Researchers have conducted a large-scale single-cell analysis and in silico perturbation to study the dynamic evolution of hepatocellular carcinoma (HCC). The study involves integrating single-cell atlases and machine learning to predict individualized drug responses and identify high-risk cells. The approach combines various techniques, including temporal network analysis, multi-omics, and artificial intelligence, to guide precision therapeutics and potentially inform drug discovery.