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

In this new article publication from Acta Pharmaceutica Sinica B, authors Zhen Qin, Bin Dong, Renbing Wang and colleagues from the China Pharmaceutical University, Nanjing, discuss how EIDD-2801 was optimized in a decagram scale with overall yield of 58% under a four-step synthesis.

EIDD-2801, an orally bioavailable prodrug, received first authorization globally on 4 November 2021 by MHRA, and 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. 

Article reference: Zhen Qin, Bin Dong, Renbing Wang, Dechun Huang, Jubo Wang, Xi Feng, Jinlei Bian, Zhiyu Li, Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning, Acta Pharmaceutica Sinica B, 2021, ISSN 2211-3835, https://doi.org/10.1016/j.apsb.2021.10.011

Keywords: EIDD-2801, SARS-CoV-2, Antiviral drug, Decision tree, Shapley value

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The Journal of the Institute of Materia Medica, the Chinese Academy of Medical Sciences and the Chinese Pharmaceutical Association.

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CiteScore: 12.5

Impact Factor: 11.614

JIF without self-citation: 10.746

 

ISSN 2211-3835

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