Evidence map›Paper›PMID 42647463›Full record

ArticlePloS one2026

Changes in evidence used for FDA Novel Drug Approvals: 2016-2024.

Aditya Narayan, Veronica L Irvin, Amanda J Koong, Sujin Song, Robert M Kaplan

Abstract read
In one paragraph

Article in PloS one, 2026. 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
–field-weighted citation impact
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.

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

5 authors.

Aditya NarayanStanford University School of Medicine, Clinical Excellence Research Center, Palo Alto, California, United States of America.ORCID https://orcid.org/0000-0002-2427-6445
Veronica L IrvinOregon State University, College of Health, Corvallis, Oregon, United States of America.
Amanda J KoongMcGovern School of Medicine, Houston, Texas, USA and UCLA, Fielding School of Public Health, Los Angeles, California, United States of America.ORCID https://orcid.org/0000-0002-2447-4695
Sujin SongStanford University School of Medicine, Clinical Excellence Research Center, Palo Alto, California, United States of America.ORCID https://orcid.org/0009-0002-5742-4667
Robert M KaplanStanford University School of Medicine, Clinical Excellence Research Center, Palo Alto, California, United States of America.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe 21st Century Cures Act (2017) was enacted during a period of evolving FDA flexibility in evidentiary standards for drug approval. To examine trends before and after implementation, we independently reviewed all novel drugs approved between 2016 and 2024.

methodsWe constructed a database of all novel FDA approvals from January 1, 2016, through December 31, 2024. Each study linked to an approved drug (N = 6,763) was cataloged by study number, sponsorship, and timing of results reporting relative to completion.

resultsSince 2016, the number of studies supporting approval has steadily declined. Beginning in 2017, the modal number of studies per approval fell to one. Industry sponsorship increased while NIH-supported studies decreased. Average time to public posting of results exceeded the one-year statutory limit.

conclusionsIn the post-2016 period, FDA approvals were supported by fewer studies and by a greater proportion of industry-sponsored studies. Although this may accelerate access to new therapies, it raises concerns about the strength of evidence for safety and effectiveness.

Indexed as

Drug ApprovalUnited States Food and Drug AdministrationDatabases, FactualDrug IndustryHumansUnited States

Identifiers

PMID42647463
PMCPMC13514025

What OpenQuestion holds

Textmetadata
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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.