The organic linkers corresponding to these 5,178 MOFs were then passed to the trained RF-based classifier to predict their potential toxicity. 809 linkers were classified as potentially safe, 2,252 as potentially toxic and 1,993 as potentially fatal; for approximately 120 linkers, featurization was not successfulpossibly due to complexities during the fragmentation procedure. Since these linkers accounted for ca. 2% of all linkers, they were thus ignored from considerationand we anticipate that this low percentage does not affect the subsequent analysis performed. This list of 809 MOFs with safe linkers has been reported in Supporting Information, Section S9. Figure shows the distribution of the 6 continuous features (MaxPartialCharge, MinEStateIndex, MinAbsPartialCharge, EState_VSA1, VSA_EState2, SMR_VSA6), having the highest correlation to the observed toxicity as identified in Figure . Fatal molecules have the highest average MaxPartialCharge (0.35) with toxic molecules having the lowest average (0.25). On the other hand, safe molecules have the lowest average MinEStateIndex compared to toxic and fatal molecules (-1.82, -0.94, and -1.57, respectively). In the context of the MinAbsPartialCharge, safe molecules had the highest average (0.28), with fatal molecules having the lowest (0.20). Safe molecules again had the highest EState_VSA1 when compared to toxic and fatal molecules (21.95, 12.93, and 16.09 respectively). This further translated to VSA_EState2 with similar average values. Lastly, with regards to SMR_VSA6, safe molecules had an average value intermediary to toxic and fatal molecules (4.59, 6.58, and 3.05). It is however evident that these distributions overlap considerablywith rather subtle differences between individual features. It thus becomes difficult to infer useful guiding principles on linker design on the basis of these distributions, relying purely on experimental approaches. This brings us back to the point that we initially raised, that although there are chemical trends that guide biocompatibility, these are difficult to generalize. It is hypothesized that these subtle differences add up due to synergistic interactions between several features, resulting in large apparent differences in observed toxicity profiles. While these trends may not be necessarily intuitive, they nonetheless suggest regions in the chemical space that are theoretically safe for the design of bio-compatible linkers. More recent computational approaches, such as generative models are particularly good at modelling these distributions, by exploiting subtle differences for inverse design.