Understanding how different antipsychotic treatments affect elderly patients with schizophrenia
Official title: Robust Learning Approaches for Assessing Effects and Effect Heterogeneity of Real World Antipsychotic Treatment Regimes in Elderly Persons with Schizophrenia
Funded at Harvard Medical School · NIH-10954256 · Data updated 2026-11-12
This study looks at how well different antipsychotic medications work for older adults with schizophrenia, taking into account their backgrounds and life situations, to help find the best treatments for them.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Harvard Medical School NIH-funded |
| Lab location | 1 site (Boston, United States) |
| Project start | December 1, 2022 |
| Project end | October 31, 2027 |
| Funding year | 2025 |
| Award (this year) | $714,997 |
| NIH project number | 5R01MH130213-03 |
| Project ID | NIH-10954256 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are elderly individuals aged 65 and older who are receiving antipsychotic treatment for schizophrenia.
✕Less likely to help
Patients under the age of 65 or those not diagnosed with schizophrenia may not benefit from this research.
What this research studies
This research investigates the effectiveness of various antipsychotic medications in elderly patients with schizophrenia by analyzing large datasets from real-world treatment settings. It aims to identify which medications work best for different individuals based on factors like race, ethnicity, and social circumstances. By employing advanced statistical methods and machine learning techniques, the study seeks to provide insights into treatment patterns and their outcomes, ultimately improving care for this vulnerable population.
Why it matters
Potential benefit: If successful, this research could lead to more personalized and effective antipsychotic treatment strategies for elderly patients with schizophrenia.
How similar studies have gone: Previous research has shown promise in using machine learning to analyze treatment outcomes, suggesting that this approach could yield valuable insights.
Where this research is happening
-
Harvard Medical School
Boston, United States Active
Researchers
- Principal investigator: Normand, Sharon-Lise Teresa — Harvard Medical School
- Study coordinator: Normand, Sharon-Lise Teresa
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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.