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  • 1
    Online Resource
    Online Resource
    The promise of machine learning: using Seismic’s IMPACT platform to design IgG cleaving enzymes for chronic treatment of autoimmune diseases
    The American Association of Immunologists ; 2023
    In:  The Journal of Immunology Vol. 210, No. 1_Supplement ( 2023-05-01), p. 238.22-238.22
    Details
    In: The Journal of Immunology, The American Association of Immunologists, Vol. 210, No. 1_Supplement ( 2023-05-01), p. 238.22-238.22
    Abstract: Proteases derived from human pathogens can specifically cleave IgG into F(ab′)2 and Fc fragments. This unique trait suggests a novel opportunity to use these molecules to treat auto antibody mediated disease. IdeS, an IgG cleaving enzyme derived from Streptococcus pyogenes has shown clinical proof of concept and is approved for use before kidney transplant. Due to the immunogenic nature of these proteases, the dosing regimen is impacted by pre-existing antibodies and the induction of anti-drug antibodies after dosing. To mitigate the impact of the immune system on our novel enzyme, we employed our IMPACT platform leveraging machine learning to reduce T and B cell epitopes and to ensure that our molecule exhibits desirable drug like properties while maintaining enzymatic activity. To extend the pharmacokinetics (PK) of our molecule, we fused it with a Fc domain. To evaluate IgG protease PK and pharmacodynamics (PD), intravenous immunoglobulin (IVIg) was injected at different time points after protease treatment and IgG levels were quantified by MSD. As expected, the addition of the Fc increased the molecule’s half-life that resulted in a PD effect at later time points than observed with a control enzyme without a Fc. Taken together, our IMPACT platform leveraging machine learning demonstrates that we can optimize drug-like properties and reduce the immunogenicity of a molecule while maintaining function, resulting in a potential novel treatment for chronic autoimmune diseases.
    Type of Medium: Online Resource
    ISSN: 0022-1767 , 1550-6606
    URL: Article
    DOI: 10.4049/jimmunol.210.Supp.238_22
    RVK:
    XA 54100
    RVK:
    XA 10000
    Language: English
    Publisher: The American Association of Immunologists
    Publication Date: 2023
    detail.hit.zdb_id: 1475085-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 2
    Online Resource
    Online Resource
    The promise of machine learning: using Seismic’s IMPACT platform to design IgG cleaving enzymes for chronic treatment of autoimmune diseases
    The American Association of Immunologists ; 2023
    In:  The Journal of Immunology Vol. 210, No. 1_Supplement ( 2023-05-01), p. 85.13-85.13
    Details
    In: The Journal of Immunology, The American Association of Immunologists, Vol. 210, No. 1_Supplement ( 2023-05-01), p. 85.13-85.13
    Abstract: Proteases derived from human pathogens can specifically cleave IgG into F(ab′)2 and Fc fragments. This unique trait suggests a novel opportunity to use these molecules to treat auto antibody mediated disease. IdeS, an IgG cleaving enzyme derived from Streptococcus pyogenes has shown clinical proof of concept and is approved for use before kidney transplant. Due to the immunogenic nature of these proteases, the dosing regimen is impacted by pre-existing antibodies and the induction of anti-drug antibodies after dosing. To mitigate the impact of the immune system on our novel enzyme, we employed our IMPACT platform leveraging machine learning to reduce T and B cell epitopes and to ensure that our molecule exhibits desirable drug like properties while maintaining enzymatic activity. To extend the pharmacokinetics (PK) of our molecule, we fused it with a Fc domain. To evaluate IgG protease PK and pharmacodynamics (PD), intravenous immunoglobulin (IVIg) was injected at different time points after protease treatment and IgG levels were quantified by MSD. As expected, the addition of the Fc increased the molecule’s half-life that resulted in a PD effect at later time points than observed with a control enzyme without a Fc. Taken together, our IMPACT platform leveraging machine learning demonstrates that we can optimize drug-like properties and reduce the immunogenicity of a molecule while maintaining function, resulting in a potential novel treatment for chronic autoimmune diseases.
    Type of Medium: Online Resource
    ISSN: 0022-1767 , 1550-6606
    URL: Article
    DOI: 10.4049/jimmunol.210.Supp.85.13
    RVK:
    XA 54100
    RVK:
    XA 10000
    Language: English
    Publisher: The American Association of Immunologists
    Publication Date: 2023
    detail.hit.zdb_id: 1475085-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 3
    Online Resource
    Online Resource
    In vivo PK/PD assessment of invisibilized IgG cleaving protease for chronic treatment of autoimmune diseases
    The American Association of Immunologists ; 2023
    In:  The Journal of Immunology Vol. 210, No. 1_Supplement ( 2023-05-01), p. 238.16-238.16
    Details
    In: The Journal of Immunology, The American Association of Immunologists, Vol. 210, No. 1_Supplement ( 2023-05-01), p. 238.16-238.16
    Abstract: Pathogenic autoantibodies are key effectors of inflammation, promoting complement cascade activation, immune cell response, and the consequent tissue damage in autoimmune disease and transplant rejection. Proteases that cleave IgG antibodies present a novel therapeutic opportunity to treat autoimmune diseases and antibody mediated transplant rejection. Using our IMPACT platform leveraging machine learning, we engineered IgG proteases with reduced immunogenicity for acute and chronic treatment of antibody-mediated diseases. In addition, the invisibilized protease was fused to a Fc to extend its half-life. To evaluate these IgG proteases in vivowe developed a pharmacokinetics and pharmacodynamics (PK/PD) model. C57BL6 mice were dosed with intravenous immunoglobulin (IVIg) at different time points after protease treatment. Protease and IgG levels were quantified by MSD 15 minutes before and two hours after IVIg injection, respectively. IgG cleavage was detected at early time points which correlated with higher systemic drug levels. Additionally, the Fc-fused protease was detected at later time points with increased systemic enzymatic activity, as compared to the enzyme domain only. Finally, we evaluated the potential of the Fc-protease to cleave antigen bound IgG at the tissue level in a mouse anti–glomerular basement membrane (GBM) induced nephritis model. In summary, our in vivo studies established a PK/PD relationship between exposure and cleaved IgG while showing the benefit of fusing the protease domain to a Fc.
    Type of Medium: Online Resource
    ISSN: 0022-1767 , 1550-6606
    URL: Article
    DOI: 10.4049/jimmunol.210.Supp.238.16
    RVK:
    XA 54100
    RVK:
    XA 10000
    Language: English
    Publisher: The American Association of Immunologists
    Publication Date: 2023
    detail.hit.zdb_id: 1475085-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
  • 4
    Online Resource
    Online Resource
    In vitro assay development to assess successful removal of T and B cell epitopes through Seismic’s IMPACT platform
    The American Association of Immunologists ; 2023
    In:  The Journal of Immunology Vol. 210, No. 1_Supplement ( 2023-05-01), p. 85.16-85.16
    Details
    In: The Journal of Immunology, The American Association of Immunologists, Vol. 210, No. 1_Supplement ( 2023-05-01), p. 85.16-85.16
    Abstract: Proteases derived from human pathogens can specifically cleave IgG into F(ab’)2 and Fc fragments. IdeS, an IgG cleaving enzyme derived from Streptococcus pyogenes, has shown clinical proof of concept, and is approved for use before kidney transplantation. Due to the immunogenic nature of these proteases, dosing is limited by high prevalence of pre-existing antibodies and the induction of anti-drug antibodies after dosing. Therefore, to mitigate the impact of the immune system on our enzyme, we identify and remove putative T and B cell epitopes using Seismic’s IMPACT platform leveraging machine learning. To experimentally validate in silicopredictions, we developed two complementary in vitroassays using intravenous immunoglobulin (IVIg) to assess removal of B cell epitopes. First, we assess how mutating the wild type (WT) protease sequence impacts pre-existing antibodies in a competitive binding assay followed by evaluating global binding of pre-existing antibodies to our protease. Additionally, we developed an in vitroPBMC proliferation assay to determine the success of T cell epitope removal. Using flow cytometry, we quantitively assess CD4 proliferation via bromodeoxyuridine (BrdU) incorporation. We demonstrate examples of molecules designed through our IMPACT platform to reduce both T and B cell epitopes. The B cell epitope assays show a decrease in competition as compared to the WT protease while achieving a reduction in IVIg binding. These data suggest that these in vitroassays can be used to screen for successful invisibilization of molecules of interest.
    Type of Medium: Online Resource
    ISSN: 0022-1767 , 1550-6606
    URL: Article
    DOI: 10.4049/jimmunol.210.Supp.85.16
    RVK:
    XA 54100
    RVK:
    XA 10000
    Language: English
    Publisher: The American Association of Immunologists
    Publication Date: 2023
    detail.hit.zdb_id: 1475085-5
    Location Call Number Limitation Availability
    BibTip Others were also interested in ...
    Online Resource
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