal Investigator has been well trained both in engineering and physiology to lead this interdisciplinary research. The Institutional support is adequate, I recommend support.

药物治疗疾病变得更有效时， 所施用的药物在体内的浓度保持恒定。 这一行动为一个研究项目提供了新的支持， 其中用于体内的闭环控制的离散算法 药物浓度或某些生理参数。 这些算法基于积分脉冲频率调制 （IPFM），其中控制的形式是小剂量推注 流毒 准确、快速的识别手段，估计参数， 各种受控植物（植物动力学与药物浓度相关 或调节的生理参数到药物输入速率），而 闭环系统的运作将得到发展。 连续估计 的药代动力学工厂的参数将被用来调整 控制器，检测药物的副作用，并形成数据库 特定药物在体内的行为。 一个改进的，更细粒度的非线性模型的葡萄糖代谢将 开发，以适应非线性IPFM控制器先前 设计用于有效运行外周室葡萄糖 传感器. 未来，将开发用于深层动力学的模型。 人类的疼痛，包括神经生理和心理因素， 以及阿片类镇痛药物的药代动力学。 一个非线性的， 自适应，需求镇痛控制器将被设计为安全和 镇痛药的有效自我管理。 首席研究员在工程和 生理学来领导这项跨学科的研究。 体制 支持是足够的，我建议支持。