Machine learning optimized autoimmune therapeutics with a focus on Type 1 Diabetes

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Principal Investigator: David K Gifford
Organization: THINK THERAPEUTICS, INC.
Fiscal Year: 2024
Award: $306,500
Funding agency: National Institute of Allergy and Infectious Diseases

Project Summary
We propose to develop a new immunogenicity assay and machine learning based
framework for creating tolerization vaccines for autoimmune diseases with improved
population coverage. In collaboration with Harvard University and the University of
Massachusetts Chan Medical School Diabetes Center of Excellence we will develop a
new assay, the Multiplexed Multi-antigen Activation Assay (MMAA), to discover self-
antigens that are recognized by cytotoxic T cells in Type 1 Diabetes (T1D) (Aim 1). We
will use the self-antigens we have confirmed to design novel multi-epitope tolerization
vaccines and test the vaccines for their ability to expand CD4+ TReg cells in PBMCs from
T1D donors (Aim 2). We will utilize new machine learning methods to modify and select
vaccine epitopes to substantially improve tolerization vaccine population coverage. Our
products will be the resulting vaccines.

Terms: <Admission><Admission activity><Alleles><Allelomorphs><Amino Acid Sequence><Antigenic Determinants><Antigens><Assay><Autoantigens><Autoimmune><Autoimmune Diseases><Autoimmune Status><Autoimmunity><Autologous Antigens><Binding Determinants><Bioassay><Biological Assay><Brittle Diabetes Mellitus><Businesses><CD4 Cells><CD4 Positive T Lymphocytes><CD4 T cells><CD4 helper T cell><CD4 lymphocyte><CD4+ T-Lymphocyte><CD4-Positive Lymphocytes><CD8><CD8 Cell><CD8 T cells><CD8 lymphocyte><CD8+ T cell><CD8+ T-Lymphocyte><CD8-Positive Lymphocytes><CD8-Positive T-Lymphocytes><CD8B><CD8B1><CD8B1 gene><Cell Body><Cell Communication and Signaling><Cell Function><Cell Physiology><Cell Process><Cell Signaling><Cell surface><Cell-Mediated Lympholytic Cells><Cells><Cellular Function><Cellular Physiology><Cellular Process><Class I Genes><Class II Genes><Code><Coding System><Collaborations><Computing Methodologies><Cytolytic T-Cell><Cytotoxic T Cell><Cytotoxic T-Lymphocytes><Data><Data Bases><Databases><Derivation><Derivation procedure><Diabetes Mellitus><Epitopes><FOXP3><FOXP3 gene><Forkhead Box P3><Foundations><Frequencies><HLA Class II Genes><HLA-A><HLA-A gene><HLAA><Haplotypes><High Throughput Assay><Human><IDDM><Immune><Immune Surveillance><Immune system><Immunes><Immunologic Surveillance><Immunologic Surveillances><Immunological Surveillance><Immunological Surveillances><Immunosurveillance><Individual><Insulin-Dependent Diabetes Mellitus><Intracellular Communication and Signaling><JM2><Juvenile-Onset Diabetes Mellitus><K Cells><Ketosis-Prone Diabetes Mellitus><Killer Cells><LYT3><Legal patent><Letters><Literature><Lymphatic cell><Lymphocyte><Lymphocytic><MHC Class I><MHC Class I Genes><MHC Class II><MHC Class II Genes><MHC Receptor><Machine Learning><Major Histocompatibility Complex Receptor><Mass Photometry/Spectrum Analysis><Mass Spectrometry><Mass Spectroscopy><Mass Spectrum><Mass Spectrum Analyses><Mass Spectrum Analysis><Massachusetts><Methods><Modern Man><Normal Cell><PBMC><Patents><Peptide-MHC><Peptide-Major Histocompatibility Protein Complex><Peptide/MHC Complex><Peptides><Peripheral Blood Mononuclear Cell><Persons><Population><Primary Protein Structure><Proteins><Receptor Protein><Recovery><Regulatory T-Lymphocyte><Research><SCURFIN><Sampling><Self-Antigens><Signal Transduction><Signal Transduction Systems><Signaling><Subcellular Process><Sudden-Onset Diabetes Mellitus><Symptoms><T-Cell Activation><T-Cell Antigen Receptors><T-Cell Receptor><T-Cells><T-Lymphocyte><T-cell receptor repertoire><T1 DM><T1 diabetes><T1D><T1DM><T4 Cells><T4 Lymphocytes><T8 Cells><T8 Lymphocytes><TCR repertoire><Testing><Therapeutic><Treg><Type 1 Diabetes Mellitus><Type 1 diabetes><Type I Diabetes Mellitus><Universities><Vaccine Design><Vaccines><Work><activate T cells><antigen based test><antigen test><autoimmune condition><autoimmune disorder><autoimmunity disease><biological signal transduction><computational methodology><computational methods><computer based method><computer methods><computing method><cross reactivity><data base><design><designing><diabetes><evaluate vaccines><high throughput screening><immunogen><immunogenicity><improved><insulin dependent diabetes><insulin dependent type 1><juvenile diabetes><juvenile diabetes mellitus><ketosis prone diabetes><killer T cell><lymph cell><mRNA lipid nano particle vaccine><mRNA-LNP based vaccine><mRNA-LNP combination vaccines><mRNA-LNP vaccines><machine based learning><machine learning based framework><machine learning based method><machine learning framework><machine learning method><machine learning methodologies><medical college><medical schools><novel><outcome following vaccination><outcome following vaccine><pMHC><pre-proinsulin><preproinsulin><prevent><preventing><protein sequence><receptor><receptor binding><receptor bound><regulatory T-cells><response><result following vaccination><result following vaccine><school of medicine><thymus derived lymphocyte><type I diabetes><type one diabetes><vaccination outcome><vaccination result><vaccine evaluation><vaccine outcome><vaccine result><vaccine screening><vaccine testing>