Developing new drugs to fight malaria using machine learning
Official title: Novel Dual-Stage Antimalarials: Machine learning prediction, validation and evolution
Funded at Rutgers Biomedical and Health Sciences · NIH-10878908 · Data updated 2026-11-12
This study is working on developing new medicines to fight malaria by targeting the infection in both the blood and liver, using smart computer technology to find the best options, so that patients can have better treatments, especially as current drugs are becoming less effective.
Quick facts
| Grant type | R21 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Rutgers Biomedical and Health Sciences NIH-funded |
| Lab location | 1 site (Newark, UNITED STATES) |
| Project start | July 3, 2023 |
| Project end | December 31, 2025 |
| Funding year | 2024 |
| Award (this year) | $194,915 |
| NIH project number | 5R21AI174151-02 |
| Project ID | NIH-10878908 on NIH RePORTER |
Who could benefit from this research
✓Could help
Ideal candidates for this research are individuals at risk of malaria infection, particularly in regions where drug-resistant strains are prevalent.
✕Less likely to help
Patients who are not at risk of malaria or those who have already been effectively treated with existing antimalarial medications may not benefit from this research.
What this research studies
This research focuses on creating new small molecules that can effectively target both the blood and liver stages of malaria infection caused by the Plasmodium parasite. By utilizing machine learning models, the project aims to predict and validate these novel antimalarial compounds, which have shown promise in preliminary tests for their effectiveness and safety. The goal is to provide new treatment options for malaria, especially in cases where existing drugs are becoming less effective due to resistance. Patients may benefit from these advancements through improved treatment outcomes and reduced mortality rates associated with malaria.
Why it matters
Potential benefit: If successful, this research could lead to the development of more effective antimalarial drugs that can save lives and improve health outcomes for those infected.
How similar studies have gone: Previous research has shown promise in using machine learning for drug discovery, indicating that this approach could yield significant advancements in antimalarial treatments.
Where this research is happening
-
Rutgers Biomedical and Health Sciences
Newark, United States Active
Researchers
- Principal investigator: Freundlich, Joel Stephen — Rutgers Biomedical and Health Sciences
- Study coordinator: Freundlich, Joel Stephen
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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.