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Host cell proteins in monoclonal antibody processing: Control, detection, and removal. | LitMetric

Host cell proteins in monoclonal antibody processing: Control, detection, and removal.

Biotechnol Prog

Life Science, Process Solutions, Merck Life Sciences Pvt. Ltd. (An Affiliate of Merck KGaA, Darmstadt, Germany), Bangalore, India.

Published: August 2024

AI Article Synopsis

  • Host cell proteins (HCPs) are unwanted impurities that can affect the quality of therapeutic proteins produced through cell culture, particularly in monoclonal antibody (mAb) production.
  • The review analyzes industry trends, technologies for removing HCPs, and evaluates data to understand their impact on manufacturing and therapeutic quality.
  • It highlights that while higher cell density cultures lead to increased HCP levels, effective operations can reduce HCP concentrations to around 10 ppm, with no notable performance differences between modern and traditional manufacturing processes.

Article Abstract

Host cell proteins (HCPs) are process-related impurities in a therapeutic protein expressed using cell culture technology. This review presents biopharmaceutical industry trends in terms of both HCPs in the bioprocessing of monoclonal antibodies (mAbs) and the capabilities for HCP clearance by downstream unit operations. A comprehensive assessment of currently implemented and emerging technologies in the manufacturing processes with extensive references was performed. Meta-analyses of published downstream data were conducted to identify trends. Improved analytical methods and understanding of "high-risk" HCPs lead to more robust manufacturing processes and higher-quality therapeutics. The trend of higher cell density cultures leads to both higher mAb expression and higher HCP levels. However, HCP levels can be significantly reduced with improvements in operations, resulting in similar concentrations of approx. 10 ppm HCPs. There are no differences in the performance of HCP clearance between recent enhanced downstream operations and traditional batch processing. This review includes best practices for developing improved processes.

Download full-text PDF

Source
http://dx.doi.org/10.1002/btpr.3448DOI Listing

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