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Repurposing of H1-receptor antagonists (levo)cetirizine, (des)loratadine, and fexofenadine as a case study for systematic analysis of trials on clinicaltrials.gov using semi-automated processes with custom-coded software.

Authors :
Specht, Tim
Seifert, Roland
Source :
Naunyn-Schmiedeberg's Archives of Pharmacology; May2024, Vol. 397 Issue 5, p2995-3018, 24p
Publication Year :
2024

Abstract

To gain a comprehensive overview of the landscape of clinical trials for the H<subscript>1</subscript>-receptor antagonists (H<subscript>1</subscript>R antagonists) cetirizine, levocetirizine, loratadine, desloratadine, and fexofenadine and their potential use cases in drug repurposing (the use of well-known drugs outside the scope of the original medical indication), we analyzed trials from clincialtrials.gov using novel custom-coded software, which itself is also a key emphasis of this paper. To automate data acquisition from clincialtrials.gov via its API, data processing, and storage, we created custom software by leveraging a variety of open-source tools. Data were stored in a relational database and annotated facilitating a specially adapted web application. Through the data analysis, we identified use cases for repurposing and reviewed backgrounds and results in the scientific literature. Even though we found very few trials with published results for repurpose indications, extended literature research revealed some prominent use cases: Cetirizine seems promising in mitigating infusion-associated reactions and is also more effective than placebo in the treatment of androgenetic alopecia. Loratadine may be beneficial in the prophylaxis of G-CSF-related bone pain. In COVID-19, H<subscript>1</subscript>R antagonists may be helpful, but placebo-controlled scientific evidence is needed. For asthma, the effect of H<subscript>1</subscript>R antagonists only seems to be secondary by alleviating allergy symptoms. Our novel method to find potential use cases for repurposing of H<subscript>1</subscript>R antagonists allows for high automation, reduces human error, and was successful in revealing potential areas of interest. The software could be used for similar research questions and analyses in the future. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00281298
Volume :
397
Issue :
5
Database :
Complementary Index
Journal :
Naunyn-Schmiedeberg's Archives of Pharmacology
Publication Type :
Academic Journal
Accession number :
177062756
Full Text :
https://doi.org/10.1007/s00210-023-02796-9