Evidence map›Paper›PMID 33227451›Full record

ArticleContemporary clinical trials2021

Innovative trial designs and analyses for vaccine clinical development.

Mengya Liu, Qing Li, Jianchang Lin, Yunzhi Lin, Elaine Hoffman

Abstract read
In one paragraph

Article in Contemporary clinical trials, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mengya LiuTakeda Pharmaceuticals, 300 Massachusetts Ave, Cambridge, MA 02139, United States. Electronic address: Mona.Liu@takeda.com.
Qing LiTakeda Pharmaceuticals, 300 Massachusetts Ave, Cambridge, MA 02139, United States. Electronic address: qing.li2@takeda.com.
Jianchang LinTakeda Pharmaceuticals, 300 Massachusetts Ave, Cambridge, MA 02139, United States. Electronic address: Jianchang.Lin@takeda.com.
Yunzhi LinSanofi, 50 Binney Street, Cambridge, MA 02142, United States.
Elaine HoffmanTakeda Pharmaceuticals, 300 Massachusetts Ave, Cambridge, MA 02139, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the past decades, the world has experienced several major virus outbreaks, e.g. West African Ebola outbreak, Zika virus in South America and most recently global coronavirus (COVID-19) pandemic. Many vaccines have been developed to prevent a variety of infectious diseases successfully. However, several infections have not been preventable so far, like COVID-19, which induces an immediate urgent need for effective vaccines. These emerging infectious diseases often pose unprecedent challenges for the global heath community as well as the conventional vaccine development paradigm. With a long and costly traditional vaccine development process, there are extensive needs in innovative vaccine trial designs and analyses, which aim to design more efficient vaccines trials. Featured with reduced development timeline, less resource consuming or improved estimate for the endpoints of interests, these more efficient trials bring effective medicine to target population in a faster and less costly way. In this paper, we will review a few vaccine trials equipped with adaptive design features, Bayesian designs that accommodate historical data borrowing, the master protocol strategy emerging during COVID-19 vaccine development, Real-World-Data (RWD) embedded trials and the correlate of protection framework and relevant research works. We will also discuss some statistical methodologies that improve the vaccine efficacy, safety and immunogenicity analyses. Innovative clinical trial designs and analyses, together with advanced research technologies and deeper understanding of the human immune system, are paving the way for the efficient development of new vaccines in the future.

Indexed as

Viral VaccinesBayes TheoremBiomedical ResearchClinical Trials as TopicDrug DevelopmentHumansTime FactorsViral VaccinesAdaptive designBayesian designCorrelate of protectionCOVID-19Master protocolRWDVaccine trials

Identifiers

PMID33227451
PMCPMC7834363

What OpenQuestion holds

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Registered trials

None linked

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.