Using computers to better predict and treat heart rhythm problems
Official title: A population-based computational approach for arrhythmia prediction and therapy
Funded at University of California Los Angeles · NIH-11135498 · Data updated 2026-11-12
This project uses advanced computer modeling to understand and predict dangerous heart rhythms, like those that cause sudden cardiac death, aiming to find safer and more effective treatments for patients.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of California Los Angeles NIH-funded |
| Lab location | 1 site (Los Angeles, United States) |
| Project start | July 9, 2024 |
| Project end | June 30, 2028 |
| Funding year | 2025 |
| Award (this year) | $393,750 |
| NIH project number | 5R01HL175074-02 |
| Project ID | NIH-11135498 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients with cardiac arrhythmias, particularly those at risk for sudden cardiac death or with conditions like Brugada syndrome, could potentially benefit from the future therapies developed from this research.
✕Less likely to help
Patients without cardiac arrhythmias or related cardiac conditions would not directly benefit from this specific research.
What this research studies
Sudden cardiac death is a serious concern, often caused by irregular heartbeats called ventricular arrhythmias. Current treatments, including medications and implanted devices, have limitations because they don't always work well for everyone and can sometimes even make things worse. This project aims to overcome these challenges by using powerful computer models to understand the complex causes of arrhythmias, from the molecular level to the whole heart tissue. By considering how individuals differ, this work hopes to identify better ways to predict who is at risk and develop more personalized and effective therapies.
Why it matters
Potential benefit: If successful, this work could lead to more accurate ways to predict dangerous heart rhythms and help develop new, safer, and more effective treatments for patients with conditions like Brugada syndrome and other cardiac diseases.
How similar studies have gone: Current antiarrhythmic drug therapies have shown limitations and unexpected side effects in large clinical trials, indicating a need for novel computational approaches like this one.
Where this research is happening
-
University of California Los Angeles
Los Angeles, United States Active
Researchers
- Principal investigator: Qu, Zhilin — University of California Los Angeles
- Study coordinator: Qu, Zhilin
Related research
Other NIH-funded projects on the same topics.
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Understanding how heart nerves affect dangerous heart rhythms after a heart attack
This NIH grant studies how changes in the heart’s nerve signaling after a heart attack lead to dangerous rhythm problems, with the goal of finding ways to prevent them.
-
Dexterous needle ablation for ventricular arrhythmia guided by MRI
A new MRI-guided, robot-assisted catheter delivers deeper heart tissue ablation to treat ventricular tachycardia.
-
Sex-specific heart cell signaling and rhythm problems linked to a heart failure drug target
A study from UCLA aims to understand how a key heart signaling pathway controls heart beating and rhythm differently in men and women with heart failure.
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Additive-made wearable magnetic sensors for heart monitoring with AI
A wearable system using affordable, 3D-printed sensors and machine learning to help detect heart rhythm problems in people.
-
Understanding fat deposits after heart attack and their link to dangerous heart rhythms
A Penn Medicine team is studying how fat buildup in the heart after a heart attack may influence dangerous heart rhythms and recovery.
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Developing 3D Real-Time CMR for Arrhythmia Imaging
Aims to make real-time 3D heart MRI usable for people with irregular heartbeats to improve how doctors see arrhythmias.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.