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

A survey conducted by the Therapeutic Product Immunogenicity (TPI) community within the American Association of Pharmaceutical Scientists (AAPS) posed questions to the participants on their immunogenicity risk assessment strategies prior to clinical development. The survey was conducted in 2 phases spanning 5 years, and queried information about in silico algorithms and in vitro assay formats for immunogenicity risk assessments and how the data were used to inform early developability effort in discovery, chemistry, manufacturing and control (CMC), and non-clinical stages of development. The key findings representing the trends from a majority of the participants included the use of high throughput in silico algorithms, human immune cell-based assays, and proteomics based outputs, as well as specialized assays when therapeutic mechanism of action could impact risk assessment. Additional insights into the CMC-related risks could also be gathered with the same tools to inform future process development and de-risk critical quality attributes with uncertain and unknown risks. The use of the outputs beyond supporting early development activities was also noted with participants utilizing the risk assessments to drive their clinical strategy and streamline bioanalysis.

T cell immunity ameliorates COVID-19 disease severity and provides post-exposure prophylaxis after peptide-vaccination, in Syrian hamsters.

Background: The emergence of novel SARS-CoV-2 variants that resist neutralizing antibodies drew the attention to cellular immunity and calls for the development of alternative vaccination strategies to combat the pandemic. Here, we have assessed the kinetics of T cell responses and protective efficacy against severe COVID-19 in pre- and post-exposure settings, elicited by PolyPEPI-SCoV-2, a peptide based T cell vaccine. Methods: 75 Syrian hamsters were immunized subcutaneously with PolyPEPI-SCoV-2 on D0 and D14. On D42, hamsters were intranasally challenged with 102 TCID50 of the virus. To analyze immunogenicity by IFN-γ ELISPOT and antibody secretion, lymphoid tissues were collected both before (D0, D14, D28, D42) and after challenge (D44, D46, D49). To measure vaccine efficacy, lung tissue, throat swabs and nasal turbinate samples were assessed for viral load and histopathological changes. Further, body weight was monitored on D0, D28, D42 and every day after challenge. Results: The vaccine induced robust activation of T cells against all SARS-CoV-2 structural proteins that were rapidly boosted after virus challenge compared to control animals (~4-fold, p<0.05). A single dose of PolyPEPI-SCoV-2 administered one day after challenge also resulted in elevated T cell response (p<0.01). The vaccination did not induce virus-specific antibodies and viral load reduction. Still, peptide vaccination significantly reduced body weight loss (p<0.001), relative lung weight (p<0.05) and lung lesions (p<0.05), in both settings. Conclusion: Our study provides first proof of concept data on the contribution of T cell immunity on disease course and provide rationale for the use of T cell-based peptide vaccines against both novel SARS-CoV-2 variants and supports post-exposure prophylaxis as alternative vaccination strategy against COVID-19.

The mutational landscape of SARS-CoV-2 variants diversifies T cell targets in an HLA-supertype-dependent manner.

The rapid, global dispersion of SARS-CoV-2 has led to the emergence of a diverse range of variants. Here, we describe how the mutational landscape of SARS-CoV-2 has shaped HLA-restricted T cell immunity at the population level during the first year of the pandemic. We analyzed a total of 330,246 high-quality SARS-CoV-2 genome assemblies, sampled across 143 countries and all major continents from December 2019 to December 2020 before mass vaccination or the rise of the Delta variant. We observed that proline residues are preferentially removed from the proteome of prevalent mutants, leading to a predicted global loss of SARS-CoV-2 T cell epitopes in individuals expressing HLA-B alleles of the B7 supertype family; this is largely driven by a dominant C-to-U mutation type at the RNA level. These results indicate that B7-supertype-associated epitopes, including the most immunodominant ones, were more likely to escape CD8+ T cell immunosurveillance during the first year of the pandemic.

A Peptide Vaccine Candidate Tailored to Individuals' Genetics Mimics the Multi-Targeted T Cell Immunity of COVID-19 Convalescent Subjects.

Long-term immunity to coronaviruses likely stems from T cell activity. We present here a novel approach for the selection of immunoprevalent SARS-CoV-2-derived T cell epitopes using an in silico cohort of HLA-genotyped individuals with different ethnicities. Nine 30-mer peptides derived from the four major structural proteins of SARS-CoV-2 were selected and included in a peptide vaccine candidate to recapitulate the broad virus-specific T cell responses observed in natural infection. PolyPEPI-SCoV-2-specific, polyfunctional CD8+ and CD4+ T cells were detected in each of the 17 asymptomatic/mild COVID-19 convalescents' blood against on average seven different vaccine peptides. Furthermore, convalescents' complete HLA-genotype predicted their T cell responses to SARS-CoV-2-derived peptides with 84% accuracy. Computational extrapolation of this relationship to a cohort of 16,000 HLA-genotyped individuals with 16 different ethnicities suggest that PolyPEPI-SCoV-2 vaccination will likely elicit multi-antigenic T cell responses in 98% of individuals, independent of ethnicity. PolyPEPI-SCoV-2 administered with Montanide ISA 51 VG generated robust, Th1-biased CD8+, and CD4+ T cell responses against all represented proteins, as well as binding antibodies upon subcutaneous injection into BALB/c and hCD34+ transgenic mice modeling human immune system. These results have implications for the development of global, highly immunogenic, T cell-focused vaccines against various pathogens and diseases.

Immunopeptidomic Data Integration to Artificial Neural Networks Enhances Protein-Drug Immunogenicity Prediction.

Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adverse effects, including allergic reactions and compromised therapeutic efficacy. Production of ADAs is most often associated with activation of CD4 T cell responses resulting from proteolysis of the biotherapeutic and loading of drug-specific peptides into major histocompatibility complex (MHC) class II on professional antigen-presenting cells. Recently, readouts from MHC-associated peptide proteomics (MAPPs) assays have been shown to correlate with the presence of CD4 T cell epitopes. However, the limited sensitivity of MAPPs challenges its use as an immunogenicity biomarker. In this work, MAPPs data was used to construct an artificial neural network (ANN) model for MHC class II antigen presentation. Using Infliximab and Rituximab as showcase stories, the model demonstrated an unprecedented performance for predicting MAPPs and CD4 T cell epitopes in the context of protein-drug immunogenicity, complementing results from MAPPs assays and outperforming conventional prediction models trained on binding affinity data.