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
We applied the principles of quality by design to the production process of a pharmaceutical gel by using the near infrared spectroscopy (NIRS) technique in combination with multivariate chemometric tools. For this purpose, we constructed a D-optimal experimental design having normal operational condition (NOC) batches as central point. The primary aim here was to develop an expeditious NIRS method for determining the composition of a pharmaceutical gel and assess the temporal changes in major physical factors affecting the quality of the product (specifically, viscosity and pH). Gel components were quantified by using partial least squares (PLS) calibration models of the PLS1 type. The study was completed by using the batch statistical process control method to compare product batches included in the experimental design with NOC batches. Similarities and differences between the two types of batches were identified by using control charts for residuals (Q-statistic) and Hotteling's T2 (D-statistic). The ensuing models, which were subject to errors less than 5%, allowed the gel production process to be effectively monitored. As shown in this work, the NIRS technique is a highly suitable tool for process analytical technology.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/jps.22607 | DOI Listing |
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