There is a balance between the number of reaction templates and the reaction space they represent, which is specific to the domain in which the tool is applied. However, increasing the number of reaction templates also introduces noise and does not necessarily mean that there is an increase in the diversity of templates, nor coverage of the reaction space. This can be seen in Figure , where the overall predictive performance falls by 4 % and 6 % for the 'combinatorial' and 'bespoke' libraries respectively, when increasing the template library size from 77,281 to 285,018 reaction templates. the test set, as compared to the overall performance. The overall performance is with respect to the ability to predict full synthetic routes to a set of 1,731 compounds from 41 virtual libraries designed at AstraZeneca. The experimental average refers to the percentage of compounds synthesized out of those sent for synthesis after refinement of the virtual library. The accuracy decreases with increasing template library size, whereas the overall predictive performance increases up to a library size of the 77,281 most frequently occurring reactions. b) The virtual library set can be further broken down into libraries designed using a 'combinatorial' approach, and a broader set of reactions using more 'bespoke' chemistry. The overall model performance increases marginally for the 'combinatorial' libraries with increasing template library size. Whereas, the libraries requiring more 'bespoke' chemistry for their synthesis benefit from the inclusion of additional reactions.