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◆ Frontiers in Immunology2025-10-10· Immunogenicity

MAPPs assays for non-clinical immunogenicity risk assessment: best practices recommended by the European immunogenicity platform

Anette Karle, Karla Kopp, Robert Seward, Sophie Tourdot, Chloé Ackaert, Michael Gutknecht, Edward A. Cloake, Noel Smith, Axel Ducret

原始摘要(英文原文)· Original abstract
The use of the MAPPs (Major histocompatibility complex Associated Peptide Proteomics) assay by pharmaceutical companies, service providers, and academic laboratories is rapidly increasing, attesting to its increasingly pivotal role in biotherapeutic drug candidate design, selection, and mechanistic investigations. Implementation of the MAPPs assay is labor-intensive, necessitating a high level of expertise. Differences observed in protocols established by laboratories may lead to considerable variability in data quality, limiting inter-laboratory comparisons. To address these challenges, the Non-Clinical Immunogenicity Risk Assessment working group (NCIRA) of the European Immunogenicity Platform (EIP) sought to provide comprehensive recommendations for establishing robust workflows that will ensure robust data and meaningful interpretation. Recognizing the improbability of the complete harmonization of protocols, we aimed to define and propose a set of best practices to maximize confidence in the data generated by laboratories. The work presented here reviews the pitfalls and limitations of the assay, proposes strategies to enhance assay sensitivity and robustness, and outlines approaches for data analysis, reporting, and interpretation. Additionally, the potential of the MAPPs assay for future applications such as clinical studies is discussed. By proposing measures and controls that support the development of high-quality MAPPs assays, we seek to improve their reproducibility and reliability for drug candidates' nonclinical immunogenicity risk evaluation.
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MAPPs assays for non-clinical immunogenicity risk assessment: best practices recommended by the European immunogenicity platform — 科研速览 Science Skim