ArticleThe AAPS journal2019
TCPro: an In Silico Risk Assessment Tool for Biotherapeutic Protein Immunogenicity.
Article in The AAPS journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- T-Cell Dependent Immunogenicity of Protein Therapeutics Pre-clinical Assessment and Mitigation-Updated Consensus and Review 2020.Frontiers in immunology · 2020Pooled it
- T cell assays for non-clinical immunogenicity risk assessment: best practices recommended by the European Immunogenicity Platform.Frontiers in immunology · 2025Review
- Elucidation of B-cell specific drug immunogenicity liabilities via a novelFrontiers in immunology · 2025Article
- Immunogenicity risk assessment and mitigation for engineered antibody and protein therapeutics.Nature reviews. Drug discovery · 2024Review
- Individual and population-level variability in HLA-DR associated immunogenicity risk of biologics used for the treatment of rheumatoid arthritis.Frontiers in immunology · 2024Article
- QSP Designer: Quantitative systems pharmacology modeling with modular biological process map notation and multiple language code generation.CPT: pharmacometrics & systems pharmacology · 2023Article
- Learn-confirm in model-informed drug development: Assessing an immunogenicity quantitative systems pharmacology platform.CPT: pharmacometrics & systems pharmacology · 2023Article
- Mathematical model of a personalized neoantigen cancer vaccine and the human immune system.PLoS computational biology · 2021Article
- Trastuzumab immunogenicity development in patients' sera and in laboratory animals.BMC immunology · 2021Article
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Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most immune responses to biotherapeutic proteins involve the development of anti-drug antibodies (ADAs). New drugs must undergo immunogenicity assessments to identify potential risks at early stages in the drug development process. This immune response is T cell-dependent. Ex vivo assays that monitor T cell proliferation often are used to assess immunogenicity risk. Such assays can be expensive and time-consuming to carry out. Furthermore, T cell proliferation requires presentation of the immunogenic epitope by major histocompatibility complex class II (MHCII) proteins on antigen-presenting cells. The MHC proteins are the most diverse in the human genome. Thus, obtaining cells from subjects that reflect the distribution of the different MHCII proteins in the human population can be challenging. The allelic frequencies of MHCII proteins differ among subpopulations, and understanding the potential immunogenicity risks would thus require generation of datasets for specific subpopulations involving complex subject recruitment. We developed TCPro, a computational tool that predicts the temporal dynamics of T cell counts in common ex vivo assays for drug immunogenicity. Using TCPro, we can test virtual pools of subjects based on MHCII frequencies and estimate immunogenicity risks for different populations. It also provides rapid and inexpensive initial screens for new biotherapeutics and can be used to determine the potential immunogenicity risk of new sequences introduced while bioengineering proteins. We validated TCPro using an experimental immunogenicity dataset, making predictions on the population-based immunogenicity risk of 15 protein-based biotherapeutics. Immunogenicity rankings generated using TCPro are consistent with the reported clinical experience with these therapeutics.
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Registered trials
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