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 large costs associated with modern drug discovery mean that governments and regulatory bodies need to provide economic incentives to promote the development of orphan drugs (i.e., medicinal products that are designed to treat rare disease that affect only small numbers of patients). Under European Union (EU) legislation, a medicine can only be authorised for treating a specific rare disease if it is not similar to other orphan drugs already authorised for that particular disease. Here, we discuss the use of 2D fingerprints to calculate the Tanimoto similarity between potential and existing orphan drugs for the same disease, and present logistic regression models correlating these computed similarities with the judgements of human experts.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.drudis.2016.11.024 | DOI Listing |
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!