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Hartmeier PR, Ostrowski SM, Busch EE, Empey KM, Meng WS. Lymphatic distribution considerations for subunit vaccine design and development. Vaccine 2024; 42:2519-2529. [PMID: 38494411 DOI: 10.1016/j.vaccine.2024.03.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/30/2024] [Accepted: 03/13/2024] [Indexed: 03/19/2024]
Abstract
Subunit vaccines are an important platform for controlling current and emerging infectious diseases. The lymph nodes are the primary site generating the humoral response and delivery of antigens to these sites is critical to effective immunization. Indeed, the duration of antigen exposure within the lymph node is correlated with the antibody response. While current licensed vaccines are typically given through the intramuscular route, injecting vaccines subcutaneously allows for direct access to lymphatic vessels and therefore can enhance the transfer of antigen to the lymph nodes. However, protein subunit antigen uptake into the lymph nodes is inefficient, and subunit vaccines require adjuvants to stimulate the initial immune response. Therefore, formulation strategies have been developed to enhance the exposure of subunit proteins and adjuvants to the lymph nodes by increasing lymphatic uptake or prolonging the retention at the injection site. Given that lymph node exposure is a crucial consideration in vaccine design, in depth analyses of the pharmacokinetics of antigens and adjuvants should be the focus of future preclinical and clinical studies. This review will provide an overview of formulation strategies for targeting the lymphatics and prolonging antigen exposure and will discuss pharmacokinetic evaluations which can be applied toward vaccine development.
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Affiliation(s)
- Paul R Hartmeier
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, USA
| | - Sarah M Ostrowski
- Department of Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, PA 15213, USA
| | - Emelia E Busch
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, USA
| | - Kerry M Empey
- Center for Clinical Pharmaceutical Sciences, School of Pharmacy, University of Pittsburgh, Pittsburgh, PA 15261, USA; Department of Pharmacy and Therapeutics, School of Pharmacy, University of Pittsburgh, PA 15213, USA; Department of Immunology, School of Medicine University of Pittsburgh, PA 15213, USA
| | - Wilson S Meng
- Graduate School of Pharmaceutical Sciences, School of Pharmacy, Duquesne University, Pittsburgh, PA 15282, USA; McGowan Institute for Regenerative Medicine, University of Pittsburgh, PA 15219, USA.
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Desikan R, Germani M, van der Graaf PH, Magee M. A Quantitative Clinical Pharmacology-Based Framework For Model-Informed Vaccine Development. J Pharm Sci 2024; 113:22-32. [PMID: 37924975 DOI: 10.1016/j.xphs.2023.10.043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/27/2023] [Accepted: 10/28/2023] [Indexed: 11/06/2023]
Abstract
Historically, vaccine development and dose optimization have followed mostly empirical approaches without clinical pharmacology and model-informed approaches playing a major role, in contrast to conventional drug development. This is attributed to the complex cascade of immunobiological mechanisms associated with vaccines and a lack of quantitative frameworks for extracting dose-exposure-efficacy-toxicity relationships. However, the Covid-19 pandemic highlighted the lack of sufficient immunogenicity due to suboptimal vaccine dosing regimens and the need for well-designed, model-informed clinical trials which enhance the probability of selection of optimal vaccine dosing regimens. In this perspective, we attempt to develop a quantitative clinical pharmacology-based approach that integrates vaccine dose-efficacy-toxicity across various stages of vaccine development into a unified framework that we term as model-informed vaccine dose-optimization and development (MIVD). We highlight scenarios where the adoption of MIVD approaches may have a strategic advantage compared to conventional practices for vaccines.
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Affiliation(s)
- Rajat Desikan
- Clinical Pharmacology Modelling & Simulation, GSK, United Kingdom.
| | | | - Piet H van der Graaf
- Certara QSP, Canterbury Innovation Centre, University Road, Canterbury CT2 7FG, United Kingdom; Leiden Academic Centre for Drug Research, Einsteinweg 55, 2333 CC Leiden, Netherlands
| | - Mindy Magee
- Clinical Pharmacology Modelling & Simulation, GSK, United States
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3
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Boonstra PS, Tabarrok A, Strohbehn GW. Targeted randomization dose optimization trials enable fractional dosing of scarce drugs. PLoS One 2023; 18:e0287511. [PMID: 37903093 PMCID: PMC10615276 DOI: 10.1371/journal.pone.0287511] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2022] [Accepted: 06/07/2023] [Indexed: 11/01/2023] Open
Abstract
Administering drug at a dose lower than that used in pivotal clinical trials, known as fractional dosing, can stretch scarce resources. Implementing fractional dosing with confidence requires understanding a drug's dose-response relationship. Clinical trials aimed at describing dose-response in scarce, efficacious drugs risk underdosing, leading dose-finding trials to not be pursued despite their obvious potential benefit. We developed a new set of response-adaptive randomized dose-finding trials and demonstrate, in a series of simulated trials across diverse dose-response curves, these designs' efficiency in identifying the minimum dose that achieves satisfactory efficacy. Compared to conventional designs, these trials have higher probabilities of identifying lower doses while reducing the risks of both population- and subject-level underdosing. We strongly recommend that, upon demonstration of a drug's efficacy, pandemic drug development swiftly proceeds with response-adaptive dose-finding trials. This unified strategy ensures that scarce effective drugs produce maximum social benefits.
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Affiliation(s)
- Philip S. Boonstra
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America
- Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Alex Tabarrok
- Department of Economics, George Mason University, Fairfax, Virginia, United States of America
| | - Garth W. Strohbehn
- Rogel Cancer Center, University of Michigan, Ann Arbor, Michigan, United States of America
- Veterans Affairs Center for Clinical Management and Research, Ann Arbor, Michigan, United States of America
- Institute for Health Policy and Innovation, University of Michigan, Ann Arbor, Michigan, United States of America
- Division of Medical Oncology, LTC Charles S Kettles VA Medical Center, Ann Arbor, Michigan, United States of America
- Division of Hematology/Oncology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
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Rhodes S, Smith N, Evans T, White R. Identifying COVID-19 optimal vaccine dose using mathematical immunostimulation/immunodynamic modelling. Vaccine 2022; 40:7032-7041. [PMID: 36272876 PMCID: PMC9574467 DOI: 10.1016/j.vaccine.2022.10.012] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2022] [Revised: 10/03/2022] [Accepted: 10/07/2022] [Indexed: 11/05/2022]
Abstract
INTRODUCTION Identifying optimal COVID-19 vaccine dose is essential for maximizing their impact. However, COVID-19 vaccine dose-finding has been an empirical process, limited by short development timeframes, and therefore potentially not thoroughly investigated. Mathematical IS/ID modelling is a novel method for predicting optimal vaccine dose which could inform future COVID-19 vaccine dose decision making. METHODS Published clinical data on COVID-19 vaccine dose-response was identified and extracted. Mathematical models were calibrated to the dose-response data stratified by subpopulation, where possible to predict optimal dose. Predicted optimal doses were summarised across vaccine type and compared to chosen dose for the primary series of COVID-19 vaccines to identify vaccine doses that may benefit from re-evaluation. RESULTS 30 clinical dose-response datasets in adults and elderly population were extracted for four vaccine types and optimal doses predicted using the models. Results suggest that, if re-assessed for dose, COVID-19 vaccines Ad26.cov, ChadOx1 n-Cov19, BNT162b2, Coronavac, and NVX-CoV2373 could benefit from increased dose in adults and mRNA-1273 and Coronavac, could benefit from increased and decreased dose for the elderly population, respectively. DISCUSSION Future iterations of COVID-19 vaccines could benefit from re-evaluating dose to ensure most effective use of the vaccine and mathematical modelling can support this.
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Affiliation(s)
- Sophie Rhodes
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK,Corresponding author
| | - Neal Smith
- Defence and Science Technology Laboratory, UK
| | | | - Richard White
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK
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Benest J, Rhodes S, Evans TG, White RG. Mathematical Modelling for Optimal Vaccine Dose Finding: Maximising Efficacy and Minimising Toxicity. Vaccines (Basel) 2022; 10:vaccines10050756. [PMID: 35632511 PMCID: PMC9144167 DOI: 10.3390/vaccines10050756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2022] [Revised: 05/03/2022] [Accepted: 05/06/2022] [Indexed: 02/06/2023] Open
Abstract
Vaccination is a key tool to reduce global disease burden. Vaccine dose can affect vaccine efficacy and toxicity. Given the expense of developing vaccines, optimising vaccine dose is essential. Mathematical modelling has been suggested as an approach for optimising vaccine dose by quantitatively establishing the relationships between dose and efficacy/toxicity. In this work, we performed simulation studies to assess the performance of modelling approaches in determining optimal dose. We found that the ability of modelling approaches to determine optimal dose improved with trial size, particularly for studies with at least 30 trial participants, and that, generally, using a peaking or a weighted model-averaging-based dose–efficacy relationship was most effective in finding optimal dose. Most methods of trial dose selection were similarly effective for the purpose of determining optimal dose; however, including modelling to adapt doses during a trial may lead to more trial participants receiving a more optimal dose. Clinical trial dosing around the predicted optimal dose, rather than only at the predicted optimal dose, may improve final dose selection. This work suggests modelling can be used effectively for vaccine dose finding, prompting potential practical applications of these methods in accelerating effective vaccine development and saving lives.
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Affiliation(s)
- John Benest
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.G.W.)
- Correspondence:
| | - Sophie Rhodes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.G.W.)
| | - Thomas G. Evans
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK;
| | - Richard G. White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.G.W.)
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Long-Term In Vitro Passaging Had a Negligible Effect on Extracellular Vesicles Released by Leishmania amazonensis and Induced Protective Immune Response in BALB/c Mice. J Immunol Res 2022; 2021:7809637. [PMID: 34977257 PMCID: PMC8720021 DOI: 10.1155/2021/7809637] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Revised: 11/07/2021] [Accepted: 11/25/2021] [Indexed: 12/03/2022] Open
Abstract
Depending on Leishmania species and the presence/absence of virulence factors, Leishmania extracellular vesicles (EVs) can differently stimulate host immune cells. This work is aimed at characterizing and evaluating the protective role of EVs released by Leishmania amazonensis promastigotes under different maintenance conditions. Initially, using a control strain, we standardized 26°C as the best release temperature to obtain EVs with a potential protective role in the experimental leishmaniasis model. Then, long-term (LT-P) promastigotes of L. amazonensis were obtained after long-term in vitro culture (100 in vitro passages). In vivo-derived (IVD-P) promastigotes of L. amazonensis were selected after 3 consecutive experimental infections in BALB/c mice. Those strains developed similar lesion sizes except for IVD-P at 8 weeks post infection. No differences in EV production were detected in both strains. However, the presence of LPG between LT-P and IVD-P EVs was different. Groups of mice immunized with EVs emulsified in the adjuvant and challenged with IVD-P parasites showed decreased lesion size and parasitic load compared with the nonimmunized groups. The immunization regimen with two doses showed high IFN-γ and IgG2a titers in challenged mice with either IVD-P or LT-P EVs. IL-4 and IL-10 were detected in immunized mice, suggesting a mixed Th1/Th2 profile. EVs released by either IVD-P or LT-P induced a partial protective effect in an immunization model. Thus, our results uncover a potential protective role of EVs from L. amazonensis for cutaneous leishmaniasis. Moreover, long-term maintenance under in vitro conditions did not seem to affect EV release and their immunization properties in mice.
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Ciupe SM, Vaidya NK, Forde JE. Early events in hepatitis B infection: the role of inoculum dose. Proc Biol Sci 2021; 288:20202715. [PMID: 33563115 DOI: 10.1098/rspb.2020.2715] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The relationship between the inoculum dose and the ability of the pathogen to invade the host is poorly understood. Experimental studies in non-human primates infected with different inoculum doses of hepatitis B virus have shown a non-monotonic relationship between dose magnitude and infection outcome, with high and low doses leading to 100% liver infection and intermediate doses leading to less than 0.1% liver infection, corresponding to CD4 T-cell priming. Since hepatitis B clearance is CD8 T-cell mediated, the question of whether the inoculum dose influences CD8 T-cell dynamics arises. To help answer this question, we developed a mathematical model of virus-host interaction following hepatitis B virus infection. Our model explains the experimental data well, and predicts that the inoculum dose affects both the timing of the CD8 T-cell expansion and the quality of its response, especially the non-cytotoxic function. We find that a low-dose challenge leads to slow CD8 T-cell expansion, weak non-cytotoxic functions, and virus persistence; high- and medium-dose challenges lead to fast CD8 T-cell expansion, strong cytotoxic and non-cytotoxic function, and virus clearance; while a super-low-dose challenge leads to delayed CD8 T-cell expansion, strong cytotoxic and non-cytotoxic function, and virus clearance. These results are useful for designing immune cell-based interventions.
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Affiliation(s)
- Stanca M Ciupe
- Department of Mathematics, Virginia Tech, Blacksburg, 24060 VA, USA
| | - Naveen K Vaidya
- Department of Mathematics and Statistics, San Diego State University, San Diego, CA 92182, USA.,Computational Science Research Center, San Diego State University, San Diego, CA 92182, USA.,Viral Information Institute, San Diego State University, San Diego, CA 92182, USA
| | - Jonathan E Forde
- Department of Mathematics and Computer Science, Hobart and William Smith Colleges, Geneva, New York 14456, USA
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Benest J, Rhodes S, Quaife M, Evans TG, White RG. Optimising Vaccine Dose in Inoculation against SARS-CoV-2, a Multi-Factor Optimisation Modelling Study to Maximise Vaccine Safety and Efficacy. Vaccines (Basel) 2021; 9:vaccines9020078. [PMID: 33499326 PMCID: PMC7911627 DOI: 10.3390/vaccines9020078] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Revised: 01/17/2021] [Accepted: 01/20/2021] [Indexed: 01/05/2023] Open
Abstract
Developing a vaccine against the global pandemic SARS-CoV-2 is a critical area of active research. Modelling can be used to identify optimal vaccine dosing; maximising vaccine efficacy and safety and minimising cost. We calibrated statistical models to published dose-dependent seroconversion and adverse event data of a recombinant adenovirus type-5 (Ad5) SARS-CoV-2 vaccine given at doses 5.0 × 1010, 1.0 × 1011 and 1.5 × 1011 viral particles. We estimated the optimal dose for three objectives, finding: (A) the minimum dose that may induce herd immunity, (B) the dose that maximises immunogenicity and safety and (C) the dose that maximises immunogenicity and safety whilst minimising cost. Results suggest optimal dose [95% confidence interval] in viral particles per person was (A) 1.3 × 1011 [0.8–7.9 × 1011], (B) 1.5 × 1011 [0.3–5.0 × 1011] and (C) 1.1 × 1011 [0.2–1.5 × 1011]. Optimal dose exceeded 5.0 × 1010 viral particles only if the cost of delivery exceeded £0.65 or cost per 1011 viral particles was less than £6.23. Optimal dose may differ depending on the objectives of developers and policy-makers, but further research is required to improve the accuracy of optimal-dose estimates.
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Affiliation(s)
- John Benest
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (M.Q.); (R.G.W.)
- Correspondence:
| | - Sophie Rhodes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (M.Q.); (R.G.W.)
| | - Matthew Quaife
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (M.Q.); (R.G.W.)
| | - Thomas G. Evans
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK;
| | - Richard G. White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (M.Q.); (R.G.W.)
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Shemesh CS, Hsu JC, Hosseini I, Shen BQ, Rotte A, Twomey P, Girish S, Wu B. Personalized Cancer Vaccines: Clinical Landscape, Challenges, and Opportunities. Mol Ther 2020; 29:555-570. [PMID: 33038322 DOI: 10.1016/j.ymthe.2020.09.038] [Citation(s) in RCA: 126] [Impact Index Per Article: 31.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2020] [Revised: 09/15/2020] [Accepted: 09/26/2020] [Indexed: 12/21/2022] Open
Abstract
Tremendous innovation is underway among a rapidly expanding repertoire of promising personalized immune-based treatments. Therapeutic cancer vaccines (TCVs) are attractive systemic immunotherapies that activate and expand antigen-specific CD8+ and CD4+ T cells to enhance anti-tumor immunity. Our review highlights key issues impacting TCVs in clinical practice and reports on progress in development. We review the mechanism of action, immune-monitoring, dosing strategies, combinations, obstacles, and regulation of cancer vaccines. Most trials of personalized TCVs are ongoing and represent diverse platforms with predominantly early investigations of mRNA, DNA, or peptide-based targeting strategies against neoantigens in solid tumors, with many in combination immunotherapies. Multiple delivery systems, routes of administration, and dosing strategies are used. Intravenous or intramuscular administration is common, including delivery by lipid nanoparticles. Absorption and biodistribution impact antigen uptake, expression, and presentation, affecting the strength, speed, and duration of immune response. The emerging trials illustrate the complexity of developing this class of innovative immunotherapies. Methodical testing of the multiple potential factors influencing immune responses, as well as refined quantitative methodologies to facilitate optimal dosing strategies, could help resolve uncertainty of therapeutic approaches. To increase the likelihood of success in bringing these medicines to patients, several unique development challenges must be overcome.
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Affiliation(s)
- Colby S Shemesh
- Department of Clinical Pharmacology Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA.
| | - Joy C Hsu
- Department of Clinical Pharmacology Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Iraj Hosseini
- Department of Preclinical and Translational Pharmacokinetics and Pharmacodynamics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Ben-Quan Shen
- Department of Preclinical and Translational Pharmacokinetics and Pharmacodynamics, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Anand Rotte
- Department of Clinical Pharmacology Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Patrick Twomey
- Department of Product Development Safety, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Sandhya Girish
- Department of Clinical Pharmacology Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
| | - Benjamin Wu
- Department of Clinical Pharmacology Oncology, Genentech, Inc., 1 DNA Way, South San Francisco, CA 94080, USA
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Eyer K, Castrillon C, Chenon G, Bibette J, Bruhns P, Griffiths AD, Baudry J. The Quantitative Assessment of the Secreted IgG Repertoire after Recall to Evaluate the Quality of Immunizations. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2020; 205:1176-1184. [PMID: 32669311 PMCID: PMC7416324 DOI: 10.4049/jimmunol.2000112] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2020] [Accepted: 06/15/2020] [Indexed: 01/03/2023]
Abstract
One of the major goals of vaccination is to prepare the body to rapidly secrete specific Abs during an infection. Assessment of the vaccine quality is often difficult to perform, as simple measurements like Ab titer only partly correlate with protection. Similarly, these simple measurements are not always sensitive to changes in the preceding immunization scheme. Therefore, we introduce in this paper a new, to our knowledge, method to assay the quality of immunization schemes for mice: shortly after a recall with pure Ag, we analyze the frequencies of IgG-secreting cells (IgG-SCs) in the spleen, as well as for each cells, the Ag affinity of the secreted Abs. We observed that after recall, appearance of the IgG-SCs within the spleen of immunized mice was fast (<24 h) and this early response was free of naive IgG-SCs. We further confirmed that our phenotypic analysis of IgG-SCs after recall strongly correlated with the different employed immunization schemes. Additionally, a phenotypic comparison of IgG-SCs presented in the spleen during immunization or after recall revealed similarities but also significant differences. The developed approach introduced a novel (to our knowledge), quantitative, and functional highly resolved alternative to study the quality of immunizations.
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Affiliation(s)
- Klaus Eyer
- Laboratoire Colloïdes et Matériaux Divisés, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France;
- Laboratory for Functional Immune Repertoire Analysis, Institute of Pharmaceutical Sciences, Department of Chemistry and Applied Biology, ETH Zürich, 8093 Zurich, Switzerland
| | - Carlos Castrillon
- Unit of Antibodies in Therapy and Pathology, Pasteur Institute, UMR1222 INSERM, 75015 Paris, France
- Laboratoire de Biochimie, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France; and
- Sorbonne Université, Collège Doctoral, F-75005 Paris, France
| | - Guilhem Chenon
- Laboratoire Colloïdes et Matériaux Divisés, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France
| | - Jérôme Bibette
- Laboratoire Colloïdes et Matériaux Divisés, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France
| | - Pierre Bruhns
- Unit of Antibodies in Therapy and Pathology, Pasteur Institute, UMR1222 INSERM, 75015 Paris, France
| | - Andrew D Griffiths
- Laboratoire de Biochimie, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France; and
| | - Jean Baudry
- Laboratoire Colloïdes et Matériaux Divisés, Institut Chimie, Biologie, Innovation, UMR8231, ESPCI Paris, CNRS, Université Paris Sciences et Lettres, 75005 Paris, France
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11
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Benest J, Rhodes S, Afrough S, Evans T, White R. Response Type and Host Species may be Sufficient to Predict Dose-Response Curve Shape for Adenoviral Vector Vaccines. Vaccines (Basel) 2020; 8:vaccines8020155. [PMID: 32235634 PMCID: PMC7349762 DOI: 10.3390/vaccines8020155] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 03/20/2020] [Accepted: 03/26/2020] [Indexed: 12/20/2022] Open
Abstract
Vaccine dose-response curves can follow both saturating and peaking shapes. Dose-response curves for adenoviral vector vaccines have not been systematically described. In this paper, we explore the dose-response shape of published adenoviral animal and human studies. Where data were informative, dose-response was approximately five times more likely to be peaking than saturating. There was evidence that host species and response type may be sufficient for prediction of dose-response curve shape. Dose-response curve shape prediction could decrease clinical trial costs, accelerating the development of life-saving vaccines.
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Affiliation(s)
- John Benest
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.)
- Correspondence:
| | - Sophie Rhodes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.)
| | - Sara Afrough
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK (T.E.)
| | - Thomas Evans
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK (T.E.)
| | - Richard White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.)
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12
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Afrough S, Rhodes S, Evans T, White R, Benest J. Immunologic Dose-Response to Adenovirus-Vectored Vaccines in Animals and Humans: A Systematic Review of Dose-Response Studies of Replication Incompetent Adenoviral Vaccine Vectors when Given via an Intramuscular or Subcutaneous Route. Vaccines (Basel) 2020; 8:E131. [PMID: 32192058 PMCID: PMC7157626 DOI: 10.3390/vaccines8010131] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Revised: 03/09/2020] [Accepted: 03/10/2020] [Indexed: 12/21/2022] Open
Abstract
Optimal vaccine dosing is important to ensure the greatest protection and safety. Analysis of dose-response data, from previous studies, may inform future studies to determine the optimal dose. Implementing more quantitative modelling approaches in vaccine dose finding have been recently suggested to accelerate vaccine development. Adenoviral vectored vaccines are in advanced stage of development for a variety of prophylactic and therapeutic indications, however dose-response has not yet been systematically determined. To further inform adenoviral vectored vaccines dose identification, historical dose-response data should be systematically reviewed. A systematic literature review was conducted to collate and describe the available dose-response studies for adenovirus vectored vaccines. Of 2787 papers identified by Medline search strategy, 35 were found to conform to pre-defined criteria. The majority of studies were in mice or humans and studied adenovirus serotype 5. Dose-response data were available for 12 different immunological responses. The majority of papers evaluated three dose levels, only two evaluated more than five dose levels. The most common dosing range was 107-1010 viral particles in mouse studies and 108-1011 viral particles in human studies. Data were available on adenovirus vaccine dose-response, primarily on adenovirus serotype 5 backbones and in mice and humans. These data could be used for quantitative adenoviral vectored vaccine dose optimisation analysis.
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Affiliation(s)
- Sara Afrough
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK;
| | - Sophie Rhodes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.); (J.B.)
| | - Thomas Evans
- Vaccitech Ltd., The Schrodinger Building, Heatley Road, The Oxford Science Park, Oxford OX4 4GE, UK;
| | - Richard White
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.); (J.B.)
| | - John Benest
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK; (S.R.); (R.W.); (J.B.)
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13
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Duthie MS, Frevol A, Day T, Coler RN, Vergara J, Rolf T, Sagawa ZK, Marie Beckmann A, Casper C, Reed SG. A phase 1 antigen dose escalation trial to evaluate safety, tolerability and immunogenicity of the leprosy vaccine candidate LepVax (LEP-F1 + GLA–SE) in healthy adults. Vaccine 2020; 38:1700-1707. [DOI: 10.1016/j.vaccine.2019.12.050] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Revised: 12/09/2019] [Accepted: 12/20/2019] [Indexed: 12/31/2022]
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14
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Suliman S, Luabeya AKK, Geldenhuys H, Tameris M, Hoff ST, Shi Z, Tait D, Kromann I, Ruhwald M, Rutkowski KT, Shepherd B, Hokey D, Ginsberg AM, Hanekom WA, Andersen P, Scriba TJ, Hatherill M. Dose Optimization of H56:IC31 Vaccine for Tuberculosis-Endemic Populations. A Double-Blind, Placebo-controlled, Dose-Selection Trial. Am J Respir Crit Care Med 2019; 199:220-231. [PMID: 30092143 DOI: 10.1164/rccm.201802-0366oc] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
RATIONALE Global tuberculosis (TB) control requires effective vaccines in TB-endemic countries, where most adults are infected with Mycobacterium tuberculosis (M.tb). OBJECTIVES We sought to define optimal dose and schedule of H56:IC31, an experimental TB vaccine comprising Ag85B, ESAT-6, and Rv2660c, for M.tb-infected and M.tb-uninfected adults. METHODS We enrolled 98 healthy, HIV-uninfected, bacillus Calmette-Guérin-vaccinated, South African adults. M.tb infection was defined by QuantiFERON-TB (QFT) assay. QFT-negative participants received two vaccinations of different concentrations of H56 in 500 nmol of IC31 to enable dose selection for further vaccine development. Subsequently, QFT-positive and QFT-negative participants were randomized to receive two or three vaccinations to compare potential schedules. Participants were followed for safety and immunogenicity for 292 days. MEASUREMENTS AND MAIN RESULTS H56:IC31 showed acceptable reactogenicity profiles irrespective of dose, number of vaccinations, or M.tb infection. No vaccine-related severe or serious adverse events were observed. The three H56 concentrations tested induced equivalent frequencies and functional profiles of antigen-specific CD4 T cells. ESAT-6 was only immunogenic in QFT-negative participants who received three vaccinations. CONCLUSIONS Two or three H56:IC31 vaccinations at the lowest dose induced durable antigen-specific CD4 T-cell responses with acceptable safety and tolerability profiles in M.tb-infected and M.tb-uninfected adults. Additional studies should validate applicability of vaccine doses and regimens to both QFT-positive and QFT-negative individuals. Clinical trial registered with www.clinicaltrials.gov (NCT01865487).
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Affiliation(s)
- Sara Suliman
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Angelique Kany Kany Luabeya
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Hennie Geldenhuys
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Michele Tameris
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | | | | | | | | | | | | | | | | | | | - Willem A Hanekom
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | | | - Thomas J Scriba
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | - Mark Hatherill
- 1 South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine, and.,2 Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
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15
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Attaya A, Jiang Y, Secombes CJ, Wang T. Distinct response of immune gene expression in peripheral blood leucocytes modulated by bacterin vaccine candidates in rainbow trout Oncorhynchus mykiss: A potential in vitro screening and batch testing system for vaccine development in aquaculture. FISH & SHELLFISH IMMUNOLOGY 2019; 93:631-640. [PMID: 31377431 DOI: 10.1016/j.fsi.2019.08.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2019] [Revised: 07/02/2019] [Accepted: 08/01/2019] [Indexed: 06/10/2023]
Abstract
Fish aquaculture is the world's fastest growing food production industry and infectious diseases are a major limiting factor. Vaccination is the most appropriate method for controlling infectious diseases and a key reason for the success of salmonid cultivation and has reduced the use of antibiotics. The development of fish vaccines requires the use of a great number of experimental animals that are challenged with virulent pathogens. In vitro cell culture systems have the potential to replace in vivo pathogen exposure for initial screening and testing of novel vaccine candidates/preparations, and for batch potency and safety tests. PBL contain major immune cells that enable the detection of both innate and adaptive immune responses in vitro. Fish PBL can be easily prepared using a hypotonic method and is the only way to obtain large numbers of immune cells non-lethally. Distinct gene expression profiles of innate and adaptive immunity have been observed between bacterins prepared from different bacterial species, as well as from different strains or culturing conditions of the same bacterial species. Distinct immune pathways are activated by pathogens or vaccines in vivo that can be detected in PBL in vitro. Immune gene expression in PBL after stimulation with vaccine candidates may shed light on the immune pathways involved that lead to vaccine-mediated protection. This study suggests that PBL are a suitable platform for initial screening of vaccine candidates, for evaluation of vaccine-induced immune responses, and a cheap alternative for potency testing to reduce animal use in aquaculture vaccine development.
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Affiliation(s)
- Ahmed Attaya
- Scottish Fish Immunology Research Centre, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
| | - Yousheng Jiang
- Scottish Fish Immunology Research Centre, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK; College of Fishery and Life Science, Shanghai Ocean University, Shanghai, 201306, China
| | - Christopher J Secombes
- Scottish Fish Immunology Research Centre, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK
| | - Tiehui Wang
- Scottish Fish Immunology Research Centre, Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen, AB24 2TZ, UK.
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16
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Rhodes SJ, Knight GM, Kirschner DE, White RG, Evans TG. Dose finding for new vaccines: The role for immunostimulation/immunodynamic modelling. J Theor Biol 2019; 465:51-55. [PMID: 30639297 PMCID: PMC6860008 DOI: 10.1016/j.jtbi.2019.01.017] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Revised: 12/12/2018] [Accepted: 01/09/2019] [Indexed: 12/17/2022]
Abstract
Current methods to optimize vaccine dose are purely empirically based, whereas in the drug development field, dosing determinations use far more advanced quantitative methodology to accelerate decision-making. Applying these established methods in the field of vaccine development may reduce the currently large clinical trial sample sizes, long time frames, high costs, and ultimately have a better potential to save lives. We propose the field of immunostimulation/immunodynamic (IS/ID) modelling, which aims to translate mathematical frameworks used for drug dosing towards optimizing vaccine dose decision-making. Analogous to Pharmacokinetic/Pharmacodynamic (PK/PD) modelling, the mathematical description of drug distribution (PK) and effect (PD) in host, IS/ID modelling approaches apply mathematical models to describe the underlying mechanisms by which the immune response is stimulated by vaccination (IS) and the resulting measured immune response dynamics (ID). To move IS/ID modelling forward, existing datasets and further data on vaccine allometry and dose-dependent dynamics need to be generated and collate, requiring a collaborative environment with input from academia, industry, regulators, governmental and non-governmental agencies to share modelling expertise, and connect modellers to vaccine data.
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Affiliation(s)
- Sophie J Rhodes
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK.
| | - Gwenan M Knight
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK
| | | | - Richard G White
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, UK
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17
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Handel A, Li Y, McKay B, Pawelek KA, Zarnitsyna V, Antia R. Exploring the impact of inoculum dose on host immunity and morbidity to inform model-based vaccine design. PLoS Comput Biol 2018; 14:e1006505. [PMID: 30273336 PMCID: PMC6181424 DOI: 10.1371/journal.pcbi.1006505] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 10/11/2018] [Accepted: 09/12/2018] [Indexed: 12/11/2022] Open
Abstract
Vaccination is an effective method to protect against infectious diseases. An important consideration in any vaccine formulation is the inoculum dose, i.e., amount of antigen or live attenuated pathogen that is used. Higher levels generally lead to better stimulation of the immune response but might cause more severe side effects and allow for less population coverage in the presence of vaccine shortages. Determining the optimal amount of inoculum dose is an important component of rational vaccine design. A combination of mathematical models with experimental data can help determine the impact of the inoculum dose. We illustrate the concept of using data and models to inform inoculum dose determination for vaccines, wby fitting a mathematical model to data from influenza A virus (IAV) infection of mice and human parainfluenza virus (HPIV) infection of cotton rats at different inoculum doses. We use the model to map inoculum dose to the level of immune protection and morbidity and to explore how such a framework might be used to determine an optimal inoculum dose. We show how a framework that combines mathematical models with experimental data can be used to study the impact of inoculum dose on important outcomes such as immune protection and morbidity. Our findings illustrate that the impact of inoculum dose on immune protection and morbidity can depend on the specific pathogen and that both protection and morbidity do not necessarily increase monotonically with increasing inoculum dose. Once vaccine design goals are specified with required levels of protection and acceptable levels of morbidity, our proposed framework can help in the rational design of vaccines and determination of the optimal amount of inoculum. An important component of vaccines is the amount of pathogen inoculum, dead or alive, that is included in the vaccine. This inoculum dose, sometimes also referred to as antigen dose, needs to be large enough to induce good protective immunity. However, one usually also wants to keep the dose low to reduce costs, maximize the number of vaccine doses available, and minimize potential vaccine side effects. The inoculum dose is currently chosen based on limited data from clinical trials. In this study, we set up a framework that combines data with mathematical models to illustrate how such a combination could lead to better and more efficient determination of an optimal inoculum dose for vaccines.
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Affiliation(s)
- Andreas Handel
- Department of Epidemiology and Biostatistics and Health Informatics Institute and Center for the Ecology of Infectious Diseases, University of Georgia, Athens, Georgia, United States of America
- * E-mail:
| | - Yan Li
- Institute of Bioinformatics, University of Georgia, Athens, Georgia, United States of America
| | - Brian McKay
- Department of Epidemiology and Biostatistics, University of Georgia, Athens, Georgia, United States of America
| | - Kasia A. Pawelek
- Department of Mathematics and Computational Science, University of South Carolina Beaufort, Bluffton, South Carolina, United States of America
| | - Veronika Zarnitsyna
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, Georgia, United States of America
| | - Rustom Antia
- Department of Biology, Emory University, Atlanta, Georgia, United States of America
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18
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Rhodes SJ, Guedj J, Fletcher HA, Lindenstrøm T, Scriba TJ, Evans TG, Knight GM, White RG. Using vaccine Immunostimulation/Immunodynamic modelling methods to inform vaccine dose decision-making. NPJ Vaccines 2018; 3:36. [PMID: 30245860 PMCID: PMC6141590 DOI: 10.1038/s41541-018-0075-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2017] [Revised: 06/30/2018] [Accepted: 07/12/2018] [Indexed: 12/14/2022] Open
Abstract
Unlike drug dose optimisation, mathematical modelling has not been applied to vaccine dose finding. We applied a novel Immunostimulation/Immunodynamic mathematical modelling framework to translate multi-dose TB vaccine immune responses from mice, to predict most immunogenic dose in humans. Data were previously collected on IFN-γ secreting CD4+ T cells over time for novel TB vaccines H56 and H1 adjuvanted with IC31 in mice (1 dose groups (0.1-1.5 and 15 μg H56 + IC31), 45 mice) and humans (1 dose (50 μg H56/H1 + IC31), 18 humans). A two-compartment mathematical model, describing the dynamics of the post-vaccination IFN-γ T cell response, was fitted to mouse and human data, separately, using nonlinear mixed effects methods. We used these fitted models and a vaccine dose allometric scaling assumption, to predict the most immunogenic human dose. Based on the changes in model parameters by mouse H56 + IC31 dose and by varying the H56 dose allometric scaling factor between mouse and humans, we established that, at a late time point (224 days) doses of 0.8-8 μg H56 + IC31 in humans may be the most immunogenic. A 0.8-8 μg of H-series TB vaccines in humans, may be as, or more, immunogenic, as larger doses. The Immunostimulation/Immunodynamic mathematical modelling framework is a novel, and potentially revolutionary tool, to predict most immunogenic vaccine doses, and accelerate vaccine development.
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Affiliation(s)
- Sophie J. Rhodes
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, London, UK
| | - Jeremie Guedj
- IAME, UMR 1137, INSERM, Université Paris Diderot, Sorbonne Paris Cité Paris, France
- Univ Paris Diderot, Sorbonne Paris Cité, F-75018 Paris, France
| | - Helen A. Fletcher
- Immunology and Infection Department, London School of Hygiene and Tropical Medicine, London, UK
| | | | - Thomas J. Scriba
- South African Tuberculosis Vaccine Initiative, Institute of Infectious Disease and Molecular Medicine and Division of Immunology, Department of Pathology, University of Cape Town, Cape Town, South Africa
| | | | - Gwenan M. Knight
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, London, UK
| | - Richard G. White
- TB Modelling Group, CMMID, TB Centre, London School of Hygiene and Tropical Medicine, London, UK
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19
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Billeskov R, Lindenstrøm T, Woodworth J, Vilaplana C, Cardona PJ, Cassidy JP, Mortensen R, Agger EM, Andersen P. High Antigen Dose Is Detrimental to Post-Exposure Vaccine Protection against Tuberculosis. Front Immunol 2018; 8:1973. [PMID: 29379507 PMCID: PMC5775287 DOI: 10.3389/fimmu.2017.01973] [Citation(s) in RCA: 25] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2017] [Accepted: 12/20/2017] [Indexed: 11/20/2022] Open
Abstract
Mycobacterium tuberculosis (Mtb), the etiologic agent of tuberculosis (TB), causes 1.8M deaths annually. The current vaccine, BCG, has failed to eradicate TB leaving 25% of the world’s population with latent Mtb infection (LTBI), and 5–10% of these people will reactivate and develop active TB. An efficient therapeutic vaccine targeting LTBI could have an enormous impact on global TB incidence, and could be an important aid in fighting multidrug resistance, which is increasing globally. Here we show in a mouse model using the H56 (Ag85B-ESAT-6-Rv2660) TB vaccine candidate that post-exposure, but not preventive, vaccine protection requires low vaccine antigen doses for optimal protection. Loss of protection from high dose post-exposure vaccination was not associated with a loss of overall vaccine response magnitude, but rather with greater differentiation and lower functional avidity of vaccine-specific CD4 T cells. High vaccine antigen dose also led to a decreased ability of vaccine-specific CD4 T cells to home into the Mtb-infected lung parenchyma, a recently discovered important feature of T cell protection in mice. These results underscore the importance of T cell quality rather than magnitude in TB-vaccine protection, and the significant role that antigen dosing plays in vaccine-mediated protection.
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Affiliation(s)
- Rolf Billeskov
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Thomas Lindenstrøm
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Joshua Woodworth
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Cristina Vilaplana
- Unitat de Tuberculosi Experimental, Institut per a la Investigació en Ciències de la Salut Germans Trias I Pujol, CIBER Enfermedades Respiratorias, Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain
| | - Pere-Joan Cardona
- Unitat de Tuberculosi Experimental, Institut per a la Investigació en Ciències de la Salut Germans Trias I Pujol, CIBER Enfermedades Respiratorias, Universitat Autònoma de Barcelona, Badalona, Barcelona, Spain
| | - Joseph P Cassidy
- Veterinary Sciences Centre, School of Veterinary Medicine, University College Dublin, Belfield, Dublin, Ireland
| | - Rasmus Mortensen
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Else Marie Agger
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
| | - Peter Andersen
- Department of Infectious Disease Immunology, Statens Serum Institut, Copenhagen, Denmark
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