为了全面了解H1受体拮抗剂(H1N1拮抗剂)西替利嗪的临床试验情况,左西替利嗪,氯雷他定,地氯雷他定,和非索非那定及其在药物再利用中的潜在使用案例(使用原医学适应症范围之外的众所周知的药物),我们使用新颖的自定义编码软件分析了clincialtrials.gov的试验,这本身也是本文的重点。为了通过其API自动从clincialtrials.gov获取数据,数据处理,和存储,我们通过利用各种开源工具创建了自定义软件。数据存储在关系数据库中,并带有注释,以促进专门改编的Web应用程序。通过数据分析,我们确定了用于重新利用的用例,并回顾了科学文献中的背景和结果.尽管我们发现很少有发表结果的试验用于重新调整适应症,广泛的文献研究揭示了一些突出的用例:西替利嗪在减轻输注相关反应方面似乎很有希望,并且在治疗雄激素性脱发方面也比安慰剂更有效.氯雷他定可能有益于预防G-CSF相关骨痛。在COVID-19中,H1N1拮抗剂可能会有所帮助,但需要安慰剂对照的科学证据。对于哮喘,H1N1拮抗剂的作用似乎仅是通过缓解过敏症状而产生的。我们的新方法来发现重新利用H1N1拮抗剂的潜在用例,可以实现高度自动化,减少人为错误,并成功揭示了潜在的兴趣领域。该软件将来可用于类似的研究问题和分析。
To gain a comprehensive overview of the landscape of clinical trials for the H1-receptor antagonists (H1R 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, H1R antagonists may be helpful, but placebo-controlled scientific evidence is needed. For asthma, the effect of H1R antagonists only seems to be secondary by alleviating allergy symptoms. Our novel method to find potential use cases for repurposing of H1R 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.