Customized for Vaccine Development

Customized for Vaccine Development

Lab scientists in white coats working in a modern, well-lit laboratory setting.

Comprehensive Support Across All Stages of Development

Comprehensive Support Across All

Stages of Development

From early discovery through clinical development and post-licensure, SeromYx’s Systems Serology platform helps vaccine developers understand the functional immune mechanisms that drive protection.

We support natural infection studies, controlled human infection models, field efficacy trials, and post-licensure analyses by identifying functional correlates of protection and immune signatures linked to efficacy. Our data informs critical decisions around antigen and adjuvant selection, dose optimization, manufacturing process changes, and comparison of vaccine candidates against licensed products.

Pathogens Studied Using Systems Serology

Our Systems Serology platform has been applied across a wide range of infectious diseases to support vaccine development, immunogenicity assessment, and immune correlate discovery. The pathogens below represent viruses, bacteria, parasites, and fungi that have been studied using SeromYx’s comprehensive Fc-mediated antibody profiling and functional immune analysis.

  • Viruses (26)

    Coronaviruses

    SARS-CoV-1, SARS-CoV-2, MERS, Common cold coronaviruses (NL63, OC43)

    Flaviviruses & Others

    Dengue, Zika, Yellow fever

    Retroviruses

    HIV, SHIV, SIV, Endogenous retroviruses

    Herpesviruses

    HSV-1, HSV-2, Epstein-Barr virus, Varicella zoster

    Other Viruses

    Influenza, Measles, Mumps, RSV, Hep B, Hep C, HPV, Merkel Cell Polyomavirus, Crimean-Congo Hemorrhagic Fever, Rift Valley Fever

  • Fungus

    Aspergillus spp.

  • Parasite

    Plasmodium falciparum

  • Bacteria (14)

    • Bordetella pertussis
    • Clostridium botulinum
    • Clostridium tetani
    • Corynebacterium diphtheriae
    • Klebsiella pneumoniae
    • Mycobacterium tuberculosis
    • Neisseria meningitidis
    • Pseudomonas aeruginosa
    • Salmonella typhi
    • Shigella spp.
    • Staphylococcus aureus
    • Streptococcus agalactiae
    • Streptococcus pneumoniae
    • Vibrio cholerae

Viruses (26)

Fungi

Parasite

Bacteria (14)

Coronaviruses
SARS-CoV-1, SARS-CoV-2, MERS, Common cold coronaviruses (NL63, OC43)


Flaviviruses & Others
Dengue, Zika, Yellow fever


Retroviruses
HIV, SHIV, SIV, Endogenous retroviruses


Herpesviruses
HSV-1, HSV-2, Epstein-Barr virus, Varicella zoster


Other Viruses
Influenza, Measles, Mumps, RSV, Hep B, Hep C, HPV, Merkel Cell Polyomavirus, Crimean-Congo Hemorrhagic Fever, Rift Valley Fever

Aspergillus spp.

Plasmodium falcioarum

Bordetella pertussis

Clostridium botulinum

Clostridium tetani

Corynebacterium diphtheriae

Klebsiella pneumoniae

Mycobacterium tuberculosis

Neisseria meningitidis

Pseudomonas aeruginosa

Salmonella typhi

Shigella spp.

Staphylococcus aureus

Streptococcus agalactiae

Streptococcus pneumoniae

Vibrio cholerae

DISCOVERY

Systems Serology identifies antibody features linked to disease outcomes.


Profiling hospitalized COVID-19 patients revealed distinct antibody responses: survivors showed a spike (S)-focused, functional profile, while non-survivors had nucleocapsid (N)-biased, less effective antibodies. Just five key antibody features predicted clinical trajectory, supporting early risk stratification and biomarker development. These findings highlight the importance of spike-specific functional antibodies for vaccine targeting.


  • Differentiates survivors and non-survivors using key antibody signatures
  • Links enhanced S-specific phagocytosis and complement activity to protection
  • Informs vaccine antigen selection and immune monitoring strategies
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LEAD SELECTION

Prioritize candidates by protective antibody functions, not just quantity.


Systems Serology enables comparison of vaccine regimens based on their ability to elicit key protective antibody functions. Screening HIV vaccine candidates revealed wide variation in ADCP levels despite similar antibody titers. Changes in adjuvants and dosing shifted functional profiles, helping developers select candidates that induce higher-quality immune responses. This accelerates confident, data-driven down-selection for clinical advancement.


  • Differentiates vaccine leads by antibody function, not just titer
  • Reveals impact of formulation and regimen on immune quality
  • Supports efficient selection of candidates with greater clinical potential
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ASSAY DEVELOPMENT, VALIDATION, QUALIFICATION

Robust immune profiling beyond neutralization for clinical trials.


SeromYx developed and qualified a Systems Serology assay under WHO and GCLP standards to measure antibody-dependent functions in SARS-CoV-2 vaccine trials. The assay delivers precise, specific, and sensitive measurement of Fc effector activities (ADCP, ADCD, ADNKA), supporting secondary endpoints in Phase 3 studies and regulatory filings. This validated platform is adaptable for diverse vaccine programs requiring advanced immune monitoring.


  • Ensures reproducible, regulatory-grade immune data across cohorts
  • Measures extra-neutralizing Fc functions linked to protection
  • Scalable qualification framework for broad vaccine applications
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CLINICAL EFFICACY TESTING

Uncovering antibody mechanisms linked to protection beyond neutralization.


A head-to-head study of mRNA-1273 and BNT162b2 vaccines showed both induced strong humoral responses, but mRNA-1273 elicited higher IgA titers, enhanced Fcγ receptor binding, and greater functional activity (ADNP, ADNKA). Systems Serology mapped distinct Fc effector functions, offering mechanistic insights into their differing real-world efficacy and supporting identification of immune correlates of protection.


  • Differentiates vaccine-induced functional antibody profiles linked to protection
  • Detects spike-specific Fc activities beyond neutralization
  • Provides mechanistic insight for clinical trial correlates and disease attenuation
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MANUFACTURING SCALE-UP

Integrating antibody avidity with Fc effector profiling to enhance vaccine assessment.


By combining Systems Serology with surface plasmon resonance (SPR)–based avidity measurements, this study uncovered distinct immune profiles differentiating two vaccine manufacturing processes. While one process drove higher effector function with lower avidity, the other generated stronger avidity with reduced effector activity. Multivariate modeling highlighted avidity, NK cell IFNγ responses, and IgG1 as key features distinguishing the processes, providing mechanistic insight into how manufacturing influences vaccine-induced immunity.


  • Links antibody avidity with functional immune readouts
  • Differentiates immune profiles across vaccine manufacturing processes
  • Provides mechanistic insight to guide vaccine design and optimization
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SCIENTIFIC RESOURCES

October 29, 2026
Abstract: RTS,S/AS01 (RTS,S) is one of two WHO-recommended malaria vaccines for children in moderate-to-high transmission settings. Yet, no validated immune correlate of protection (CoP) has been established for this vaccine. We selected 16 biomarkers to further assess as candidate CoPs, based largely on their ability to well-predict post-challenge outcomes in a integrative correlates analysis of two phase 2a controlled human malaria infection (CHMI) studies, Malaria-068 and Malaria-071. We evaluated the predictive power of these 16 biomarkers in two additional phase 2a CHMI studies, Malaria-092 and Malaria-102, to confirm these candidate CoPs in new malaria vaccine trials. In MAL092, malaria-naïve volunteers were challenged three months after a series of two or three doses of RTS,S/AS01, and in MAL102, a subset were boosted nine months later and re-challenged after three weeks. The 16 biomarkers included Plasmodium falciparum circumsporozoite protein (CSP)-specific IgG antibodies targeting the CSP NANP-repeat region (CSP IgG ELISA), NANP repeat-specific antibody binding to human Fc gamma receptors (FcγRs), CSP-specific antibody Fc effector functions, total NANP6-specific serum Ig measured by biolayer interferometry (BLI), and NANP6-specific IgG1 antibodies measured by binding antibody multiplex assay. Immunogenicity analyses confirmed that the vaccine regimens elicited robust immune responses, including multiple biomarkers not previously reported on, in both trials. I 52 n MAL092, participants clustered into two distinct immunogenicity profiles that overlapped with malaria protection status. In univariate logistic regression analyses, most biomarkers were significantly associated with protection when measured on the day of challenge in both trials. Notably, the same three biomarkers ranked as top correlates in both trials (FCGR2AH NANP6, FCGR2AR NANP6, and FCGR2B NANP6; all adjusted p-values <0.001), with similar effect sizes across studies. Despite these strong associations, no biomarker demonstrated significantly better individual-level predictive performance than CSP IgG ELISA. In MAL092, CSP IgG ELISA achieved an area under the curve (AUC) [95% confidence interval (CI)] of 0.74 (0.63, 0.84), compared with AUCs of 0.76 - 0.78 for the top five biomarkers, all of which reflected NANP6-specific FcγR binding (all adjusted p-values > 0.37 versus CSP IgG ELISA). Predictive models trained on data from two prior CHMI studies and applied to MAL092 and MAL102 identified a model based on FCGR2B NANP6 (validation AUC = 0.77 in MAL092; 0.80 in MAL102) as the best-performing univariate model for both studies. The best-performing multivariate predictive model for MAL092 was based on BLI NANP6 Dissociation AUC and ADCP NANP6 (validation AUC = 0.76), and in MAL102, it was based on CSP IgG ELISA, BLI NANP6 Dissociation AUC, and ADCP NANP6 (validation AUC = 0.82). The next approximately 10 highest-ranked models, however, had comparable performance with overlapping 95% CIs, and none were clearly superior to CSP IgG ELISA (validation AUCs 0.74 and 0.71 in MAL092 and MAL102, respectively). Collectively, these findings suggest that the majority of the previously identified candidate CoPs also hold up well in two additional malaria vaccine CHMI trials and underscore the continued utility of the CSP IgG ELISA readout as a robust marker of protection. Further studies are needed to determine whether these candidate CoPs hold in malaria-endemic field settings. Identifying validated CoPs that predict malaria vaccine efficacy would promote the development and approval of more effective and durable next-generation vaccines. These advances could also inform vaccine strategies for other infectious diseases.
August 31, 2026
Abstract: Respiratory syncytial virus (RSV) is a leading cause of respiratory illness and there is no universally accepted serological correlate of protection (CoP). We evaluated serum pre-fusion immunoglobulin G binding (preF-IgG) and RSV-A2 neutralizing antibodies (RSV-nAb) in adults aged >60 years following vaccination with investigational Ad26.RSV.preF–RSV preF vaccine. PreF-IgG and RSV-nAb measured pre-vaccination (Day 1) and Day 15 post-vaccination were assessed as CoPs against RSV-mediated acute respiratory infection (ARI) and lower respiratory tract disease (LRTD). An increase in both preF-IgG and RSV-nAb at Day 15 was significantly associated with reduced occurrence of RSV-mediated ARI and LRTD during follow-up. Based on controlled vaccine-efficacy curves and Prentice criteria, both markers were identified as CoPs for RSV-mediated ARI and LRTD. These results were validated using samples from a second randomized, phase 3 efficacy trial. Comprehensive profiling of preF-specific antibody responses showed that preF IgG3 and IgG2 may also contribute to protection from RSV.
August 13, 2026
The Fc Review: When you engineer the Fc to enhance one mechanism, what else changes? A recent Nature Cancer study takes a closer look at that question using an agonistic anti-GITR antibody, showing how Fc optimization can influence not only FcγR engagement and Treg depletion, but other immune pathways contributing to antitumor activity. Background: GITR is a stimulatory immune checkpoint receptor being explored as a target for cancer immunotherapy. While agonistic anti-GITR antibodies have shown promise preclinically, clinical efficacy has been limited. Because FcγR engagement can contribute to the activity of these antibodies, the authors used Fc protein engineering and glycoengineering to alter interactions with different human FcγRs and examine how those changes affected antitumor activity. The study highlights: Fc variants with enhanced engagement of activating FcγRIIa or FcγRIIIa increased antitumor activity, while preferentially enhancing engagement of inhibitory FcγRIIb did not improve tumor control. Combining G236A with reduced fucosylation enhanced engagement of both activating FcγRIIa and FcγRIIIa, without enhanced binding to FcγRIIb. This combined variant showed greater antitumor activity than variants enhancing either activating receptor individually in the tested model. Fc-active variants depleted Tregs within the tumor. However, the optimized variant and IgG1 produced similar Treg depletion despite differences in therapeutic activity, pointing to an additional FcγR-mediated mechanism. The Fc-optimized antibody also increased dendritic cell activation, and the authors found that conventional DCs, particularly cDC1s, were required for the Fc-mediated antitumor effect in their models. Further experiments connected this activity to CD4 T cell–DC engagement, with downstream CD4 T cell cytotoxicity and enhanced CD8 T cell activity

Frequently Asked Questions (FAQ)

  • Can you analyze clinical trial samples?

    Yes. Our platform supports preclinical through clinical-stage vaccine programs, including natural infection studies, controlled human infection models, and field efficacy trials.

  • Can you identify immune signatures associated with protection?

    Yes. Using systems-level analytics, we identify multivariate immune features that associate with protection, durability, or reduced disease severity.

  • When is the best time to engage SeromYx in a program?

    We provide value across all phases, but especially during:

    • Candidate down-selection
    • Phase I/II immunogenicity studies
    • Correlate of protection investigations
  • What are the sample requirements for vaccine studies?

    Sample volume requirements vary depending on the assay panel selected. In general, we require approximately 25–150 µL per assay when performed in isolation against a single antigen.


    When multiple assays are combined within an integrated panel, overall sample requirements may decrease due to optimized assay design.


    If sample volume is limited, particularly for clinical trial cohorts, we can develop a tailored strategy to maximize data generation while conserving material. We encourage teams to contact us for a study-specific estimate as it may fall outside the range provided above.