Biases in compound selection and synthesis. Both the methods used to obtain the list of selected compounds (from 423,466 unique ones to 12081 selected, see section 2.3) and the synthesizability of the compounds (878, see section 2.4) introduced biases. Table shows that team imolecule, lci, lci, virtualflow, molecule, and cermn had the largest numbers of compounds selected for the targets N, Nsp3, Nsp5, Nsp12, S and TMPRSS2, respectively (see bold red numbers). Figure displays these results by the method of selection, i.e., either by GTM, k-medoids, or top-ranked. Some teams had most of their selected compounds originate from consensus selection. For example lci, cermn, kyuken, and pharmai had many compounds selected by GTM (Figure ). In contrast, other teams (e.g., covid19ddc and sarswars) had most of their selected compounds directly from their top-ranked ones. Overall, the selected compound list and the synthesized compound lists are skewed toward the top 200 positions of each team for each protein target (Figure ). For jku, a bias was found in the number of synthesized compounds (62) versus those selected (259) likely due their chemical similarity and the fact that they can be easily synthesized (see 'benzotriazolyl acetamide' family in the next sections and in discussion section 3 below). Some teams had large numbers of molecules selected in the first step but none were finally synthesized. For example team belarus had 32 compounds for Nsp5 and 67 for S, but none of them were selected by WuXi Apptec since these compounds did not pass their ADME filters and/or cost/feasibility analysis. If the filtering would have been known a priori, the teams could have likely had more suitable compounds in their submitted lists thus avoiding the fact that some teams ended up with zero compounds. We could not discern a clear trend in the origin of selection of the compounds (i.e., GTM, k-medoids, or top-ranked) versus what was synthesized by WuXi Apptec in the end (Figure ), but the percentage of GTM compounds did increase ~10% in favor of top-ranked compounds (Figure ). We do not deem this significant, that is, the selection method did not influence which compounds were eliminated by the WuXi Apptec filtering.