African Americans (AA) develop hypertension (HTN) at an earlier age, have a greater frequency and severity of HTN, and have poorer control of blood pressure (BP) as compared to the white population. The mechanisms responsible for these disparities are unknown. The multifactorial nature of HTN and the similar presentation of its etiologies complicate its treatment. Mathematical modeling provides the ability to analyze complicated interrelated effects across multiple systems. Our current model, HumMod, is a large physiological simulator that is comprised of 14 organ systems, and includes key systems that play an integral role in BP control such as neural, endocrine, circulatory, and renal systems. We have created tools that integrate HumMod to generate virtual populations that are calibrated from clinical data. Thiazide (THZ) diuretics generally reduce BP and improve cardiovascular outcomes in AA. Using de‐identified clinical data from the Genetic Epidemiology Network of Atherosclerosis (GENOA) study, we calibrated virtual populations to normotensive AA or hypertensive AA with or without THZ therapy. The clinical and virtual populations were statistically similar in multiple variables including mean arterial pressure (MAP), glomerular filtration rate (GFR), left ventricular mass index (LVMI), cardiac output, and total peripheral resistance (Figure 1). Interestingly, virtual patients that did not respond to 4 weeks of THZ therapy (ΔMAP = 0±5 mmHg) were associated with greater falls in renal hemodynamics, activation of the renin‐angiotensin system, and decreased plasma atrial natriuretic peptide (ANP) as compared to THZ responders (ΔMAP = −9±3 mmHg) (Figure 2). This suggests that differences in the hormonal response to diuretic therapy may be an important factor that prevents successful HTN treatment in AA. These data are both a proof of concept of established physiology and a tool to test existing and new hypotheses of the mechanisms of nonresponse to varying antihypertensive regimens. These techniques and the potential insights gleaned from these simulations may also have broad implications for improving BP control in other hypertensive populations.Support or Funding InformationSupported by AHA 17POST33661071 and NIH PO1 HL51971This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.