Cotet, T.-S.; Krawczuk, I.; Pacesa, M.; Nickel, L.; Correia, B. E.; Haas, N.; Qamar, A.; Challacombe, C. A.; Kidger, P.; Ferragu, C.; Naka, A.; Castorina, L. V.; Subr, K.; Kluonis, T.; Stam, M. J.; Unal, S. M.; Wood, C. W.; Stocco, F.; Ferruz, N.; Kurumida, Y.; Calia, C. N.; Paesani, F.; Machado, L. d. A.; Belot, E.; Gitter, A.; Campbell, M. J.; Hallee, L.; Adaptyv Competition Organizers,

In this report, we summarize and analyze the 2024 Adaptyv EGFR protein design competition. Participants used computational and ML methods of their choice to design proteins to bind the EGFR, a key drug target that plays a critical role in cell growth, differentiation, and cancer development. Over 1800 designs were submitted to the competition across two rounds. Of these, 601 proteins were selected and characterized for expression and binding affinity to EGFR, with competitors both optimizing existing binders (achieving 1.21 nM) and creating novel (de novo) binders (achieving 82 nM). All selected designs were experimentally validated with Adaptyv\'s automated BLI pipeline. This illustrates the potential of crowdsourced competitions to drive creativity and innovation in protein design. However, the competition also exposed key challenges, such as the lack of standardized benchmarks, standardized experimental design targets, and robust computational metrics for method comparison. We anticipate that future competitions will allow for addressing these gaps and motivate continued progress in computational protein design.