ArticleVaccine2021
Mind the gap from research laboratory to clinic: Challenges and opportunities for next-generation assays in human diseases.
Article in Vaccine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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Who cites it
0 citing papers in PubMed.
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Authors and funding
10 authors.
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Abstract
Modern vaccinology has experienced major conceptual and technological advances over the past 30 years. These include atomic-level structures driving immunogen design, new vaccine delivery methods, powerful adjuvants, and novel animal models. In addition, utilizing advanced assays to learn how the immune system senses a pathogen and orchestrates protective immunity has been critical in the design of effective vaccines and therapeutics. The National Institute of Allergy and Infectious Diseases of the National Institutes of Health convened a workshop in September 2020 focused on next generation assays for vaccine development (Table 1). The workshop focused on four critical pathogens: severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) and human immunodeficiency virus (HIV)-which have no licensed vaccines-and tuberculosis (TB) and influenza-both of which are in critical need of improved vaccines. The goal was to share progress and lessons learned, and to identify any commonalities that can be leveraged to design vaccines and therapeutics.
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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.