Machine-learning-assisted continuous flow synthesis of clonidine.

Authors

Cloudius R Sagandira, Sinazo Nqeketo, Alexander Pomberger, Daniel Wigh, Christophe Len

Published in

Communications chemistry. Jun 29, 2026. Epub Jun 29, 2026.

Abstract

Clonidine•HCl is a clinically important imidazoline derivative whose manufacturing routes have seen little innovation since their development in the mid-to-late 20^th century. Its widespread use as an antihypertensive and neuroactive agent underscores the need for more efficient, modern production strategies. Herein, we report the first continuous flow strategy for the synthesis of clonidine. By integrating telescoped multistep sequences, inline liquid-liquid workup, advanced solid handling, and machine learning, we developed an intensified process that delivers clonidine•HCl in only 24 min total residence time across 5 continuous transformations, achieving an overall yield of 54%. This approach significantly outperforms conventional batch protocols, which typically require more than 18 h. The platform enables efficient and precisely controlled isothiocyanate formation, thiourea hydrolysis, S-methylation, and imidazoline cyclisation, while reducing intermediate isolations, minimising reagent handling, and eliminating hazardous materials associated with legacy routes. These advances provide a scalable, data-driven manufacturing solution and establish a foundation for intensified production of clonidine and related APIs under continuous flow conditions.

PMID:
42373924
Bibliographic data and abstract were imported from PubMed on 30 Jun 2026.

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