A quality evaluation strategy for residual host cell proteins based on orthogonal analysis

Area of Science:

• Biopharmaceutical Quality Control
• Analytical Chemistry
• Immunotechnology

Background:

• Accurate quantification of host cell proteins (HCPs) is critical for biopharmaceutical safety and quality.
• Current enzyme-linked immunosorbent assay (ELISA) kits exhibit method-dependent bias due to antibody repertoire heterogeneity.

Purpose of the Study:

• To develop a novel strategy for evaluating the quality of HCP detection kits for biologics.
• To functionally compare nine mainstream commercial HCP ELISA kits using Chinese hamster ovary (CHO) cell-derived samples.

Main Methods:

• Introduction of an "adjacent dilution-gradient back-calculation recovery" metric to assess dilution linearity, sensitivity, and matrix interference resistance.
• Implementation of an unsupervised machine learning workflow (hierarchical clustering analysis) for objective kit stratification based on a 10-dimensional functional feature matrix.
• Orthogonal evaluation using IMBS-MS/MS for antibody coverage analysis.

Main Results:

• Significant functional stratification was observed among the nine evaluated kits.
• Kit A demonstrated superior analytical performance, maintaining 80%-120% recovery across 16- to 128-fold dilutions, overcoming hook effects and false-negative risks.
• While kits A and I showed >80% antibody coverage, only Kit A exhibited concordance between high coverage and superior functional performance.

Conclusions:

• High antibody coverage is necessary but insufficient for reliable ELISA performance in HCP quantification.
• An orthogonal evaluation framework combining functional verification (especially dilution linearity) and HCP coverage analysis is recommended for robust impurity monitoring.
• This approach ensures scientifically sound and compliant quality control for biopharmaceuticals.