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Rwanda Medical Journal
Rwanda Health Communication Center - Rwanda Biomedical Center (RHCC - RBC)
ISSN: 2079-097X
EISSN: 2079-097X
Vol. 71, No. 1, 2014, pp. 15-20
Bioline Code: rw14003
Full paper language: English
Document type: Research Article
Document available free of charge

Rwanda Medical Journal, Vol. 71, No. 1, 2014, pp. 15-20

Musanabaganwa, C. & Byiringiro, F.


Immunogenicity testing is a vital component of drug development as it leads to drugs that are safer and more effective. This review provides an overview of the pre-clinical models that can be used to predict the immunogenic potential of novel protein therapeutics prior to administration in humans. Tools important for the prediction of the immunogenicity of protein therapeutics include animal models, in vitro cell assays, and in silico techniques. Animal models including rodents, transgenic mice, and non-human primates are reviewed. Among the immunoinformatics tools commonly used to predict immunogenicity include the Structural Epitope Database, Immune Epitope Database and Analysis Resource (IEDB), The MHCBN database, Dana-Farber Repository for Machine Learning in Immunology, and TEPITOPE. Identifiation and subsequent removal or inhibition of epitopes and MHC agretopes minimizes immunogenicity. Strategies for minimization of immunogenicity in biotherapeutics including epitope and MHC agretope removal, improvement of solubility, derivatization with polyethylene glycol (PEG), and use of chimeric antibodies are also discussed. Immunogenicity testing is an important part of the drug development process as it leads to drugs that are safer and more effective. Animal models including rodents, transgenic mice, and non-human primates; in vitro cell assays; and immunoinformatics tools are used to identify epitopes and MHC agretopes which are then eliminated or inhibited so as to minimize immunogenicity.

immunogenicity; immunogenicity testing; biotherapeutics; animal models; immunoinformatics

Musanabaganwa, C. & Byiringiro, F.


Les tests d’immunogenicité sont des facteurs majeur dans le développement des médicaments en vue d’élaborer molécules plus sures et plus spécifiues. Cetteétude dispose d’une analyse globale des modelésprécliniques qui prévoient un pouvoir immunogenique des nouvelles moléculesthérapeutiquesavant leur utilisation sur l’homme. Les éléments essentiels dans la prédiction de cet immunogenicité des molécules thérapeutiques sont les cobayes utilisés tels que les animaux (in vivo), l’échantillonnage de cellules (in vitro), et d’autres techniques utilisées in silico. Les modèles des cobayes utilisés (les rongeurs, les souris transgéniques, et les primates) sont revus et analysés. Les outils informatiques les plus utilisés dans l’immunogenicité sont les " Structural EpitopeDatabase", "Immune EpitopeDatabase and Analysis Resource (IEDB)", "MHCBN database, Dana-FarberRepository for Machine Learning in Immunology", et le "TEPITOPE". L’identifiation suivie de la suppression ou le blocage des épitopes et des agretopes MHC diminuent le risque immunogène. Cette étude discute des stratégies de réduction du pouvoir immunogenique utilisées en biothérapie qui sont entreautre la suppression des epitopes et les agretopes MHC, l’amélioration de la solubilité, la production des nouvelles molécules thérapeutiques à partir du polyethylene glycol (PEGylation), et l’utilisation des anticorps chimériques.

Mots Clés
Immunogenicité; tests d’immunogenicité; Biotherapie; Cobayes; Immunoinformatique

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