Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Triclabendazole (TCB) is a well-established anthelmintic effective in treating fascioliasis, a neglected tropical disease. This study employs quality by design (QbD) to investigate the impact of TCB polymorphism and pharmacotechnical variables, from the development of immediate-release tablets to process optimization and green analysis. Critical process parameters (CPPs) and critical material attributes (CMAs), characterized by type of polymorph, composition of excipients (talc, lactose, cornstarch, and magnesium stearate), and compression force, were screened using a Plackett-Burman design (n = 24), identifying polymorphic purity and cornstarch as a CPP. To establish a mathematical model linking CPP to dissolution behaviour, a multiple linear regression (MLR) was applied to the training design (central composite design, n = 18). Simultaneously, a near-infrared spectroscopy coupled to partial least squares (NIR-PLSs) method was developed to analyze CPPs. An independent set of samples was prepared and analyzed using the NIR-PLSs model, and their dissolution profiles were also obtained. The PLSs model successfully predicted the CPPs in the new samples, yielding almost quantitative results (100 ± 3%), and MLR dissolution predictions mirrored the actual dissolution profiles (f2 = 85). In conclusion, the developed model could serve as a comprehensive tool for the development and control of pharmaceutical formulations, starting from the polymorphic composition and extending to achieve targeted dissolution outcomes.
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Source |
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http://dx.doi.org/10.3390/pharmaceutics16121594 | DOI Listing |
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