Computational Approach to Personalized Anemia Management

描述（由申请人提供）：终末期肾病（ESRD）患者的红细胞生成反应差异很大，因此有效的贫血管理是一项复杂的任务。有证据表明，在低反应患者中使用过量的促红细胞生成剂（ESA）会增加心血管并发症。除了健康风险之外，医疗保险规定的报销限制要求欧空局管理部门提高警惕。铁是影响红细胞生成反应的最重要元素之一。与血液透析治疗相关的持续失血、胃肠道出血风险增加、通路并发症以及铁吸收不良导致ESRD患者的铁消耗。标准的贫血管理方案不能完全解决促红细胞生成素和铁之间相互作用的协同性质。因此，为了达到预期的临床结果，减少患者风险暴露，提高治疗的成本效益，有必要采取个性化的策略来协调ESA和铁的剂量。我们的长期目标是生物医学计算的进步，以个性化医疗和慢性疾病的药理学管理。该项目的目标是解决多种药物给药个性化的挑战，具体应用于ESA和ESRD贫血的铁管理。中心假设是，可以开发一种计算方法来执行协调的红细胞生成刺激剂和铁的个性化剂量，以达到理想的临床结果，并最大限度地减少患者暴露，从而实现最佳护理。提出的研究背后的基本原理是，量化铁和促红细胞生成素之间相互作用的计算模型可以通过控制理论和机器学习原理应用，以获得两种药物的个性化剂量策略。主要目标将通过三个具体目标来实现：1)通过临床相关的计算模型来量化促红细胞生成素-铁相互作用；2)应用这些模型来推导协调个性化ESA和铁剂量的算法；3)通过“在硅”试验对广泛的模拟受试者和临床条件进行验证。该项目的预期结果是一种新的系统方法来管理ESRD贫血，使用多种药物，从而改善患者护理和降低成本，这将广泛适用于其他治疗领域。

DESCRIPTION (provided by applicant): Effective anemia management in End-Stage Renal Disease (ESRD) is a complex task due to large variation in erythropoietic response among the ESRD patients. Evidence shows that excessive doses of Erythropoiesis Stimulating Agents (ESA), used in hypo-responsive patients, coincide with increased cardiovascular complications. In addition to health risks, reimbursement restrictions imposed by Medicare demand additional vigilance in ESA administration. Iron is one of the most important elements affecting the erythropoietic response. The ongoing blood losses associated with hemodialysis treatments, increased risk of gastrointestinal bleeding, and access complications, as well as poor iron absorption lead to iron depletion in ESRD patients. Standard anemia management protocols do not fully address the synergistic nature of interactions between erythropoietin and iron. Personalized strategies for coordinated ESA and iron dosing are therefore necessary to achieve the desired clinical outcome, reduce patient risk exposure, and improve the cost-effectiveness of treatment. Our long-term goal is the advancement of biomedical computing to personalize medicine and pharmacologic management of chronic conditions. The objective of this project is to address the challenge of multiple drug dosing personalization with a specific application to ESA and iron management in anemia of ESRD. The central hypothesis is that a computational approach can be developed to perform coordinated personalized dosing of erythropoiesis stimulating agents and iron in order to achieve desired clinical outcomes and minimize patient exposure resulting in optimal care. The rationale behind the proposed research is that computational models quantifying the interaction between iron and erythropoietin can be applied through the principles of control theory and machine learning, to derive personalized dosing strategies for both agents. The main objective will be accomplished through three specific aims: 1) quantification of the erythropoietin-iron interaction through clinically relevant computational models, 2) application of such models to derive algorithms for coordinated personalized ESA and iron dosing, 3) validation of these algorithms through an "in sillico" trial for a wide range o simulated subjects and clinical conditions. The expected outcome of this project is a new systematic approach to the management of ESRD anemia using multiple agents resulting in improved patient care and decreased cost which will be broadly applicable to other therapeutic areas.