In the past few years, a combination of scientific and technical advances has made it possible to conceptualize a benchmarking exercise that can overcome some of these limitations. Among the most important is the creation of ultra-large libraries of chemicals that can be described in silico and procured "on-demand" . This reduces significantly the cost associated with accessing chemical matter to test predictions. There has also been a dramatic increase in the availability of computational resources, which facilitates data sharing and democratizes the ability to make predictions. Hand in hand with the improvements in infrastructure has been the development of new computational algorithms, both machine learning and physics-based. Recently, all these advances were mobilized within community-wide efforts to identify new chemical starting points for SARS-CoV-2 drug discovery .