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
Aggregate criteria for individual bioequivalence allow a tradeoff between difference in average bioavailability and reduction in within-subject variability. That is, a large difference in the average bioavailability between a test and a reference formulation can be offset by a sufficient reduction in variability of the test formulation. This offset could allow the test formulation to pass many individual bioequivalence criteria. We have identified 4 possible approaches for dealing with this tradeoff issue: say "No problem," since a reduction in variability is desirable; use disaggregate criteria; use general weighted forms of the individual bioequivalence criteria that weight the variance terms; and change the acceptable upper limits to reduce the impact of scaling to the reference formulation's within-subject variability. A dataset with a 14% increase in average bioavailability and a 48% reduction in within-subject standard deviation is used as an example of these issues.
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