A Predictive Model of Vaccine Reactogenicity Using Data from an In Vitro Human Innate Immunity Assay System

A primary concern in vaccine development is safety, particularly avoiding an excessive immune reaction in an otherwise healthy individual. An accurate prediction of vaccine reactogenicity using in vitro assays and computational models would facilitate screening and prioritization of novel candidates early in the vaccine development process. Using the modular in vitro immune construct model of human innate immunity, PBMCs from 40 healthy donors were treated with 10 different vaccines of varying reactogenicity profiles and then cell culture supernatants were analyzed via flow cytometry and a multichemokine/cytokine assay. Differential response profiles of innate activity and cell viability were observed in the system. In parallel, an extensive adverse event (AE) dataset for the vaccines was assembled from clinical trial data. A novel reactogenicity scoring framework accounting for the frequency and severity of local and systemic AEs was applied to the clinical data, and a machine learning approach was employed to predict the incidence of clinical AEs from the in vitro assay data. Biomarker analysis suggested that the relative levels of IL-1B, IL-6, IL-10, and CCL4 have higher predictive importance for AE risk. Predictive models were developed for local reactogenicity, systemic reactogenicity, and specific individual AEs. A forward-validation study was performed with a vaccine not used in model development, Trumenba (meningococcal group B vaccine). The clinically observed Trumenba local and systemic reactogenicity fell on the 26th and 93rd percentiles of the ranges predicted by the respective models. Models predicting specific AEs were less accurate. Our study presents a useful framework for the further development of vaccine reactogenicity predictive models.

Bridging Computational Vaccinology and Vaccine Development Through Systematic Identification, Characterization, and Downselection of Conserved and Variable Circumsporozoite Protein CD4 T Cell Epitopes From Diverse Plasmodium falciparum Strains

An effective malaria vaccine must prevent disease in a range of populations living in regions with vastly different transmission rates and protect against genetically-diverse Plasmodium falciparum (Pf) strains. The protective efficacy afforded by the currently licensed malaria vaccine, Mosquirix™, promotes strong humoral responses to Pf circumsporozoite protein (CSP) 3D7 but protection is limited in duration and by strain variation. Helper CD4 T cells are central to development of protective immune responses, playing roles in B cell activation and maturation processes, cytokine production, and stimulation of effector T cells. Therefore, we took advantage of recent in silico modeling advances to predict and analyze human leukocyte antigen (HLA)-restricted class II epitopes from PfCSP – across the entire PfCSP 3D7 sequence as well as in 539 PfCSP sequence variants – with the goal of improving PfCSP-based malaria vaccines. Specifically, we developed a systematic workflow to identify peptide sequences capable of binding HLA-DR in a context relevant to achieving broad human population coverage utilizing cognate T cell help and with limited T regulatory cell activation triggers. Through this workflow, we identified seven predicted class II epitope clusters in the N- and C-terminal regions of PfCSP 3D7 and an additional eight clusters through comparative analysis of 539 PfCSP sequence variants. A subset of these predicted class II epitope clusters was synthesized as peptides and assessed for HLA-DR binding in vitro. Further, we characterized the functional capacity of these peptides to prime and activate human peripheral blood mononuclear cells (PBMCs), by monitoring cytokine response profiles using MIMIC^® technology (Modular IMmune In vitro Construct). Utilizing this decision framework, we found sufficient differential cellular activation and cytokine profiles among HLA-DR-matched PBMC donors to downselect class II epitope clusters for inclusion in a vaccine targeting PfCSP. Importantly, the downselected clusters are not highly conserved across PfCSP variants but rather, they overlap a hypervariable region (TH2R) in the C-terminus of the protein. We recommend assessing these class II epitope clusters within the context of a PfCSP vaccine, employing a test system capable of measuring immunogenicity across a broad set of HLA-DR alleles.

Identification, Selection and Immune Assessment of Liver Stage CD8 T Cell Epitopes From Plasmodium falciparum

Immunization with radiation-attenuated sporozoites (RAS) has been shown to protect against malaria infection, primarily through CD8 T cell responses, but protection is limited based on parasite strain. Therefore, while CD8 T cells are an ideal effector population target for liver stage malaria vaccine development strategies, such strategies must incorporate conserved epitopes that cover a large range of class I human leukocyte antigen (HLA) supertypes to elicit cross-strain immunity across the target population. This approach requires identifying and characterizing a wide range of CD8 T cell epitopes for incorporation into a vaccine such that coverage across a large range of class I HLA alleles is attained. Accordingly, we devised an experimental framework to identify CD8 T cell epitopes from novel and minimally characterized antigens found at the pre-erythrocytic stage of parasite development. Through in silico analysis we selected conserved P. falciparum proteins, using P. vivax orthologues to establish stringent conservation parameters, predicted to have a high number of T cell epitopes across a set of six class I HLA alleles representative of major supertypes. Using the decision framework, five proteins were selected based on the density and number of predicted epitopes. Selected epitopes were synthesized as peptides and evaluated for binding to the class I HLA alleles in vitro to verify in silico binding predictions, and subsequently for stimulation of human T cells using the Modular IMmune In-vitro Construct (MIMIC®) technology to verify immunogenicity. By combining the in silico tools with the ex vivo high throughput MIMIC platform, we identified 15 novel CD8 T cell epitopes capable of stimulating an immune response in alleles across the class I HLA panel. We recommend these epitopes should be evaluated in appropriate in vivo humanized immune system models to determine their protective efficacy for potential inclusion in future vaccines.

Are patients with cancer concerned about burdening their families?

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Background: A diagnosis of advanced cancer frequently thrusts family members into the role of caregiver. Although caregiver burdens have been well documented, less is known about the level of concern borne by the patient (pt) with cancer in placing a family member in this role, known as self-perceived burden (SPB). Methods: As part of the larger “Living with Cancer” project we prospectively surveyed 1307 pts with advanced malignancies receiving treatment with non-curative intent at 17 New Jersey cancer programs within the Regional Cancer Care Associates network between Sept 2015 and Apr 2016. Pts were asked one question about SPB on family members (5-level Likert scale). Results: Pts felt that “Living with Cancer burdens my family” all day every day 68 pts (5%), part of each day 109 pts (8%), most days 136 pts (10%), occasionally 571 pts (44%) or not at all 423 pts (32%). Twenty-four percent of responses were flagged as concerned (rated most days or greater by 313 pts). In a logistic regression model, SPB was correlated with marital status (married and divorced more concerned than single) and younger age (both p < 0.05). Patients living in lower median income neighborhoods also appeared to have a higher frequency of concern (p < 0.1) Factors not correlating with the level of SPB included gender, race, solid vs liquid tumor type, and length of cancer diagnosis. SPB was also not influenced by DNR status, having developed a Living Will, or documentation of power of attorney. Distance from the pt’s home to the cancer center was not associated with SPB on the caregiver. For comparison, on the same LWC project 38% of pts with advanced cancer were concerned about the financial toxicity of their care and 33% were concerned about pain (both p < 0.01 compared to SPB). Conclusions: Self-perceived burden on a caregiver was identified in 24% of pts with advanced cancer, less than those concerned about financial toxicity or pain, in this NJ series. Divorced/married pts and younger pts with cancer are more likely to express concern. Developing an EOLC plan (DNR/Living will/POA) does not appear to influence SPB concerns.

Analysis of a live attenuated bacterial vaccine for tularemia in the MIMIC® (Modular Immune In vitro Construct) System (52.6)

Sanofi Pasteur has optimized a series of unique, sensitive, automatable, and cost-effective assay systems, termed the Modular IMmune In vitro Construct (MIMIC®), to permit the evaluation of human innate and adaptive immunity in a laboratory setting. The lymphoid tissue equivalent (LTE) module of the MIMIC® platform reproduces the correct cellular interactions and kinetics to initiate primary (naïve) human B and T cell responses in an in vitro setting. We are currently investigating LVS, a live attenuated bacterial vaccine strain of Francisella tularensis, in the MIMIC® System. LVS generates a strong, naïve, TH1-skewed CD4 T cell response demonstrated by the percentage of responding cells producing intracellular IFNγ and TNFα. This data is consistent with human in vivo data showing that protection elicited by LVS vaccine includes a strong cellular immunity component. Previous studies have also shown that LVS drives production of protective antibodies in humans. We have currently demonstrated that the MIMIC® System can drive the generation of LVS-specific antibody responses in vitro using a fully autologous system. These studies indicate that the in vitro MIMIC® system offers a platform in which to conduct experiments in a fully human system prior to the involvement of human subjects. Therefore, the MIMIC® system provides a platform for analysis of new vaccine candidates and can be utilized for greater understanding of how efficient vaccines function.