Startseite Comprehensive and in-depth insights into photo-assisted halogenation reactions: a pharmaceutical industry perspective
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Comprehensive and in-depth insights into photo-assisted halogenation reactions: a pharmaceutical industry perspective

  • Aditi Prabhu , Pradip Mali , Satyapaul A. Singh und Inkollu Sreedhar ORCID logo EMAIL logo
Veröffentlicht/Copyright: 18. November 2024
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Abstract

Halogenation reactions are a vital area of study for the pharmaceutical industry. The study of the reaction conditions along with the reactors and their scale-up is a thrust area in drug synthesis and manufacturing. There is a shift in the research community towards accommodating renewable energy sources which has driven scientists to include energy sources that are sustainable and aid in making the overall process efficient. This review provides a comprehensive overview of the challenges in selecting the best catalyst, light source and reaction conditions for the fluorination, chlorination and bromination reactions. This paper goes a step further to explain the photoreactors’ design and modelling as well as the scale-up of the same. Overall, it provides a comprehensive view of diverse scientific areas, from halogenation in drug synthesis to the potential of photochemical batch and flow approaches in halogenation reactions.


Corresponding author: Inkollu Sreedhar, Department of Chemical Engineering, BITS Pilani Hyderabad Campus, Hyderabad, 500078, India, E-mail:

Acknowledgments

The authors extend their appreciation to BITS Pilani Hyderabad Campus for facilitating this project.

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: AP: Conceptualization, Methodology; Investigation; Drafting-Original and revised version. PM: Conceptualization, Methodology; Investigation; Drafting-Original and revised version. SS: Drafting-Revised version and editing. IS: Conceptualization; Project Administration; Supervision; Writing-Review and editing.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: None declared.

  7. Data availability: Not applicable.

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Received: 2024-04-05
Accepted: 2024-09-24
Published Online: 2024-11-18
Published in Print: 2025-01-29

© 2024 Walter de Gruyter GmbH, Berlin/Boston

Heruntergeladen am 21.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/revce-2024-0021/html?lang=de
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