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.
