Artificial intelligence-based modeling and validation for prediction of drug delivery capacity and cytotoxicity in design of porous materials
Mahboubeh Pishnamazi
Metal organic frameworks (MOFs) have attracted attention for application of drug delivery because of their ordered porous properties. Optimizing both drug loading capacity and biocompatibility remains a complex challenge for MOFs because these performance indicators depend on nonlinear interactions among structural, compositional, and physicochemical features. In this study, an explainable ensemble learning framework was developed to predict Drug Loading Capacity (g/g) and Cell Viability (%) of