• Most experimentally reported MOFs that were predicted to be 'safe', except for Zr-centered MOFs, lack the desired porosity, posing a challenge for drug delivery applications where ample pore volume is essential. This emphasizes the potential of Zr-based MOFs for healthcare applications due to their high biocompatibility and superior pore characteristics. It also underscores the necessity for theory-guided rational MOF design using the principles outlined in this study to create highly porous, biocompatible MOFs. Furthermore, the emergence of generative AI techniques in materials science will be a valuable tool for achieving this goal. The idea of being able to predict the toxicity of a material from its precursors is, by all means, an approximation. At present, our models do not consider factors such as node connectivity, pH and chemical stability, or the presence of defects. In realistic scenarios, several factors such as strength of bonds, particle sizes and external surface chemistry would also contribute to the toxic effects. Since MOF degradation is expected after the drug release process, our models here are meant for screening purposes of their building blocks, with an intent of restricting the number of MOF and building block candidates that need to be experimentally tested. This approach will help reduce associated costs, timescales, experimental burden and, more importantly, address the ethical concerns pertaining to animal studies. These approximations are also the reason we did not develop regression-based models, as quantitative predictions would rarely have any correlation to observations in realistic scenarios. Such approximations are not uncommon to most modeling approaches such as density functional theory and molecular dynamics, where strategies such as force-field mixing and treating materials as a sum of their parts are routinely employed. Having screened over 800 potentially safe candidates for drug delivery, we are optimistic of the applicability of these materials at a clinical level. Looking to the future, there are several ways these findings can be utilized. These 800 MOFs can be further screened using computational approaches for ideal properties such as surface chemistry and interactions with therapeutic agents to shortlist ideal candidates that can be explored in-depth using experimental approaches. Alternatively, operating according to the design guidelines and within the chemical spaces identified suggests the possibility of discovering new MOFs for drug delivery applications. In either case, the experimental outcomes can be used as feedback to further optimize model performance.