We noted that the fingerprint size used to encode the product had a marginal effect on the ability of the model to predict full synthetic routes for the internal virtual library dataset (Supplementary). In addition, we found that increasing the size of the stock library to include the ACD catalogue, increased the ability of the model to predict full synthetic routes to compounds in the virtual library. For both the 'Combinatorial' and 'Bespoke' libraries, the model was able to reduce the average time taken to predict full synthetic routes with the ACD catalogue, as well as reduce the average number of steps by one. The reduction in the average number of steps is more pronounced for the 'Bespoke' libraries, whereby it is consistent over both the USPTO and Reaxys datasets. This is in comparison to the 'Combinatorial' libraries whereby the reduction in the number of steps is not observed for the combined Reaxys and patent data (Supplementary).