Beyond target-level screening, our long-term vision is to establish an AI-assisted whole-cell modeling framework that captures the complex, interconnected nature of cellular physiology. This model will integrate lipid metabolism, signal transduction pathways, gene expression regulation, glucose and energy metabolism, and other essential biochemical networks to evaluate drug responses at the single-cell and organoid scales. Central to this approach is the explicit modeling of drug effects at the level of individual enzymes, where predicted changes in binding affinity or activity are incorporated into kinetic rate constants for each biochemical reaction. These enzyme-level perturbations will then propagate through the interconnected reaction network, allowing us to simulate how molecular-scale drug–target interactions translate into system-level cellular responses. Ultimately, this integrated framework will enable mechanistically grounded predictions of drug efficacy, toxicity, and pathway-level effects, bridging molecular docking results with functional phenotypes observed in cells and organoids.