Project Grant R01HL184128
- This $455,825 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) was granted to Iowa State University of Science and Technology to develop a personalized digital twin technology for monitoring and understanding cardiovascular aging. The project aims to integrate data from wearable devices, echocardiographic measurements, and advanced cardiovascular modeling to enhance the monitoring and early detection of...
- This $200,000 Project Grant award from the National Science Foundation's Computer and Information Science and Engineering (CFDA 47.070) program will fund the development of advanced computational methods to create high-fidelity, fast-running digital twins of patient hearts and cardiovascular medical devices. The project aims to deliver: 1) novel machine learning algorithms for accurate digital twin geometry reconstruction from 3D medical images, 2) an efficient inverse method to identify in vivo...
- This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) provides $999,745 to Iowa State University to develop a novel multiscale digital twin framework for predicting and controlling blood vessel growth after cardiac injury. The key products and services to be delivered include: A multiscale modeling framework that integrates molecular signaling dynamics, cellular migration, sprouting patterns, and tissue-level growth and...
- This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences Program (CFDA 47.049) provides $640,562 to Duke University to develop advanced computer models that act as "virtual replicas" of a patient's blood vessels and heart activity. Using data from wearable sensors, the investigators will simulate how blood flows and interacts with vessel walls over time, enabling large-scale in silico testing of medical devices and therapies without...
- This Project Grant award from the National Science Foundation's (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences Federal Grant Program (CFDA 47.049) aims to develop a personalized digital twin technology that will enhance the monitoring and understanding of cardiovascular aging. The $250,000 award to Lehigh University will integrate data from wearable devices, echocardiographic measurements, and advanced cardiovascular modeling to create a physics-based...
- This National Science Foundation (NSF) Project Grant award under CFDA 47.041 (Engineering) supports the development of a new computational model to predict the complex interactions between ventricular assist devices (VADs) and the beating native heart. The goal is to create a "digital twin" of an experimental mock circulatory loop used for testing VAD safety and efficacy. This $195,291 award, effective August 1, 2024 through July 31, 2026, will result in a lumped parameter model that...
- This Project Grant award, valued at $1,088,500.00, was provided by the National Heart, Lung, and Blood Institute (CFDA 93.837 - Cardiovascular Diseases Research) to The University of Iowa. The award supports three independent research projects related to genetic and molecular mechanisms of heart disease. Project #1 aims to define microRNA (miR) targeting events and their biological relevance in the heart, as well as understand the clinical significance of single nucleotide polymorphisms (SNPs)...
- The National Heart Lung and Blood Institute awarded a $414,982 Project Grant under the Cardiovascular Diseases Research program (CFDA 93.837) to the University of Arkansas, Fayetteville Division, Office of Research & Sponsored Programs. The grant aims to enhance a surgical planning tool for heart valve procedures by developing a force-validated computational model of the mitral valve using experimental data from both healthy porcine and human valves. This research will improve the...
- This Project Grant award for $713,538 from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) supports research to investigate metabolic reprogramming as a novel therapeutic approach for thrombotic cardiovascular disease. The key objectives are to explore how inhibiting the cytosolic malic enzyme 1 (ME1) in platelets and leukocytes can reduce their hyperactivation and susceptibility to arterial thrombosis, while minimizing bleeding risk compared to...
- This $760,046 federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of a computationally-efficient multiscale modeling framework that integrates machine learning and artificial intelligence to predict structural and functional changes in the heart due to disease progression. The project aims to build fundamental understanding of heart disease by combining techniques from...
This Project Grant award from the National Heart, Lung, and Blood Institute (CFDA 93.837 Cardiovascular Diseases Research) provides $1,182,618 to Iowa State University of Science and Technology to develop an advanced "digital twin" technology for personalized cardiovascular care. The goal is to create a rapid, predictive modeling platform that can simulate heart valve disease progression and optimize long-term treatment interventions. The research aims to integrate scientific machine learning with computational modeling to substantially accelerate simulation speeds for cardiac biomechanics, hemodynamics, and fluid-structure interactions. This will enable real-time, patient-specific treatment planning and monitoring for heart valve diseases like mitral valve regurgitation. The award period runs from September 1, 2025 to August 31, 2029.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.2m | 8/22/25 |