Understanding different types of Alzheimer's disease progression for better treatment
Data-driven Subtypes of Alzheimer's disease progression for targeted treatment
['FUNDING_R01'] · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · NIH-10977900
This study is looking at how Alzheimer's disease affects different people in unique ways to find out which groups might benefit most from specific treatments, so if you join, you could help improve understanding and options for everyone with the condition.
Quick facts
| Phase | ['FUNDING_R01'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON (nih funded) |
| Locations | 1 site (HOUSTON, UNITED STATES) |
| Trial ID | NIH-10977900 on ClinicalTrials.gov |
What this research studies
This research investigates the varying rates of progression in Alzheimer's disease (AD) patients to identify specific subtypes that may respond better to targeted treatments. By utilizing advanced machine learning techniques, the study aims to analyze a vast array of patient data, including biomarkers and clinical characteristics, to create a more personalized approach to therapy. The goal is to enhance the effectiveness of clinical trials by selecting more homogeneous patient groups, which could lead to faster development of new treatments. Patients participating in this research may contribute to a better understanding of their condition and potential treatment options.
Who could benefit from this research
Good fit: Ideal candidates for this research are individuals diagnosed with Alzheimer's disease, particularly those experiencing varying rates of cognitive decline.
Not a fit: Patients with other forms of dementia or those who do not have a diagnosis of Alzheimer's disease may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized treatments for Alzheimer's disease patients.
How similar studies have performed: Previous research has shown promise in using big data and machine learning to understand disease heterogeneity, suggesting that this approach could yield valuable insights.
Where this research is happening
HOUSTON, UNITED STATES
- UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON — HOUSTON, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: KIM, YEJIN — UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- Study coordinator: KIM, YEJIN
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 below.
Conditions: Alzheimer disease dementia, Alzheimer syndrome, Alzheimer's Disease, Alzheimer's disease patient