Evidence map›Paper›PMID 33864098›Full record

ReviewNaunyn-Schmiedeberg's archives of pharmacology2021

A year in pharmacology: new drugs approved by the US Food and Drug Administration in 2020.

Gizem Kayki-Mutlu, Martin C Michel

Open access · hybridAbstract readReview
In one paragraph

Review in Naunyn-Schmiedeberg's archives of pharmacology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.7field-weighted citation impact, top 17% 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

8 citing papers in PubMed, 14 citations in OpenAlex.

  1. Review
  2. Do GPCRs constitute the target of 30% of newly approved drugs in Germany?Naunyn-Schmiedeberg's archives of pharmacology · 2026
    Article
  3. Comparison of drug approvals of the FDA and EMA between 2013 and 2023.Naunyn-Schmiedeberg's archives of pharmacology · 2026
    Article
  4. Review
  5. Review
  6. Review
  7. Review
  8. Article
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 2 institutions in 2 countries.

Gizem Kayki-MutluDepartment of Pharmacology, Faculty of Pharmacy, Ankara University, Ankara, Turkey.
Martin C MichelDepartment of Pharmacology, Johannes Gutenberg University, Langenbeckstr. 1, 55118, Mainz, Germany. marmiche@uni-mainz.de.ORCID 0000-0003-4161-8467
Ankara University · TRJohannes Gutenberg University Mainz · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

While the COVID-19 pandemic also affected the work of regulatory authorities, the US Food and Drug Administration approved a total of 53 new drugs in 2020, one of the highest numbers in the past decades. Most newly approved drugs related to oncology (34%) and neurology (15%). We discuss these new drugs by level of innovation they provide, i.e., first to treat a condition, first using a novel mechanisms of action, and "others." Six drugs were first in indication, 15 first using a novel mechanism of action, and 32 other. This includes many drugs for the treatment of orphan indications and some for the treatment of tropical diseases previously neglected for commercial reasons. Small molecules continue to dominate new drug approvals, followed by antibodies. Of note, newly approved drugs also included small-interfering RNAs and antisense oligonucleotides. These data show that the trend for declines in drug discovery and development has clearly been broken.

Indexed as

COVID-19Drug ApprovalPandemicsUnited States Food and Drug AdministrationAnimalsDrug DiscoveryHumansPharmacology, ClinicalUnited StatesFDAFirst-in-classFirst-in-indicationNew drugs

Identifiers

PMID33864098
PMCPMC8051285
OpenAlexW3153612857

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.