Improving Heart Transplant Decisions with Artificial Intelligence
Official title: Developing Machine Learning Models for Decision Support and Allocation Optimization in Heart Transplantation
Funded at Medical University of South Carolina · NIH-11092289 · Data updated 2026-11-12
This research aims to create a smart computer program to help doctors make better decisions about matching donor hearts with patients who need them.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Medical University of South Carolina NIH-funded |
| Lab location | 1 site (Charleston, United States) |
| Project start | September 4, 2023 |
| Project end | March 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $648,772 |
| NIH project number | 5R01HL162882-03 |
| Project ID | NIH-11092289 on NIH RePORTER |
Who could benefit from this research
✓Could help
This research is for adult patients who are candidates for heart transplantation or those who have received a heart transplant, as it aims to improve the process for them.
✕Less likely to help
Patients not in need of a heart transplant or those with conditions unrelated to cardiac transplantation would not directly benefit from this specific research.
What this research studies
Many people need heart transplants, but there aren't enough donor hearts, and some available hearts are not used. Doctors currently rely on their experience to decide which donor heart is best for which patient, which can lead to varying outcomes. This project will build an advanced artificial intelligence tool that can quickly analyze many factors about both donor hearts and recipients. The goal is to provide doctors with data-driven insights to improve the success rate of heart transplants and ensure more donor hearts are used effectively.
Why it matters
Potential benefit: If successful, this tool could lead to more successful heart transplants, fewer wasted donor hearts, and better outcomes for patients needing a new heart.
How similar studies have gone: Existing risk models have had limited success and widespread use, indicating that this new, more advanced approach is novel and seeks to overcome prior limitations.
Where this research is happening
-
Medical University of South Carolina
Charleston, United States Active
Researchers
- Principal investigator: Kilic, Arman — Medical University of South Carolina
- Study coordinator: Kilic, Arman
Related research
Other NIH-funded projects on the same topics.
-
Targeted immune treatments to protect donated hearts
This project develops ways to send immune-suppressing medicines directly to the lymph nodes and the transplanted heart to help people with heart transplants avoid rejection while reducing side effects.
-
IL-33 helps protect heart transplant patients from long-term rejection
This grant studies how a natural molecule called IL-33 may shield heart transplant patients from ongoing immune damage and chronic rejection.
-
Targeted mRNA delivery to improve heart transplants from donation after circulatory death
This grant tests a new mRNA delivery approach to help donor hearts from donors after circulatory death survive and function better after transplant.
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Belatacept to reduce rejection and protect kidneys after a heart transplant
This trial will compare continuing tacrolimus to gradually switching to belatacept over nine months in people receiving a first-time heart transplant to lower rejection, prevent donor-specific antibodies, and protect kidney function.
-
Partial heart transplant to give growing heart valves to children
This work tries transplanting only the donor heart part that contains a valve so children can get a valve that grows with them.
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Predicting Heart Transplant Rejection Risk Before Surgery
This research aims to find ways to predict which heart transplant patients might reject their new heart, helping doctors tailor their medication plans.
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.