Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Significant advances in analytical technologies have dramatically improved our ability to deconvolute disease biology at molecular, cellular, and tissue levels. Quantitative system pharmacology (QSP) modeling is a computational framework to systematically integrate pharmaceutical properties of a drug candidate with scientific understanding of that deeper disease etiology, target expression, genetic variability, and human physiological processes, thus enabling more insightful drug development decisions related to efficacy and safety. In this chapter, we discuss the key attributes of QSP models in comparison to traditional models. We discuss a recommended four-step process to construct a QSP model to support drug development decisions. A number of illustrative QSP examples related to high-value drug development questions and decisions impacting target identification, lead generation and optimization, first in human studies, and clinical dose and schedule optimization are covered in the chapter. The future perspectives of QSP in the context of potential regulatory acceptance are also discussed.
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http://dx.doi.org/10.1007/978-1-0716-2265-0_5 | DOI Listing |