Preparing anti-SARS-CoV-2 agent EIDD-2801by a practical and scalable approach,and quick evaluation via machine learning

EIDD-2801 is an orally bioavailable prodrug,which will be applied for emergency use authorization from the U.S.Food and Drug Administration for the treatment of COVID-19.To investigate the optimal parameters,EIDD-2801 was optimized via a four-step synthesis with high purity of 99.9%.The hydroxylamination procedure was telescoped in a one-pot and the final step was precisely controlled on reagents,temperature and reaction time.Compared to the original route,the yield of the new route was enhanced from 17% to 58% without column chromatography.The optimized synthesis has been successfully determinated on a decagram scale:the first step at 200 g and the final step at 20 g.Besides,the relationship between yield and temperature,time,and reagents in the deprotection step was investigated via Shapley value explanation and machine learning approach-decision tree method.The results revealed that reagents have the greatest impact on yield estimation,followed by the temperature.