Professor Yang Huanghao's team at Fuzhou University, in collaboration with Professors Li Jingying and Zhou Jie, employed endogenous lipoic acid (LA) as a universal self-assembling building block. They constructed a ternary coassembly database comprising 63 clinically used smallmolecule drugs, yeilding1352 distinct assembly combinations. After digitizing molecular features with extended-connectivity fingerprints (ECFPs), they systematically optimized four machine learning algorithms. The final ensemble model, Best@LA, achieved a 100% positive predictive rate in experimental validation, with all top-ten predicted combinations successfully forming stable nano-assemblies.