For impurity prediction, we used the impurity prediction module in the ASKCOS software suite (Figure ). Specifically, we used the latest model trained on the larger Pistachio dataset [37], as compared to the Reaxys dataset. A key difference between these models lies in the curated data in Pistachio, along with the coverage of more reactions reported in the US Patents and Trademark Office data releases . Since the impurity prediction module, by default, is meant to produce the top impurities in the dataset, and we were more interested in getting access to the larger set of low-level impurities, we changed some of the default parameters. After a set of carefully designed manual iterations, we settled on increasing the top-k predictions to 10 from the default 3, and decreasing the threshold probability from the default 0.1 to 0.01. The top-k predictions is a criterion to filter the output predictions based on their similarity to the major product, while the threshold probability is a way to calculate the probability of the existence of the product as a result of the reaction under consideration. Here, we would like to clarify that the probability is an implicit function of the training dataset, and the lack of reported impurities in the dataset affects the probability. Also, the probability does not necessarily reflect the chemical feasibility of the impurity product, nor does it reflects the kinetic barriers for a particular product being generated. We have discussed how these chemistry-informed concepts can be incorporated into the impurity prediction pipeline in Future Directions. Computational sustainability was a key element in the design of the impurity prediction pipeline, apart from the ease of usage by experimentalists. To ensure that the pipeline remained computationally feasible, within reasonable costs, while also providing results that did not take longer times to compute, we tested a range of computing configurations on Amazon Web Services . Ultimately, we settled on the ASKCOS software suite being hosted on an AWS EC2 instance with the default configuration. For the impurity prediction, we queried the ASKCOS instance within the enterprise firewall. All the tests were made on a 4-core Intel i7 system. For the demonstrated 3-steps reaction of paracetamol synthesis, we clocked 4 min of wall time and 719 ms of CPU time to obtain the results.