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
Dry layer resistance, which is the resistance of dried cake against water vapor flow generated from sublimation, is one of the important parameters to predict maximum product temperature and drying time during primary drying in lyophilization. The purpose of this study was to develop the predictive model of dry layer resistance under various primary drying conditions using the dry layer resistance obtained from a preliminary lyophilization run. When the maximum dry layer resistance was modified under the assumption that the chamber pressure is zero, the modified dry layer resistance, which is defined as specific dry layer resistance, correlated well with the sublimation rate. From this correlation, the novel predictive model including the empirical formula of sublimation rate and specific dry layer resistance is proposed. In this model, the dry layer resistance under various conditions of shelf temperature and chamber pressure was successfully predicted based on the relationship of the sublimation rate and specific dry layer resistance of the edge and center vials obtained from the product temperature in one preliminary cycle run. It is expected that this predictive model could be a practical and useful tool to predict product temperature during primary drying.
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Source |
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http://dx.doi.org/10.1016/j.ijpharm.2013.04.081 | DOI Listing |
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