Brazilian and French researchers have developed an imaging-based AI tool to predict how multiple sclerosis patients will respond to natalizumab treatment.
Key Details
- 1Combines high-content cell imaging and machine learning to analyze patient blood samples before natalizumab therapy.
- 2Study used over 400 cell morphological features, with 130 key characteristics for prediction.
- 3Tool achieved 92% accuracy in discovery and 88% in validation cohorts for predicting drug response.
- 4Non-responders showed distinct actin remodeling and cell morphology (more elongated CD8+ T cells).
- 5Findings published in Nature Communications, suggesting potential for broader disease and drug applications.
Why It Matters

Source
EurekAlert
Related News

USC Unveils Joint Biomedical Engineering Department Bridging Medicine, Engineering, and Imaging
USC's medical and engineering schools launch a joint biomedical engineering department to accelerate interdisciplinary research and innovation, including imaging and AI.

AI Predicts Risks for Outpatient Stem Cell Therapy in Myeloma
Researchers use machine learning to predict adverse events during stem cell therapy for multiple myeloma, improving outpatient safety.

AI-Enhanced CT Heart Fat Measurement Boosts Cardiovascular Risk Prediction
AI-derived measurement of heart fat from CT scans significantly improves long-term cardiovascular disease risk prediction.