Preparing anti-SARS-CoV-2 agent EIDD-2801 by 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 hydroxy...

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Autores principales:	Zhen Qin, Bin Dong, Renbing Wang, Dechun Huang, Jubo Wang, Xi Feng, Jinlei Bian, Zhiyu Li
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	EIDD-2801 SARS-CoV-2 Antiviral drug Decision tree Shapley value Therapeutics. Pharmacology RM1-950
Acceso en línea:	https://doaj.org/article/e311f1d537714e31bf747cecb30787ef
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spelling	oai:doaj.org-article:e311f1d537714e31bf747cecb30787ef2021-12-02T05:01:26ZPreparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning2211-383510.1016/j.apsb.2021.10.011https://doaj.org/article/e311f1d537714e31bf747cecb30787ef2021-11-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2211383521004032https://doaj.org/toc/2211-3835EIDD-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.Zhen QinBin DongRenbing WangDechun HuangJubo WangXi FengJinlei BianZhiyu LiElsevierarticleEIDD-2801SARS-CoV-2Antiviral drugDecision treeShapley valueTherapeutics. PharmacologyRM1-950ENActa Pharmaceutica Sinica B, Vol 11, Iss 11, Pp 3678-3682 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	EIDD-2801 SARS-CoV-2 Antiviral drug Decision tree Shapley value Therapeutics. Pharmacology RM1-950
spellingShingle	EIDD-2801 SARS-CoV-2 Antiviral drug Decision tree Shapley value Therapeutics. Pharmacology RM1-950 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
description	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.
format	article
author	Zhen Qin Bin Dong Renbing Wang Dechun Huang Jubo Wang Xi Feng Jinlei Bian Zhiyu Li
author_facet	Zhen Qin Bin Dong Renbing Wang Dechun Huang Jubo Wang Xi Feng Jinlei Bian Zhiyu Li
author_sort	Zhen Qin
title	Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning
title_short	Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning
title_full	Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning
title_fullStr	Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning
title_full_unstemmed	Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning
title_sort	preparing anti-sars-cov-2 agent eidd-2801 by a practical and scalable approach, and quick evaluation via machine learning
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/e311f1d537714e31bf747cecb30787ef
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Preparing anti-SARS-CoV-2 agent EIDD-2801 by a practical and scalable approach, and quick evaluation via machine learning

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