Nonetheless, there are potential changes in future work that could be made to improve the functionality of the reported tool. While impurity awareness is important, it would be more useful to understand yields of impurities depending on concentrations of starting materials (e.g. distinguishing between major and minor impurities). Additionally, the workflow assumes that Reaxys® data is inherently correct which may not always be true, and it is also sensitive to missing condition data such as temperature. On average, only 50 -60 % of final analogue reaction lists contained a temperature record, which can lead to removal of important impurities (although this did not adversely impact results in the case studies). Consideration of the effects caused by other reaction components and conditions such as solvents, pressure and reaction times would also improve the quality of the suggested outcomes. Ultimately, there is a need to apply the workflow to a larger variety of case studies to assess how well it copes with reactions featuring more complex chemistries (e.g. ring forming, ring breaking, regioselective reactions, protective and deprotective group interactions). Regardless, this work can serve as a benchmark and as an example for how well-curated prior reaction data can aid in the development of more sophisticated algorithms for reaction prediction with easily interpretable results.