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: 3122
Function: getPubMedXML
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
The freeze-drying process scale-up and transfer remain a complicated and non-uniform practice. We summarized inefficient and good practices in these papers and provided some practical advice. It was demonstrated that using the same process set points/times in laboratory and commercial scale dryers may lead to loss of product quality (collapse or vial breakage). The emerging modeling approach demonstrated practical advantages. However, the upfront generation of some input parameters (vial heat transfer coefficient, minimum controllable pressure, and maximum sublimation rate) is essential for model utilization. While the primary drying step can be transferred with a high degree of confidence (e.g., using modeling), and secondary drying is usually fairly straightforward, predicting potential changes in product behavior during freezing remains challenging.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1208/s12249-022-02463-x | DOI Listing |
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