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
A new model has been developed for predicting size distributions delivered from pressurized metered dose inhalers (pMDIs) that contain suspended drug particles. This model enables the residual particle size distribution to be predicted for a broad range of formulations. It expands on previous models by allowing for polydisperse micronized input drug, multiple suspended drugs, dissolved drug, and dissolved or suspended excipient to be included in the formulation. The model indicates that for most pMDI configurations, the majority of droplets contain no drug or a single drug particle and the residual particle size distribution delivered from the pMDI is essentially equivalent to the size distribution of the micronized drug used in the formulation. However, for pMDIs with a high drug concentration or that use small micronized drug particles, there can be a substantial fraction of the droplets that contain multiple drug particles. The residual particle size distribution obtained from these pMDIs can be substantially larger than the size distribution of the micronized drug. Excellent agreement was observed between size distributions predicted using this model and those obtained from experimental cascade impactor measurements (r(2)=0.97), thus demonstrating the ability of the model to accurately predict the size distributions obtained from suspension pMDIs.
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Source |
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http://dx.doi.org/10.1016/j.ijpharm.2011.10.035 | DOI Listing |
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