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通过设计降低免疫原性:降低单克隆抗体免疫原性的方法。

Reducing Immunogenicity by Design: Approaches to Minimize Immunogenicity of Monoclonal Antibodies.

机构信息

Department of BioAnalytical Sciences, Genentech Inc., South San Francisco, CA, 94080-4990, USA.

出版信息

BioDrugs. 2024 Mar;38(2):205-226. doi: 10.1007/s40259-023-00641-2. Epub 2024 Jan 23.


DOI:10.1007/s40259-023-00641-2
PMID:38261155
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10912315/
Abstract

Monoclonal antibodies (mAbs) have transformed therapeutic strategies for various diseases. Their high specificity to target antigens makes them ideal therapeutic agents for certain diseases. However, a challenge to their application in clinical practice is their potential risk to induce unwanted immune response, termed immunogenicity. This challenge drives the continued efforts to deimmunize these protein therapeutics while maintaining their pharmacokinetic properties and therapeutic efficacy. Because mAbs hold a central position in therapeutic strategies against an array of diseases, the importance of conducting comprehensive immunogenicity risk assessment during the drug development process cannot be overstated. Such assessment necessitates the employment of in silico, in vitro, and in vivo strategies to evaluate the immunogenicity risk of mAbs. Understanding the intricacies of the mechanisms that drive mAb immunogenicity is crucial to improving their therapeutic efficacy and safety and developing the most effective strategies to determine and mitigate their immunogenic risk. This review highlights recent advances in immunogenicity prediction strategies, with a focus on protein engineering strategies used throughout development to reduce immunogenicity.

摘要

单克隆抗体(mAbs)已经改变了各种疾病的治疗策略。它们对靶抗原的高特异性使它们成为某些疾病的理想治疗药物。然而,它们在临床实践中的应用面临一个挑战,即它们可能会引起不必要的免疫反应,称为免疫原性。为了克服这一挑战,人们一直在努力使这些蛋白质治疗药物脱免疫,同时保持其药代动力学特性和治疗效果。由于 mAbs 在针对一系列疾病的治疗策略中占据核心地位,因此在药物开发过程中进行全面的免疫原性风险评估的重要性怎么强调都不为过。这种评估需要采用计算、体外和体内策略来评估 mAbs 的免疫原性风险。了解驱动 mAb 免疫原性的机制的复杂性对于提高其治疗效果和安全性以及制定最有效的策略来确定和减轻其免疫风险至关重要。本文重点介绍了免疫原性预测策略的最新进展,以及在整个开发过程中用于降低免疫原性的蛋白质工程策略。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/f3bb941fa4c0/40259_2023_641_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/9cd52a69f002/40259_2023_641_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/18175fd46340/40259_2023_641_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/c2e6592b9e63/40259_2023_641_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/f3bb941fa4c0/40259_2023_641_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/9cd52a69f002/40259_2023_641_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/18175fd46340/40259_2023_641_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/c2e6592b9e63/40259_2023_641_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e50d/10912315/f3bb941fa4c0/40259_2023_641_Fig4_HTML.jpg

相似文献

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Reducing Immunogenicity by Design: Approaches to Minimize Immunogenicity of Monoclonal Antibodies.

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[2]
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[3]
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[4]
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[5]
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[6]
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[7]
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[8]
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[9]
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[10]
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本文引用的文献

[1]
Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity.

Brief Bioinform. 2024-3-27

[2]
Survey Outcome on Immunogenicity Risk Assessment Tools for Biotherapeutics: an Insight into Consensus on Methods, Application, and Utility in Drug Development.

AAPS J. 2023-6-2

[3]
ImmuneBuilder: Deep-Learning models for predicting the structures of immune proteins.

Commun Biol. 2023-5-29

[4]
Fast, accurate antibody structure prediction from deep learning on massive set of natural antibodies.

Nat Commun. 2023-4-25

[5]
Machine learning reveals limited contribution of trans-only encoded variants to the HLA-DQ immunopeptidome.

Commun Biol. 2023-4-21

[6]
A root cause analysis to identify the mechanistic drivers of immunogenicity against the anti-VEGF biotherapeutic brolucizumab.

Sci Transl Med. 2023-2

[7]
Anti-brolucizumab immune response as one prerequisite for rare retinal vasculitis/retinal vascular occlusion adverse events.

Sci Transl Med. 2023-2

[8]
Validation of a Dendritic Cell and CD4+ T Cell Restimulation Assay Contributing to the Immunogenicity Risk Evaluation of Biotherapeutics.

Pharmaceutics. 2022-12-1

[9]
Biopharmaceutical benchmarks 2022.

Nat Biotechnol. 2022-12

[10]
Methods for addressing host cell protein impurities in biopharmaceutical product development.

Biotechnol J. 2023-3

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