Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1075
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3195
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Generally, since at least 6 months are usually needed for accelerated testing of tablet at 40 °C/75% relative humidity (RH), it would be crucial important to predict the dissolution profiles during long-term storage period by using samples stored with shorter periods such as 3 months. In this study, we developed a new method for predicting changes in dissolution from tablets during long-term storage-based changes in the available surface area [S (t)]. In addition, we discussed the dissolution behavior and mechanisms using S (t). The results revealed drastic delays in dissolution in samples stored at 40 °C/75% RH for 7 weeks. Considering changes of S (t) patterns, this delay was derived from changes of the tablet surface. New parameters, namely T and T, calculated from the S (t) profile tended to increase with an increased duration of testing. Concerning the long-term prediction model using short-term data, a nonlinear model was deemed appropriate because good agreement was observed between the value predicted using the model and the measured value for samples stored at 40 °C/75% RH for 6 months. Therefore, using the new evaluation method based on S (t), we can predict changes in dissolution during long-term storage using short-term methods.
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http://dx.doi.org/10.1016/j.ijpharm.2020.119504 | DOI Listing |