Using machine learning to predict how different cells respond to drugs

Machine Learning for Drug Response Prediction

['FUNDING_OTHER'] · UNIVERSITY OF MICHIGAN AT ANN ARBOR · NIH-10836685

This study is working on smart computer programs that can help doctors understand how different types of cells in your body might react to certain medications, making it easier to find the right treatment just for you.

Quick facts

Phase['FUNDING_OTHER']
Study typeNih_funding
SexAll
SponsorUNIVERSITY OF MICHIGAN AT ANN ARBOR (nih funded)
Locations1 site (ANN ARBOR, UNITED STATES)
Trial IDNIH-10836685 on ClinicalTrials.gov

What this research studies

This research focuses on developing advanced algorithms to predict how specific cell types respond to various medications, which is crucial for personalized medicine. The team aims to overcome challenges in transferring drug response predictions from laboratory settings to real human applications, addressing issues like sample diversity and mutation evolution. By refining their models and utilizing large language models to enhance drug information, they hope to improve the accuracy of these predictions and ultimately aid in more effective drug development.

Who could benefit from this research

Good fit: Ideal candidates for this research are patients with specific genetic mutations or conditions that affect how their cells respond to medications.

Not a fit: Patients with conditions that do not involve cellular responses to drugs or those who are not undergoing treatment may not benefit from this research.

Why it matters

Potential benefit: If successful, this research could lead to more personalized and effective drug treatments for patients based on their unique cellular responses.

How similar studies have performed: Previous research has shown promise in using machine learning for drug response predictions, indicating that this approach has potential for significant advancements in personalized medicine.

Where this research is happening

ANN ARBOR, UNITED STATES

Researchers

About this research

  1. This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
  2. Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
  3. For full project details, budget, and progress reports, visit the official NIH RePORTER page below.

View on NIH RePORTER →

Last reviewed 2026-05-15 by the Find a Trial editorial team. Information on this page is for educational purposes and is not medical advice. Always consult qualified healthcare professionals about clinical trial participation.