The results for the multi-objective analogue of the kinase inhibitor design problem illustrate a similar picture to its single objective counterpart and reinforce our findings. Strategies characterized by a higher degree of constraint violation risk tend to fully resolve the Pareto front after evaluation of about half of the parameter space. Comparatively, we expect to explore about 95% of the space using random sampling before this condition is met. Again, the FCA-0.8 strategy, which induces a high degree of risk aversion violates the synthesizability constraint function at a rate of only 11.5 ± 0.2%, the lowest such rate among tested strategies.