KEGG drugs database gives a list of drug molecules as active pharmaceutical ingredients. To test the performance of the final policy model 'decision makers', molecules were crawled from the database to compute reaction pathways to them. Since the reaction pathways were compared by reactions pools from organic chemical, biological and hybrid databases, only 3,821 drug molecules co-existing in the chemical and biological datasets were used as the target drug molecules to compare the optimal reaction pathways from the three datasets. Here we also filtered these molecules into a set of 3,746, to contain only molecules with SMILES string length greater than 10 to increase the synthetic planning complexity, see SI. The final policy model 'decision makers' from the three reactions pools were used to identify the synthetic pathways for each of the drug molecules. The results from the three environments are shown in Figure . Different from other random selected target molecules with shorter SMILES string lengths, the drug molecules are more difficult to find synthetic routes. Whilst the target molecules are usually being synthesised within five steps, the cost to make drug molecules reach median of 100 for the three datasets, which means the routes always point to a dead-end molecule. This indicates that due to the molecular complexity, the majority of drug molecules cannot be synthesised with the demonstrated method and datasets. For further work, we could use partial reactions to predict functional transformations. In this way, more possible solutions could be given to the synthetic routes. However, it is also seen that the hybrid environment exhibits a heavier tail towards lower costs to make the molecules. This means the method opens possibilities to synthesise a significant proportion of drug molecules making use of the full set of chemistry combining organic synthesis and synthetic biology.