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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Continuous manufacturing platforms and membrane chromatography are process technologies with the potential to reduce production costs and minimize process variability in monoclonal antibody production. This study presents a simulation and optimization framework to perform techno-economic analyses of these strategies. Multi-objective optimization was used to compare batch and continuous multicolumn operating modes and membrane and resin process alternatives, revealing performance differences in productivity and cost of goods attributed to variations in dynamic binding capacity, media geometry, and process residence time. From the set of optimal process configurations, we selected one membrane and one resin platform alternative yielding the highest net present values to undergo sensitivity analyses involving variations in batch cadence and product selling price. For the scenarios considered in this work, membrane continuous platforms showed benefits in the cost of goods and process mass intensity. Their shorter residence time compared to resins positions them as a viable alternative for single-use capture chromatography. Moreover, this low residence time makes membrane platforms more flexible to changes in throughput, an essential feature for integrating capture into fully continuous processes.
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Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12353975 | PMC |
http://dx.doi.org/10.1002/btpr.70033 | DOI Listing |