SBIR Phase II: Hypertension Treatment Responder Prediction

SBIR 第二阶段：高血压治疗反应预测

• 批准号: 0220661
• 负责人: Albert Man
• 金额: $ 50万
• 依托单位: PREDICTION SCIENCES, LLC
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-09-15 至 2005-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0220661&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Hypertension; Treatment

This Small Business Innovation Research Phase II project will develop a clinical predictive algorithm for hypertension medication response based upon patient genetic and medical information. The development of effective treatment for hypertension is critical to controlling costs of this disease which has the largest negative impact on the U.S. economy in loss of productive years. Anti-hypertensive drugs have a large window of therapeutic options, including significant variation in dosages, medications, and combinations of therapies used. The objective of the Phase II project is to continue development of the software platform, GeneRx, which incorporates pharmacogenetics and nonlinear adaptive algorithms toward optimizing anti-hypertension therapy on a patient specific basis. Genetic data for each patient will be acquired by genotyping DNA from the blood samples, and scored as single nucleotide polymorphisms (SNPs) present or absent in key hypertension-related genes. GeneRx will take a patient's individual genetic, demographic, and environmental variables and predict lickely efficacy of a hypertension medication. In Phase I, the basic feasibility of a predictive algorithm for predicting patient response for the ACE inhibitor class of hypertension drugs was established. The Phase II project will use patient information and blood samples from both archival and ongoing hypertension studies to predict the effectiveness of other classes of hypertension medications, including calcium channel blockers, dieuretics, and beta blockers. The commercial application of this project is in the area of hypertension therapy.

该小型企业创新研究第二阶段项目将根据患者的遗传和医疗信息开发高血压药物反应的临床预测算法。开发有效的高血压治疗方法对于控制这种疾病的成本至关重要，这种疾病对美国经济的负面影响最大，损失了生产年份。抗高血压药物有很大的治疗选择窗口，包括剂量、药物和所用治疗组合的显著变化。 II期项目的目标是继续开发软件平台GeneRx，该平台结合了药物遗传学和非线性自适应算法，以根据患者的具体情况优化抗高血压治疗。将通过对血液样本中的DNA进行基因分型来获取每例患者的遗传数据，并对关键高血压相关基因中存在或不存在的单核苷酸多态性（SNP）进行评分。GeneRx将采用患者的个体遗传、人口统计学和环境变量，并预测高血压药物的疗效。在I期研究中，建立了预测患者对ACE抑制剂类高血压药物反应的预测算法的基本可行性。II期项目将使用来自存档和正在进行的高血压研究的患者信息和血液样本来预测其他类别的高血压药物的有效性，包括钙通道阻滞剂，利尿剂和β受体阻滞剂。 该项目的商业应用是在高血压治疗领域。