Global Toxicology and Risk Assessment

Computational Toxicology and AI Applications

Computational toxicology integrates data modeling and artificial intelligence in risk prediction. This session highlights tools like QSAR models, machine learning, and virtual screening. These technologies enhance hazard identification and reduce reliance on animal tests. Data integration from multiple sources strengthens predictive capacity. Regulatory adoption of computational tools is growing steadily. Limitations and transparency of AI models are discussed. Digital innovation is transforming modern toxicological science.