Compound optimization within a project tends to follow a pattern. Projects start with a lead compound (sometimes more than one) found by design or random screening and proceed by making relatively small, incremental changes to the structure of the lead, measuring the response to the changes in an assay. This guides the chemists' choice of the next compound to make. The cycle repeats until either a compound suitable for progression is found or the patience of the project manager is exhausted, at which point the project ends. This paints a rather skeletal picture of a chemical project and does not capture some of the subtleties seen in real projects -series diverging in multiple directions at once, sudden serendipitous discoveries that radically change the projects focus etc. But for the purposes of modelling projects a simpler, reductive approach has been adopted. The aim is to create a "digital twin" 6 of a project that reproduces its statistical behavior rather than the structures of the individual compounds within it.