We showcase this workflow in the optimization of two consecutive steps on route to the synthesis of an active pharmaceutical ingredient (API) for the treatment of asthma : a Pd-catalyzed Hayashi-Heck and a Rh-catalyzed alkene hydroformylation reaction. The successful implementation of this strategy was enabled by the construction of a density functional theory (DFT) derived descriptor database of >550 bisphosphine ligands and the development of an interpretable chemical space mapping technique. Stringent purity requirements for APIs and the high cost of purification on a multi-kilogram scale demand that catalysts used in process chemistry routes impart exquisite chemo-, stereo-, and regioselectivity coupled to a high-yielding reaction. This endeavour succeeded in identifying ligands that furnished simultaneous and significant improvement of all objectives-yield, stereo-, and regioselectivity-to improve the scalability of the current route to the API. More generally, we showcase how the multi-objective workflow can be successfully applied to reactions using different transition metals that require distinct bisphosphine ligands to be effective. This large virtual library and the requisite dataprocessing scripts are publicly available, significantly enabling practitioners in academia and industry to shorten timelines for catalyst optimization campaigns where performance is controlled by bisphosphine ligands.