Improving Hypertension Treatment in African Americans Using Computational Modeling and Predictive Analytics

使用计算模型和预测分析改善非裔美国人的高血压治疗

基本信息

  • 批准号:
    10268976
  • 负责人:
  • 金额:
    $ 10.11万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2020
  • 资助国家:
    美国
  • 起止时间:
    2020-09-23 至 2022-04-30
  • 项目状态:
    已结题

项目摘要

ABSTRACT As compared to whites, African Americans (AA) develop hypertension (HTN) at an earlier age, have a greater frequency and severity of HTN, poorer control of blood pressure (BP), and have twice the mortality rate from HTN. For 47 years our department has been developing computer simulations of integrative physiology for research purposes. The current model, HumMod, is comprised of 14 organ systems, and includes neural, endocrine, circulatory, and renal physiology. We have created tools that generate and analyze large cohorts of computer-generated (virtual) patients. With these techniques HumMod has been used for hypothesis generation and for understanding underlying physiological mechanisms that are not able to be determined in either whole animal or human experiments. This proposed work will use these tools and this mathematical model of human physiology to develop a realistic AA virtual population for studying antihypertensive therapies that have well-known (diuretic or salt reduction), variable (angiotensin converting enzyme, or ACE inhibition), or unclear (renal denervation (RDX), and baroreflex activation therapy (BAT) therapeutic efficacies in AA. Published data from our laboratory show that our model is robust and can realistically simulate salt sensitivity, multiple types of HTN, and device-based antihypertensive therapy. As shown in our preliminary data, we have successfully created a virtual population that was similar to the clinical data (AA population with resistant HTN) in 5-dimensions (blood pressure, heart rate, glomerular filtration rate, cardiac output, and peripheral resistance) and have conducted in silico trials for new device-based therapy currently being evaluated for the treatment of resistant HTN—namely RDX, BAT, and arteriovenous fistula. Based on these preliminary data, we hypothesize that these techniques will allow us to investigate the physiological mechanisms responsible for the variation in response to therapy in a wide range of AA patient types and predict the likelihood of success for a particular treatment. Aim 1 of the proposal will test the hypothesis that a virtual AA population with resistant HTN can be successfully calibrated and validated. Aim 2 of the proposal will test the hypothesis that in silico trials using the calibrated populations from the first Aim can be used for testing and predicting mechanisms of nonresponse to device-based antihypertensive therapies. Aim 3 will test the hypothesis that our predictive analytic techniques can be used to identify mechanisms and proxy markers of therapeutic resistance in hypertensive AA. These proposed studies have clinical relevance because they address a leading cause of morbidity and mortality as well as potential mechanisms of therapeutic resistance in an underserved and understudied minority. Furthermore, these applications and the potential insights gleaned from our physiological model and predictive analytic tools may have broad implications for BP control in other resistant hypertensive populations.
摘要 与白人相比,非洲裔美国人(AA)在较早的年龄患上高血压(HTN), HTN的发生频率和严重程度更高,血压(BP)控制较差,死亡率是对照组的两倍。 从HTN的价格。47年来,我们的部门一直在开发计算机模拟的综合 生理学研究目的。目前的模型HumMod由14个器官系统组成, 包括神经、内分泌、循环和肾生理学。我们创造了工具, 分析大量计算机生成的(虚拟)患者。有了这些技术,HumMod 用于假设生成和理解潜在的生理机制, 可以在整个动物或人体实验中确定。这项工作将利用这些 工具和这个人体生理学的数学模型来开发一个现实的AA虚拟人口, 研究已知的抗高血压疗法(利尿剂或盐减少),变量 (血管紧张素转换酶,或ACE抑制),或不清楚(肾去神经支配(RDX),和压力反射 活化疗法(BAT)治疗AA的疗效。我们实验室公布的数据显示, 该模型是鲁棒的,可以真实地模拟盐敏感性,多种类型的HTN, 抗高血压治疗正如我们的初步数据所示,我们已经成功地创建了一个虚拟的 在5维(血液)中与临床数据相似的人群(耐药HTN的AA人群) 血压、心率、肾小球滤过率、心输出量和外周阻力), 对目前正在评价的用于治疗以下疾病的新器械疗法进行了计算机模拟试验 耐药HTN-即RDX、BAT和动静脉瘘。根据这些初步数据,我们 我假设这些技术将使我们能够调查生理机制负责 对于各种AA患者类型对治疗反应的变化,并预测 成功的一种特殊的治疗。该提案的目标1将检验虚拟AA 具有耐HTN的群体可以成功地校准和验证。该提案的目标2将测试 假设使用来自第一个Aim的校准人群的计算机模拟试验可用于检验 以及预测对基于器械的抗高血压治疗无反应的机制。目标3将测试 假设我们的预测分析技术可以用来识别机制和代理 高血压AA治疗抵抗的标志物。这些拟议的研究具有临床相关性 因为它们解决了发病率和死亡率的主要原因以及 在服务不足和研究不足的少数群体中的治疗阻力。此外,这些应用程序和 从我们的生理模型和预测分析工具中收集到的潜在见解可能具有广泛的 对其他难治性高血压人群血压控制的意义。

项目成果

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John S Clemmer其他文献

John S Clemmer的其他文献

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{{ truncateString('John S Clemmer', 18)}}的其他基金

Improving Hypertension Treatment in African Americans Using Computational Modeling and Predictive Analytics
使用计算模型和预测分析改善非裔美国人的高血压治疗
  • 批准号:
    10580094
  • 财政年份:
    2020
  • 资助金额:
    $ 10.11万
  • 项目类别:

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