Individual and population-level variability in HLA-DR associated immunogenicity risk of biologics used for the treatment of rheumatoid arthritis.

Hypothesis: While conventional in silico immunogenicity risk assessments focus on measuring immunogenicity based on the potential of therapeutic proteins to be processed and presented by a global population-wide set of human leukocyte antigen (HLA) alleles to T cells, future refinements might adjust for HLA allele frequencies in different geographic regions or populations, as well for as individuals in those populations. Adjustment by HLA allele distribution may reveal risk patterns that are specific to population groups or individuals, which current methods that rely on global-population HLA prevalence may obscure. Key findings: This analysis uses HLA frequency-weighted binding predictions to define immunogenicity risk for global and sub-global populations. A comparison of assessments tuned for North American/European versus Japanese/Asian populations suggests that the potential for anti-therapeutic responses (anti-therapeutic antibodies or ATA) for several commonly prescribed Rheumatoid Arthritis (RA) therapeutic biologics may differ, significantly, between the Caucasian and Japanese populations. This appears to align with reports of differing product-related immunogenicity that is observed in different populations. Relevance to clinical practice: Further definition of population-level (regional) and individual patient-specific immunogenic risk profiles may enable prescription of the RA therapeutic with the highest probability of success to each patient, depending on their population of origin and/or their individual HLA background. Furthermore, HLA-specific immunogenicity outcomes data are limited, thus there is a need to expand HLA-association studies that examine the relationship between HLA haplotype and ATA in the clinic.

In silico methods for immunogenicity risk assessment and human homology screening for therapeutic antibodies.

In silico immunogenicity risk assessment has been an important step in the development path for many biologic therapeutics, including monoclonal antibodies. Even if the source of a given biologic is 'fully human', T cell epitopes that are contained in the sequences of the biologic may activate the immune system, enabling the development of anti-drug antibodies that can reduce drug efficacy and may contribute to adverse events. Computational tools that identify T cell epitopes from primary amino acid sequences have been used to assess the immunogenic potential of therapeutic candidates for several decades. To facilitate larger scale analyses and accelerate preclinical immunogenicity risk assessment, our group developed an integrated web-based platform called ISPRI, (Immunogenicity Screening and Protein Re-engineering Interface) that provides hands-on access through a secure web-based interface for scientists working in large and mid-sized biotech companies in the US, Europe, and Japan. This toolkit has evolved and now contains an array of algorithms that can be used individually and/or consecutively for immunogenicity assessment and protein engineering. Most analyses start with the advanced epitope mapping tool (EpiMatrix), then proceed to identify epitope clusters using ClustiMer, and then use a tool called JanusMatrix to define whether any of the T cell epitope clusters may generate a regulatory T cell response which may diminish or eliminate anti-drug antibody formation. Candidates can be compared to similar products on a normalized immunogenicity scale. Should modifications to the biologic sequence be an option, a tool for moderating putative immunogenicity by editing T cell epitopes out of the sequence is available (OptiMatrix). Although this perspective discusses the in-silico immunogenicity risk assessment for monoclonal antibodies, bi-specifics, multi-specifics, and antibody-drug conjugates, the analysis of additional therapeutic modalities such as enzyme replacement proteins, blood factor proteins, CAR-T, gene therapy products, and peptide drugs is also made available on the ISPRI platform.

ISPRI (Interactive Screening and Protein Reengineering Interface): Integrated, cloud-based, comprehensive toolkit for Immunogenicity Risk Assessment.EpiMatrix Immunogenicity Score: Combined T effector and Treg Epitope Content per unit protein.Tregitopes: Treg Epitopes found in IgG Framework that have been shown to modulate antigen-specific effector T cell responses.ClustiMer: Tool for identifying epitope rich polypeptides from within a given protein sequence.JanusMatrix: Tool for Predicting Tolerance, Putative Treg Epitopes, and Anti-self-immune responses.OptiMatrix: Tool for modifying T cell epitope sequences to reduce (or enhance) MHC binding.

Neoadjuvant personalized cancer vaccines: the final frontier?

INTRODUCTION: Clinical trials of personalized cancer vaccines have shown that on-demand therapies that are manufactured for each patient, result in activated T cell responses against individual tumor neoantigens. However, their use has been traditionally restricted to adjuvant settings and late-stage cancer therapy. There is growing support for the implementation of PCV earlier in the cancer therapy timeline, for reasons that will be discussed in this review. AREAS COVERED: The efficacy of cancer vaccines may be to some extent dependent on treatment(s) given prior to vaccine administration. Tumors can undergo radical immunoediting following treatment with immunotherapies, such as checkpoint inhibitors, which may affect the presence of the very mutations targeted by cancer vaccines. This review will cover the topics of neoantigen cancer vaccines, tumor immunoediting, and therapy timing. EXPERT OPINION: Therapy timing remains a critical topic to address in optimizing the efficacy of personalized cancer vaccines. Most personalized cancer vaccines are being evaluated in late-stage cancer patients and after treatment with checkpoint inhibitors, but they may offer a greater benefit to the patient if administered in earlier clinical settings, such as the neoadjuvant setting, where patients are not facing T cell exhaustion and/or a further compromised immune system.

Optimization of therapeutic antibodies for reduced self-association and non-specific binding via interpretable machine learning.

Antibody development, delivery, and efficacy are influenced by antibody-antigen affinity interactions, off-target interactions that reduce antibody bioavailability and pharmacokinetics, and repulsive self-interactions that increase the stability of concentrated antibody formulations and reduce their corresponding viscosity. Yet identifying antibody variants with optimal combinations of these three types of interactions is challenging. Here we show that interpretable machine-learning classifiers, leveraging antibody structural features descriptive of their variable regions and trained on experimental data for a panel of 80 clinical-stage monoclonal antibodies, can identify antibodies with optimal combinations of low off-target binding in a common physiological-solution condition and low self-association in a common antibody-formulation condition. For three clinical-stage antibodies with suboptimal combinations of off-target binding and self-association, the classifiers predicted variable-region mutations that optimized non-affinity interactions while maintaining high-affinity antibody-antigen interactions. Interpretable machine-learning models may facilitate the optimization of antibody candidates for therapeutic applications.

A SARS-CoV-2 NSP7 homolog of a Treg epitope suppresses CD4+ and CD8+ T cell memory responses.

Pathogens escape host defenses by T-cell epitope mutation or deletion (immune escape) and by simulating the appearance of human T cell epitopes (immune camouflage). We identified a highly conserved, human-like T cell epitope in non-structural protein 7 (NSP7) of SARS-CoV-2, RNA-dependent RNA polymerase (RdRp) hetero-tetramer complex. Remarkably, this T cell epitope has significant homology to a T regulatory cell epitope (Tregitope) previously identified in the Fc region of human immunoglobulin G (IgG) (Tregitope 289). We hypothesized that the SARS-CoV-2 NSP7 epitope (NSP7-289) may induce suppressive responses by engaging and activating pre-existing regulatory T cells. We therefore compared NSP7-289 and IgG Tregitopes (289 and 289z, a shorter version of 289 that isolates the shared NSP7 epitope) in vitro. Tregitope peptides 289, 289z and NSP7-289 bound to multiple HLA-DRB1 alleles in vitro and suppressed CD4+ and CD8+ T cell memory responses. Identification and in vitro validation of SARS-CoV-2 NSP7-289 provides further evidence of immune camouflage and suggests that pathogens can use human-like epitopes to evade immune response and potentially enhance host tolerance. Further exploration of the role of cross-conserved Tregs in human immune responses to pathogens such as SARS-CoV-2 is warranted.

Development of IFNß-1a versions with reduced immunogenicity and full in vitro biological activity for the treatment of multiple sclerosis.

IFNß (recombinant interferon Beta) has been widely used for the treatment of Multiple sclerosis for the last four decades. Despite the human origin of the IFNß sequence, IFNß is immunogenic, and unwanted immune responses in IFNß-treated patients may compromise its efficacy and safety in the clinic. In this study, we applied the DeFT (De-immunization of Functional Therapeutics) approach to producing functional, de-immunized versions of IFNß-1a. Two de-immunized versions of IFNß-1a were produced in CHO cells and designated as IFNß-1a(VAR1) and IFNß-1a(VAR2). First, the secondary and tertiary protein structures were analyzed by circular dichroism spectroscopy. Then, the variants were also tested for functionality. While IFNß-1a(VAR2) showed similar in vitro antiviral activity to the original protein, IFNß-1a(VAR1) exhibited 40% more biological potency. Finally, in vivo assays using HLA-DR transgenic mice revealed that the de-immunized variants showed a markedly reduced immunogenicity when compared to the originator.

Does human homology reduce the potential immunogenicity of non-antibody scaffolds?

Biologics developers are moving beyond antibodies for delivery of a wide range of therapeutic interventions. These non-antibody modalities are often based on 'natural' protein scaffolds that are modified to deliver bioactive sequences. Both human-derived and non-human-sourced scaffold proteins have been developed. New types of "non-antibody" scaffolds are still being discovered, as they offer attractive alternatives to monoclonals due to their smaller size, improved stability, and ease of synthesis. They are believed to have low immunogenic potential. However, while several human-sourced protein scaffolds have not been immunogenic in clinical studies, this may not predict their overall performance in other therapeutic applications. A preliminary evaluation of their potential for immunogenicity is warranted. Immunogenicity risk potential has been clearly linked to the presence of T "helper" epitopes in the sequence of biologic therapeutics. In addition, tolerogenic epitopes are present in some human proteins and may decrease their immunogenic potential. While the detailed sequences of many non-antibody scaffold therapeutic candidates remain unpublished, their backbone sequences are available for review and analysis. We assessed 12 example non-antibody scaffold backbone sequences using our epitope-mapping tools (EpiMatrix) for this perspective. Based on EpiMatrix scoring, their HLA DRB1-restricted T cell epitope content appears to be lower than the average protein, and sequences that may act as tolerogenic epitopes are present in selected human-derived scaffolds. Assessing the potential immunogenicity of scaffold proteins regarding self and non-self T cell epitopes may be of use for drug developers and clinicians, as these exciting new non-antibody molecules begin to emerge from the preclinical pipeline into clinical use.

Identification of immunodominant T cell epitopes induced by natural Zika virus infection.

Zika virus (ZIKV) is a flavivirus primarily transmitted by Aedes species mosquitoes, first discovered in Africa in 1947, that disseminated through Southeast Asia and the Pacific Islands in the 2000s. The first ZIKV infections in the Americas were identified in 2014, and infections exploded through populations in Brazil and other countries in 2015/16. ZIKV infection during pregnancy can cause severe brain and eye defects in offspring, and infection in adults has been associated with higher risks of Guillain-Barré syndrome. We initiated a study to describe the natural history of Zika (the disease) and the immune response to infection, for which some results have been reported. In this paper, we identify ZIKV-specific CD4+ and CD8+ T cell epitopes that induce responses during infection. Two screening approaches were utilized: an untargeted approach with overlapping peptide arrays spanning the entire viral genome, and a targeted approach utilizing peptides predicted to bind human MHC molecules. Immunoinformatic tools were used to identify conserved MHC class I supertype binders and promiscuous class II binding peptide clusters predicted to bind 9 common class II alleles. T cell responses were evaluated in overnight IFN-γ ELISPOT assays. We found that MHC supertype binding predictions outperformed the bulk overlapping peptide approach. Diverse CD4+ T cell responses were observed in most ZIKV-infected participants, while responses to CD8+ T cell epitopes were more limited. Most individuals developed a robust T cell response against epitopes restricted to a single MHC class I supertype and only a single or few CD8+ T cell epitopes overall, suggesting a strong immunodominance phenomenon. Noteworthy is that many epitopes were commonly immunodominant across persons expressing the same class I supertype. Nearly all of the identified epitopes are unique to ZIKV and are not present in Dengue viruses. Collectively, we identified 31 immunogenic peptides restricted by the 6 major class I supertypes and 27 promiscuous class II epitopes. These sequences are highly relevant for design of T cell-targeted ZIKV vaccines and monitoring T cell responses to Zika virus infection and vaccination.

Immunoinformatic Risk Assessment of Host Cell Proteins During Process Development for Biologic Therapeutics.

The identification and removal of host cell proteins (HCPs) from biologic products is a critical step in drug development. Despite recent improvements to purification processes, biologics such as monoclonal antibodies, enzyme replacement therapies, and vaccines that are manufactured in a range of cell lines and purified using diverse processes may contain HCP impurities, making it necessary for developers to identify and quantify impurities during process development for each drug product. HCPs that contain sequences that are less conserved with human homologs may be more immunogenic than those that are more conserved. We have developed a computational tool, ISPRI-HCP, that estimates the immunogenic potential of HCP sequences by evaluating and quantifying T cell epitope density and relative conservation with similar T cell epitopes in the human proteome. Here we describe several case studies that support the use of this method for classifying candidate HCP impurities according to their immunogenicity risk.

Immunogenicity risk assessment of synthetic peptide drugs and their impurities.

Peptide drugs play an important part in medicine owing to their many therapeutic applications. Of the 80 peptide drugs approved for use in humans, at least five are now off-patent and are consequently being developed as generic alternatives to the originator products. To accelerate access to generic products, the FDA has proposed new regulatory pathways that do not require direct comparisons of generics to originators in clinical trials. The 'Abbreviated New Drug Application' (ANDA) pathway recommends that sponsors provide information on any new impurities in the generic drug, compared with the originator product, because the impurities can have potential to elicit unwanted immune responses owing to the introduction of T-cell epitopes. This review describes how peptide drug impurities can elicit unexpected immunogenicity and describes a framework for performing immunogenicity risk assessment of all types of bioactive peptide products. Although this report primarily focuses on generic peptides and their impurities, the approach might also be of interest for developers of novel peptide drugs who are preparing their products for an initial regulatory review.

Specific sequence mutations in a long-lasting rhIFN-α2b version reduce in vitro and in vivo immunogenicity and increase in vitro protein stability.

For decades, recombinant human interferon alpha (rhIFN-α2b) has been used to treat emerging and chronic viral diseases. However, rhIFN-α2b is immunogenic and has a short in vivo half-life. To solve these limitations, two long-lasting hyperglycosylated proteins with reduced immunogenicity were developed and designated as 4N-IFN(VAR1) and 4N-IFN(VAR3). Here, we continue to study the relevant characteristics of these therapeutic candidates. Thus, we demonstrated that both de-immunized IFN versions elicited significantly lower neutralizing antibody responses than the original molecule in HLA-DR1 transgenic mice, confirming our previous in vitro protein immunogenicity data. Also, we found that these biobetters exhibited remarkable stability when exposed to different physical factors that the protein product may encounter during its production process and storage, such as low pH, thermal stress, and repeated freezing/thawing cycles. Taking into consideration our previous and present results, 4N-IFN(VAR1) and 4N-IFN-4N(VAR3) appear to be valuable candidates for the treatment of human viral diseases.

Diversity and evolution of computationally predicted T cell epitopes against human respiratory syncytial virus.

Human respiratory syncytial virus (RSV) is a major cause of lower respiratory infection. Despite more than 60 years of research, there is no licensed vaccine. While B cell response is a major focus for vaccine design, the T cell epitope profile of RSV is also important for vaccine development. Here, we computationally predicted putative T cell epitopes in the Fusion protein (F) and Glycoprotein (G) of RSV wild circulating strains by predicting Major Histocompatibility Complex (MHC) class I and class II binding affinity. We limited our inferences to conserved epitopes in both F and G proteins that have been experimentally validated. We applied multidimensional scaling (MDS) to construct T cell epitope landscapes to investigate the diversity and evolution of T cell profiles across different RSV strains. We find the RSV strains are clustered into three RSV-A groups and two RSV-B groups on this T epitope landscape. These clusters represent divergent RSV strains with potentially different immunogenic profiles. In addition, our results show a greater proportion of F protein T cell epitope content conservation among recent epidemic strains, whereas the G protein T cell epitope content was decreased. Importantly, our results suggest that RSV-A and RSV-B have different patterns of epitope drift and replacement and that RSV-B vaccines may need more frequent updates. Our study provides a novel framework to study RSV T cell epitope evolution. Understanding the patterns of T cell epitope conservation and change may be valuable for vaccine design and assessment.

H1N1 G4 swine influenza T cell epitope analysis in swine and human vaccines and circulating strains uncovers potential risk to swine and humans.

BACKGROUND: Pandemic influenza viruses may emerge from animal reservoirs and spread among humans in the absence of cross-reactive antibodies in the human population. Immune response to highly conserved T cell epitopes in vaccines may still reduce morbidity and limit the spread of the new virus even when cross-protective antibody responses are lacking. METHODS: We used an established epitope content prediction and comparison tool, Epitope Content Comparison (EpiCC), to assess the potential for emergent H1N1 G4 swine influenza A virus (G4) to impact swine and human populations. We identified and computed the total cross-conserved T cell epitope content in HA sequences of human seasonal and experimental influenza vaccines, swine influenza vaccines from Europe and the United States (US) against G4. RESULTS: The overall T cell epitope content of US commercial swine vaccines was poorly conserved with G4, with an average T cell epitope coverage of 35.7%. EpiCC scores for the comparison between current human influenza vaccines and circulating human influenza strains were also very low. In contrast, the T cell epitope coverage of a recent European swine influenza vaccine (HL03) was 65.8% against G4. CONCLUSIONS: Poor T cell epitope cross-conservation between emergent G4 and swine and human influenza vaccines in the US may enable G4 to spread in swine and spillover to human populations in the absence of protective antibody response. One European influenza vaccine, HL03, may protect against emergent G4. This study illustrates the use of the EpiCC tool for prospective assessment of existing vaccine strains against emergent viruses in swine and human populations.

Expanding access to COVID-19 testing, vaccination and treatment at a free clinic for uninsured Spanish-speaking adults in Providence, RI.

The COVID-19 pandemic disproportionately impacted uninsured and minority populations, contributing to and reinforcing long-lasting health inequities. Clínica Esperanza/Hope Clinic (CEHC), a free clinic serving uninsured individuals, is one 'safety-net' clinic that improved access to COVID-19 testing and vaccinations for an at-risk population during the pandemic. A retrospective review was performed to quantify COVID-19 testing and vaccination rates for clinic participants, which were compared to rates in the general population. 51.7% of patients seeking COVID-related care at CEHC were uninsured, compared to 8% in Providence and 4.8% in Rhode Island. CEHC performed 5,623 COVID-19 tests for 4,498 unique individuals, a total of 15,783 vaccines were administered, and 10 to 20% of COVID-care participants reported food insecurity during the study period. The prevalence of COVID-19 in the uninsured population and the high demand for vaccines highlight the important role that free clinics can play in the pandemic setting.

Evaluation of a Human T Cell-Targeted Multi-Epitope Vaccine for Q Fever in Animal Models of Coxiella burnetii Immunity.

T cell-mediated immunity plays a central role in the control and clearance of intracellular Coxiella burnetii infection, which can cause Q fever. Therefore, we aimed to develop a novel T cell-targeted vaccine that induces pathogen-specific cell-mediated immunity to protect against Q fever in humans while avoiding the reactogenicity of the current inactivated whole cell vaccine. Human HLA class II T cell epitopes from C. burnetii were previously identified and selected by immunoinformatic predictions of HLA binding, conservation in multiple C. burnetii isolates, and low potential for cross-reactivity with the human proteome or microbiome. Epitopes were selected for vaccine inclusion based on long-lived human T cell recall responses to corresponding peptides in individuals that had been naturally exposed to the bacterium during a 2007-2010 Q fever outbreak in the Netherlands. Multiple viral vector-based candidate vaccines were generated that express concatemers of selected epitope sequences arranged to minimize potential junctional neo-epitopes. The vaccine candidates caused no antigen-specific reactogenicity in a sensitized guinea pig model. A subset of the vaccine epitope peptides elicited antigenic recall responses in splenocytes from C57BL/6 mice previously infected with C. burnetii. However, immunogenicity of the vaccine candidates in C57BL/6 mice was dominated by a single epitope and this was insufficient to confer protection against an infection challenge, highlighting the limitations of assessing human-targeted vaccine candidates in murine models. The viral vector-based vaccine candidates induced antigen-specific T cell responses to a broader array of epitopes in cynomolgus macaques, establishing a foundation for future vaccine efficacy studies in this large animal model of C. burnetii infection.

Novel H7N9 influenza immunogen design enhances mobilization of seasonal influenza T cell memory in H3N2 pre-immune mice.

Strategies that improve influenza vaccine immunogenicity are critical for the development of vaccines for pandemic preparedness. Hemagglutinin (HA)-specific CD4+ T cell epitopes support protective B cell responses against seasonal influenza. However, in the case of avian H7N9, which poses a pandemic threat, HA elicits only weak neutralizing antibody responses in infection and vaccination without adjuvant. We hypothesized that an immune-engineered H7N9 HA incorporating a broadly reactive H3N2 HA-specific memory CD4+ T cell epitope that replaces a regulatory T cell-inducing epitope at the corresponding position in H7N9 HA could harness preexisting influenza T cell immunity to increase CD4+ T cells that are needed for protective antibody development. We designed and produced a virus-like particle (VLP) vaccine that carries the epitope augmented H7N9 HA (OPT1) and immunized HLA-DR3 transgenic mice with established H3N2 immunity. OPT1-VLPs stimulated higher stem cell, central, and effector memory CD4+ T cell levels over wild type VLP immunization. In addition, activated, IL-21-producing follicular helper T cell frequencies were enhanced. This novel immunogen design strategy illustrates that site-specific modifications aimed to augment T cell epitope content enhance CD4+ T cell responses among critical subpopulations capable of aiding protective immune responses upon antigen re-encounter and that mobilization of immune memory can be used to overcome the poor immunogenicity of avian influenza viruses.

Meeting Gynecologic Needs and Assuring Adherence to Screening Guidelines at a Student-Run Free Clinic for Uninsured, Low-Income Women.

BACKGROUND: Uninsured, low-income, Spanish-speaking patients face barriers to obtaining gynecologic care in the United States. Clínica Esperanza/Hope Clinic, a free clinic in Rhode Island, hosts a biweekly Women's Clinic (WC) established and run by local medical students. METHODS: A retrospective chart review identified gyne- cologic services provided, needs met and adherence to screening guidelines at WC between June 2017 and May 2021. RESULTS: During 80 clinics, 278 patients were seen. 362 encounters occurred, with 288 missed appointments. Women primarily attended WC for routine care (159, 43.9%) or abnormal uterine bleeding (41, 11.3%). Common services provided include gynecologic exams (302, 27.0%), Pap smears (221, 19.7%), and STI screening (166, 14.8%). Pap smear and mammography guidelines were adhered to during 92.3% and 94.1% of visits, respectively. CONCLUSIONS: Accessible gynecologic care is a significant unmet need for uninsured, Spanish-speaking patients. These findings demonstrate the importance of gynecologic care at free clinics and warrant their expansion.

In silico Immunogenicity Assessment for Sequences Containing Unnatural Amino Acids: A Method Using Existing in silico Algorithm Infrastructure and a Vision for Future Enhancements.

The in silico prediction of T cell epitopes within any peptide or biologic drug candidate serves as an important first step for assessing immunogenicity. T cell epitopes bind human leukocyte antigen (HLA) by a well-characterized interaction of amino acid side chains and pockets in the HLA molecule binding groove. Immunoinformatics tools, such as the EpiMatrix algorithm, have been developed to screen natural amino acid sequences for peptides that will bind HLA. In addition to commonly occurring in synthetic peptide impurities, unnatural amino acids (UAA) are also often incorporated into novel peptide therapeutics to improve properties of the drug product. To date, the HLA binding properties of peptides containing UAA are not accurately estimated by most algorithms. Both scenarios warrant the need for enhanced predictive tools. The authors developed an in silico method for modeling the impact of a given UAA on a peptide's likelihood of binding to HLA and, by extension, its immunogenic potential. In silico assessment of immunogenic potential allows for risk-based selection of best candidate peptides in further confirmatory in vitro, ex vivo and in vivo assays, thereby reducing the overall cost of immunogenicity evaluation. Examples demonstrating in silico immunogenicity prediction for product impurities that are commonly found in formulations of the generic peptides teriparatide and semaglutide are provided. Next, this article discusses how HLA binding studies can be used to estimate the binding potentials of commonly encountered UAA and "correct" in silico estimates of binding based on their naturally occurring counterparts. As demonstrated here, these in vitro binding studies are usually performed with known ligands which have been modified to contain UAA in HLA anchor positions. An example using D-amino acids in relative binding position 1 (P1) of the PADRE peptide is presented. As more HLA binding data become available, new predictive models allowing for the direct estimation of HLA binding for peptides containing UAA can be established.

Neoantigen-based personalized cancer vaccines: the emergence of precision cancer immunotherapy.

INTRODUCTION: The field of cancer therapy has undergone a major transformation in less than a decade due to the introduction of checkpoint inhibitors, the advent of next generation sequencing and the discovery of neoantigens. The key observation that the breadth of each patient's immune response to the unique mutations or neoantigens present in their tumor is directly related to their survival has led oncologists to focus on driving immune responses to neoantigens through vaccination. Oncology has entered the era of precision immunotherapy, and cancer vaccine development is undergoing a paradigm shift. AREAS COVERED: Neoantigens are short peptide sequences found in tumors, but not noncancerous tissues, the vast majority of which are unique to each patient. In addition to providing a description of the distinguishing features of neoantigen discovery platforms, this review will address cross-cutting personalized cancer vaccine design themes and developmental stumbling blocks. EXPERT OPINION: Immunoinformatic pipelines that can rapidly scan cancer genomes and identify 'the best' neoantigens are in high demand. Despite the need for such tools, immunoinformatic methods for identifying neoepitopes in cancer genomes are diverse and have not been well-validated. Validation of 'personalized vaccine design pipelines' will bring about a revolution in neoantigen-based vaccine design and delivery.