ReviewAdvanced drug delivery reviews2016
Novel adjuvant formulations for delivery of anti-tuberculosis vaccine candidates.
Review in Advanced drug delivery reviews, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
37 citing papers in PubMed.
- Comparison of long-term and short-term immunogenicity based on two different types of tuberculosis subunit vaccines.Archives of microbiology · 2026Article
- Nanoparticles in the Treatment of Renal Fibrosis.International journal of nanomedicine · 2026Review
- BCG and beyond: unlocking new frontiers in TB vaccine development.Frontiers in immunology · 2025Review
- Advancements in Nanoparticle-Based Adjuvants for Enhanced Tuberculosis Vaccination: A Review.Vaccines · 2024Review
- Recombinant mycobacterial DNA-binding protein 1 with post-translational modifications boosts IFN-gamma production from BCG-vaccinated individuals' blood cells in combination with CpG-DNA.Scientific reports · 2024Article
- TB and HIV induced immunosenescence: where do vaccines play a role?Frontiers in aging · 2024Review
- Importance of adjuvant selection in tuberculosis vaccine development: Exploring basic mechanisms and clinical implications.Vaccine: X · 2023Review
- Review
- Liposomal delivery system/adjuvant for tuberculosis vaccine.Immunity, inflammation and disease · 2023Review
- A Structural View at Vaccine Development againstCells · 2023Review
- Article
- BCG vaccination strategies against tuberculosis: updates and perspectives.Human vaccines & immunotherapeutics · 2021Review
- Article
- Recent Advances in the Development of Protein- and Peptide-Based Subunit Vaccines against Tuberculosis.Cells · 2020Review
- COVID-19 vaccine development: What lessons can we learn from TB?Annals of clinical microbiology and antimicrobials · 2020Review
- Towards new TB vaccines.Seminars in immunopathology · 2020Review
- Investigating the Impact of Delivery System Design on the Efficacy of Self-Amplifying RNA Vaccines.Vaccines · 2020Article
- Article
- First-In-Human Trials of GamTBvac, a Recombinant Subunit Tuberculosis Vaccine Candidate: Safety and Immunogenicity Assessment.Vaccines · 2019Article
- Adjuvant Strategies for More Effective Tuberculosis Vaccine Immunity.Microorganisms · 2019Review
Corrections and comments
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Authors and funding
1 author.
Funding
Abstract
There is an urgent need for a new and improved vaccine against tuberculosis for controlling this disease that continues to pose a global health threat. The current research strategy is to replace the present BCG vaccine or boost BCG-immunity with subunit vaccines such as viral vectored- or protein-based vaccines. The use of recombinant proteins holds a number of production advantages including ease of scalability, but requires an adjuvant inducing cell-mediated immune responses. A number of promising novel adjuvant formulations have recently been designed and show evidence of induction of cellular immune responses in humans. A common trait of effective TB adjuvants including those already in current clinical testing is a two-component approach combining a delivery system with an appropriate immunomodulator. This review summarizes the status of current TB adjuvant research with a focus on the division of labor between delivery systems and immunomodulators.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.