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首页> 外文期刊>Journal of Mathematical Biology >Optimal EPO dosing in hemodialysis patients using a non-linear model predictive control approach
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Optimal EPO dosing in hemodialysis patients using a non-linear model predictive control approach

机译:利用非线性模型预测控制方法在血液透析患者中定量素定量的最佳EPO

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Anemia management with erythropoiesis stimulating agents is a challenging task in hemodialysis patients since their response to treatment varies highly. In general, it is difficult to achieve and maintain the predefined hemoglobin (Hgb) target levels in clinical practice. The aim of this study is to develop a fully personalizable controller scheme to stabilize Hgb levels within a narrow target window while keeping drug doses low to mitigate side effects. First in-silico results of this framework are presented in this paper. Based on a model of erythropoiesis we formulate a non-linear model predictive control (NMPC) algorithm for the individualized optimization of epoetin alfa (EPO) doses. Previous to this work, model parameters were estimated for individual patients using clinical data. The optimal control problem is formulated for a continuous drug administration. This is currently a hypothetical form of drug administration for EPO as it would require a programmable EPO pump similar to insulin pumps used to treat patients with diabetes mellitus. In each step of the NMPC method the open-loop problem is solved with a projected quasi-Newton method. The controller is successfully tested in-silico on several patient parameter sets. An appropriate control is feasible in the tested patients under the assumption that the controlled quantity is measured regularly and that continuous EPO administration is adjusted on a daily, weekly or monthly basis. Further, the controller satisfactorily handles the following challenging problems in simulations: bleedings, missed administrations and dosing errors.
机译:由于血液透析患者的血症患者血症管理是一种挑战性的任务,因为他们对治疗的反应很高。通常,难以在临床实践中实现和维持预定义的血红蛋白(HGB)目标水平。本研究的目的是开发一种完全可组织的控制器方案,以稳定窄目标窗口内的HGB水平,同时保持药物剂量低以减轻副作用。本文提出了本框架的首先硅基结果。基于红绿腺植物的模型,我们制定了用于Epoetin Alfa(EPO)剂量的个性化优化的非线性模型预测控制(NMPC)算法。在此工作之前,使用临床数据的个体患者估计模型参数。用于连续药物施用的最佳控制问题。这是目前对EPO的药物管理局的假设形式,因为它需要类似于用于治疗糖尿病患者的胰岛素泵的可编程EPO泵。在NMPC方法的每个步骤中,通过投影的准牛顿方法解决了开环问题。控制器在几个患者参数集上成功测试了Silico。在假设定期测量的受控量并且连续EPO给药时,在经常测量的患者下,在测试的患者中是可行的,并且每天,每周或每月调整连续的EPO给药。此外,控制器在模拟中令人满意地处理以下具有挑战性的问题:出血,错过主管部门和给药错误。

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