Evidence map›Paper›PMID 38265630›Full record

ReviewPharmaceutical medicine2024

Emergency Approval Mechanisms for Human Vaccines in India.

Nidhi Mehrotra, Padmavati Manchikanti

Abstract readReview
PubMed Publisher
In one paragraph

Review in Pharmaceutical medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 37% of its field
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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Nidhi MehrotraRajiv Gandhi School of Intellectual Property Law, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India. nidhimehrotra11@gmail.com.
Padmavati ManchikantiRajiv Gandhi School of Intellectual Property Law, Indian Institute of Technology Kharagpur, Kharagpur, 721302, India. mpadma@rgsoipl.iitkgp.ac.in.
Indian Institute of Technology Kharagpur · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic highlighted the world's level of preparedness in managing public health emergencies (PHEs). It revealed the critical need for timely medical therapeutics, especially vaccines. To expedite response, many nations, including India, adopted emergency approval mechanisms and offered new ways of review, such as the rolling review along with the accelerated review procedure. This response resulted in reallocating internal resources and adopting new policies and measures, such as integrating digital technology with regulatory submissions and flexibility in statistical approaches. The present review focuses on the utilization of the New Drugs and Clinical Trials Rules 2019 for granting emergency approval to COVID-19 vaccines by the Drug Controller General of India (DCGI) and explores the legislative basis for such authorization during the PHE. The review aims to elucidate key intricacies and challenges inherent in the existing 'emergency use' framework within the Indian regulatory landscape. It assesses three critical facets of the 'emergency use' paradigm: the definition of the term, establishment of a transparent decision-making process, and formulation of rules governing termination or expiration of the emergency status. It makes policy recommendations regarding the 'emergency use' framework to respond to new, emerging, or re-emerging public health threats of the future.

Indexed as

COVID-19VaccinesCOVID-19 VaccinesHumansIndiaCOVID-19 VaccinesVaccines

Identifiers

PMID38265630
OpenAlexW4391174424

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.