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

Abstract

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.

Keywords

• EIDD-2801
• SARS-CoV-2
• Antiviral drug
• Decision tree
• Shapley value