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During expression of biotherapeutic proteins, complex mixtures of additional proteins are also produced by normal expression machinery of the host cell (termed "host cell proteins," or HCP). HCPs pose a potential impact to patient safety and product efficacy, and therefore must be well-characterized and the ability of the process to clear these proteins must be demonstrated. Due to the complexity of HCP, the method(s) used for monitoring must be demonstrated to provide sufficient information about relevant proteins. The most commonly used analytical method for monitoring HCP is an enzyme-linked immunosorbent assay (ELISA). To ensure development of a suitable HCP ELISA, careful selection of critical reagents (anti-HCP antibodies and analytical standard) is crucial. During a recent major update to the manufacturing process of a biotherapeutic, we re-evaluated the suitability of the existing HCP ELISA for monitoring the HCP population in the updated process. In the evaluation, we compared a process-specific ELISA to a platform ELISA. Despite qualitative differences in the HCP profiles in 2D PAGE, LC-MS/MS showed that the HCP populations in the two analytical standards were similar. The process-specific HCP antibody had adequate HCP coverage, but was more sensitive to a few dominant proteins that were present in the upstream purification process. The platform HCP antibody had very broad coverage and additionally, could detect the majority of potential HCP impurities from this process. Furthermore, the platform HCP antibody was not biased toward a few dominant proteins and was more sensitive in the downstream purification process. Due to its broad HCP coverage and sensitivity, we conclude that our platform HCP ELISA method is superior to the process-specific HCP ELISA method. © 2017 Wiley Periodicals, Inc.

Citation

Feny Gunawan, Julie Nishihara, Peter Liu, Wendy Sandoval, Marty Vanderlaan, Heidi Zhang, Denise Krawitz. Comparison of platform host cell protein ELISA to process-specific host cell protein ELISA. Biotechnology and bioengineering. 2017 Oct 07


PMID: 28986978

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