Open AccessEvaluating high‐throughput scale‐down chromatography platforms for increased process understanding
Author(s) -
Feliciano Jessika,
Berrill Alex,
Ahnfelt Mattias,
Brekkan Eggert,
Evans Brad,
Fung Ziawei,
Godavarti Ranga,
NilssonVälimaa Kristina,
Salm Jeff,
Saplakoglu Umay,
Switzer Mary,
Łącki Karol
Publication year - 2016
Publication title -
engineering in life sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.547
H-Index - 57
eISSN - 1618-2863
pISSN - 1618-0240
DOI - 10.1002/elsc.201400241
Subject(s) - throughput , process engineering , process (computing) , quality by design , yield (engineering) , computer science , process analytical technology , filter (signal processing) , chromatography , process development , materials science , chemistry , work in process , engineering , chemical engineering , operations management , particle size , computer vision , metallurgy , wireless , operating system , telecommunications
In the biopharmaceutical industry, well‐executed process development and characterization studies ensure robust manufacturing processes. In conventional chromatography, these studies are carried out in series with ≥10 mL bed volumes, thus requiring large quantities of feed material and operator oversight. For that reason, the screening of large process spaces becomes very expensive and has the potential to negatively impact other projects in a company's portfolio competing for similar resources. In this study, we evaluated the ability of the three high‐throughput process development formats 96‐well filter plates, pipette tips, and mini columns to reduce resources in a late‐phase process characterization Protein A capture step. The study used a Protein A capture step with a single experimental design, mAb feed material, and analytical package. The evaluation was based on how identical batch and dynamic process parameters impacted the quality and process performance attributes of monomer purity, host cell protein levels, and yield. All formats were able to provide similar models for product yield and monomer purity. Except for practical limitations of PreDictor plates, all formats could identify significant factors for host cell protein levels. RoboColumn units enabled dynamic factor evaluation and the results were the most comparable to conventional chromatography.