Creating personalized drug formulations using machine learning
Designing Personalized Formulations with Machine Learning
['FUNDING_OTHER'] · DUKE UNIVERSITY · NIH-11116946
This study is working on creating better ways to deliver medications using smart technology, so that patients can get more effective and safer treatments that are specially designed for their needs.
Quick facts
| Phase | ['FUNDING_OTHER'] |
|---|---|
| Study type | Nih_funding |
| Sex | All |
| Sponsor | DUKE UNIVERSITY (nih funded) |
| Locations | 1 site (DURHAM, UNITED STATES) |
| Trial ID | NIH-11116946 on ClinicalTrials.gov |
What this research studies
This research focuses on improving the design of drug formulations to enhance the delivery and effectiveness of medications. By utilizing innovative machine learning techniques, the project aims to develop targeted drug delivery systems that can optimize the formulation process, moving away from traditional trial-and-error methods. The approach includes designing functional excipients, self-assembling nanoparticles, and tissue-selective prodrugs, which will be validated through laboratory experiments. This could lead to more effective and safer medications tailored to individual patient needs.
Who could benefit from this research
Good fit: Ideal candidates for this research are patients requiring advanced drug therapies that could benefit from personalized drug formulations.
Not a fit: Patients with conditions that do not require complex drug formulations or those who are not candidates for targeted therapies may not benefit from this research.
Why it matters
Potential benefit: If successful, this research could lead to more effective and personalized medications that improve patient outcomes.
How similar studies have performed: Other research has shown promise in using machine learning for drug formulation, indicating potential for success in this innovative approach.
Where this research is happening
DURHAM, UNITED STATES
- DUKE UNIVERSITY — DURHAM, UNITED STATES (ACTIVE)
Researchers
- Principal investigator: REKER, DANIEL — DUKE UNIVERSITY
- Study coordinator: REKER, DANIEL
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.