From Animal Models to NAMs: AI/ML-Driven Predictive Toxicology
Dr. O. Barberan’s presentation highlights a paradigm shift in toxicology, driven by AI, ML, and NAMs, to fundamentally replace traditional animal testing. By integrating human-relevant models—such as organoids, high-content imaging, and mechanistic computational tools—the approach aims to overcome the predictive shortcomings of animal models, particularly species differences and translational failures in DILI. Evidence shows […]