Predictive hemoglobin response model development for effective anemia management

肾脏疾病合并贫血的患者一般使用重组人 促红细胞生成素(RHuEPO)调节血红蛋白(Hb)水平。它已经得到了临床界的认可 不稳定的Hb水平会增加贫血患者的死亡风险。 指导rHuEPO给药的传统方法通常基于临床医生的经验和 不准确。Cybernius Medical Ltd.旨在开发一种自动决策支持系统，以实现有效 贫血管理。在这个项目中，目标是开发一个预测模型，该模型将预测 患者的血红蛋白水平对rHuEPO剂量的反应具有可接受的准确性。模型将是 利用MODEL开发贫血管理自动化决策支持系统 基于控制的技术。第一原则和数据驱动方法都将被研究来开发一个模型 这能够根据rHuEPO剂量提供准确的Hb水平预测。大量的肾脏 患有贫血的疾病患者将从这项研究中受益，降低高Hb水平的风险 可变性。这项研究还可以减少rHuEPO的使用和患者的经济负担，以及 减少临床医生花在贫血管理上的时间。

Renal disease patients with anemia are generally treated by the administration of recombinant human erythropoietin (rHuEPO) to adjust the hemoglobin (Hb) level. It has been recognized by the clinical community that an unstable Hb levels can lead to increased risk of mortality for the patients suffering from anemia. Conventional methods for guiding rHuEPO dosing are generally based on clinician's experiences and imprecise. Cybernius Medical Ltd. aims to develop an automatic decision support system to achieve effective anemia management. In this project, the objective is to develop a predictive model that would predict a patient's hemoglobin level response to rHuEPO dosing with an acceptable level of accuracy. The model will be used in future to develop an automatic decision making support system for anemia management using model based control technique. First-principle and data-driven methods will both be investigated to develop a model that is able to provide accurate Hb level predictions based on rHuEPO dosing. The large amount of renal disease patients suffering from anemia will benefit from the research with reduced risk of high Hb level variability. The research can also lead to reduced use of rHuEPO and the economic burden of patient, and reduce the clinician's time spent on anemia management.