Versatile LC-MS-Based Workflow with Robust 0.1 ppm Sensitivity for Identifying Residual HCPs in Biotherapeutic

Feng Yang1, Delia Li1, Regina Kufer2

  • 1Protein Analytical Chemistry, Genentech, A Member of the Roche Group, 1 DNA Way, South San Francisco, California 94080, United States.

Analytical Chemistry
|December 20, 2021
PubMed

Insights

This study introduces a novel workflow for highly sensitive detection of residual host cell proteins (HCPs) in biotherapeutics. The method enhances HCP identification sensitivity by 10- to 100-fold, crucial for drug safety and quality control.

Area of Science:

  • Biopharmaceutical Analysis
  • Protein Chemistry
  • Analytical Chemistry

Background:

  • Residual host cell proteins (HCPs) in biotherapeutics can compromise product quality, stability, and safety.
  • Highly active hydrolytic enzymes, even at sub-ppm levels, pose a significant challenge for detection using conventional LC-MS/MS due to wide dynamic range differences with therapeutic proteins.

Purpose of the Study:

  • To develop a highly sensitive workflow for identifying and quantifying residual host cell proteins (HCPs) in biopharmaceutical products.
  • To improve the detection limits for challenging HCPs, particularly hydrolytic enzymes, at very low concentrations.
  • To enhance the demonstration of HCP clearance during drug process development.

Main Methods:

  • Implementation of a novel analytical workflow involving native digestion at high protein concentration and addition of sodium deoxycholate during reduction.
  • Utilized solid-phase extraction with 50% MeCN elution for effective monoclonal antibody (mAb) removal prior to analysis.
  • Employed a 50 cm nanoflow charged surface hybrid column to increase sample load capacity and enhance sensitivity for LC-MS/MS analysis.

Main Results:

  • Achieved a 10- to 100-fold increase in sensitivity for HCP identification compared to previous methods.
  • Demonstrated robust identification of HCPs as low as 0.1 ppm (34.5 to 66.2 kDa MW).
  • Successfully identified over 85% of 48 UPS-1 proteins (0.10 to 1.34 ppm) in a mAb and a record 746 mouse proteins from NIST mAb in a single analysis.

Conclusions:

  • The developed workflow significantly advances the capability for detecting and quantifying trace-level HCPs in biopharmaceuticals.
  • This method is crucial for ensuring drug product quality and safety by effectively identifying critical impurities like low-level hydrolases.
  • The enhanced sensitivity and robustness provide a valuable tool for demonstrating HCP clearance in biopharmaceutical process development.