# 3-Dimensional virtual ventricles to design precision therapies in hypertrophic cardiomyopathy > **NIH NIH K08** · WASHINGTON UNIVERSITY · 2021 · $143,030 ## Abstract Project Abstract Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac disease worldwide and is the leading cause of sudden cardiac death (SCD) in young people. Though HCM is characterized by more than 1400 mutations in the genes encoding the contractile apparatus of the cell, the pathophysiology of HCM encompasses diverse clinical symptoms; it can eventually lead to heart failure and fatal ventricular arrhythmia. Despite nearly 5 decades of research, there is currently no disease-modifying or mortality-reducing drug therapy for HCM patients. HCM treatment has failed for two key reasons: (1) arrhythmias are an emergent phenomena in space and time: single cell markers of arrhythmia fail to predict the effects on the whole heart; and (2) HCM is markedly heterogeneous - it is likely there are specific molecular underpinnings leading to differential drug efficacy that are not appreciated in large clinical trials and preclude a “one-size-fits-all” approach. I hypothesize that the key to understanding the therapeutic potential of drug therapy for HCM is through patient-specific modeling of their cardiac electrophysiology and ventricular ultrastructure. Thus, the goal of this research award is to merge clinical data, genetics, advanced imaging, and biophysical characterization of HCM to understand how higher dimensional ultrastructural remodeling influences cellular electrophysiology to design precision-targeted drug therapy. Specifically, I will develop a detailed electrophysiologic model of HCM that recapitulates mutation-specific alterations to better understand key determinants of success and failure for drug therapy. I will study patient-specific responses to two test drugs: ranolazine and b-blockers by optical imaging of dissociated adult cardiomyocytes of patients with HCM. I will then use multimodal imaging to characterize ventricular geometry and myofiber architecture of these patients to create a 3D virtual ventricle to test our single cell drug predictions. These aims will allow us me understand the bidirectional relationship between ventricular remodeling and single cell electrophysiology and drug therapy. I believe I have the appropriate background and resources to address the knowledge gaps described but require additional mentorship and training to transition to independence. I previously earned a PhD in computational cardiology and have undertaken additional training in basic and translational cardiovascular research. I have completed clinical training in Internal Medicine, Cardiology, Echocardiography, and Advanced Heart Failure and Cardiac Transplant, and have been appointed Instructor of Medicine as of July 1, 2020. To transition to an independent investigator, this K08 award will allow me to focus on developing new experimental skillsets in cellular electrophysiology, optical imaging techniques, as well as cardiac MRI and echo imaging that will compliment his computational background. At the conclusion of this awa... ## Key facts - **NIH application ID:** 10215670 - **Project number:** 1K08HL153794-01A1 - **Recipient organization:** WASHINGTON UNIVERSITY - **Principal Investigator:** JONATHAN MORENO - **Activity code:** K08 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $143,030 - **Award type:** 1 - **Project period:** 2021-04-01 → 2026-03-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10215670 ## Citation > US National Institutes of Health, RePORTER application 10215670, 3-Dimensional virtual ventricles to design precision therapies in hypertrophic cardiomyopathy (1K08HL153794-01A1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10215670. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*