In the case studies where the auxiliary tasks were Suzuki R3-4, the reactivity of the substrates was much more similar in both the main and the training tasks, leading to similar optimal conditions being found. This means that MTBO achieved better, and much faster, results than STBO in these cases. Performance of MTBO can be greatly improved using multiple auxiliary tasks. As shown in Figure , when Suzuki B1 is optimized with Suzuki R1-R4 as auxiliary tasks, the optimal conditions are always found by MTBO in fewer than five experiments. Both P1-L1 and P2-L1 are considered optimal for this reaction, and MTBO selects these two catalysts in over 80 % of experiments during twenty repeats, when compared to < 50 % frequency for STBO -this is highlighted in Figure . As MTBO utilizes optimal regions of chemical space that have been identified in previous tasks with similar reactivity, this allows the algorithm to identify new (and better performing) optimal reaction conditions faster. These simulated case studies suggest that the use of MTBO is often beneficial, particularly when not mapping the predicted reactivity differences of the main and auxiliary substrates a priori. Initial guesses (optimization starting points) are typically better than random initialization because of previous reaction information, and the rate of 'best yield' improvement is also greater. In the bestcase scenario, the reactivity of the new substrate is similar to those of previous datasets and results in a greater yield much faster than standard STBO. In the worst-case scenario, MTBO can fail with one noisy auxiliary case, but we found that using multiple auxiliary tasks helps to mitigate these issues. With these findings, we were confident that MTBO would be effective in real-world case studies where we have experimental datasets from previous optimization campaigns. Further in silico case studies for other reaction types, namely Buchwald-Hartwig cross couplings, were also conducted and showed similarly promising results; these studies can be found in the Supporting Information.