Evidence map›Paper›PMID 38622352›Full record

ReviewNature reviews. Microbiology2024

COVID-19 drug discovery and treatment options.

Jasper Fuk-Woo Chan, Shuofeng Yuan, Hin Chu, Siddharth Sridhar, Kwok-Yung Yuen

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Microbiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers.

0numbers the graph read from it
0cells of the map it votes in
46citing papers in PubMed
27.6field-weighted citation impact, top 1% 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

46 citing papers in PubMed, 71 citations in OpenAlex.

  1. Trial
  2. Article
  3. Article
  4. Structural analysis of the flexibility of the Ubl2 domain within the papain-like protease of SARS-CoV-2.Acta crystallographica. Section F, Structural biology communications · 2026
    Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Host Responses to SARS-CoV-2 with an Emphasis on Cytokines.International journal of molecular sciences · 2026
    Review
  14. Article
  15. Article
  16. Fingerprint-Based Machine Learning for SARS-CoV-2 and MERS-CoVJournal of chemical information and modeling · 2025
    Article
  17. Article
  18. Review
  19. Article
  20. 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

5 authors at 2 institutions in 2 countries.

Jasper Fuk-Woo ChanState Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID http://orcid.org/0000-0001-6336-6657
Shuofeng YuanState Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID http://orcid.org/0000-0001-7996-1119
Hin ChuState Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID http://orcid.org/0000-0003-2855-9837
Siddharth SridharState Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.ORCID http://orcid.org/0000-0002-2022-8307
Kwok-Yung YuenState Key Laboratory of Emerging Infectious Diseases, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China. kyyuen@hku.hk.ORCID http://orcid.org/0000-0002-2083-1552
Hong Kong Science and Technology Parks Corporation · HKUniversity of Hong Kong - Shenzhen Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The coronavirus disease 2019 (COVID-19) pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused substantial morbidity and mortality, and serious social and economic disruptions worldwide. Unvaccinated or incompletely vaccinated older individuals with underlying diseases are especially prone to severe disease. In patients with non-fatal disease, long COVID affecting multiple body systems may persist for months. Unlike SARS-CoV and Middle East respiratory syndrome coronavirus, which have either been mitigated or remained geographically restricted, SARS-CoV-2 has disseminated globally and is likely to continue circulating in humans with possible emergence of new variants that may render vaccines less effective. Thus, safe, effective and readily available COVID-19 therapeutics are urgently needed. In this Review, we summarize the major drug discovery approaches, preclinical antiviral evaluation models, representative virus-targeting and host-targeting therapeutic options, and key therapeutics currently in clinical use for COVID-19. Preparedness against future coronavirus pandemics relies not only on effective vaccines but also on broad-spectrum antivirals targeting conserved viral components or universal host targets, and new therapeutics that can precisely modulate the immune response during infection.

Indexed as

Antiviral AgentsCOVID-19COVID-19 Drug TreatmentDrug DiscoverySARS-CoV-2AnimalsHumansAntiviral Agents

Identifiers

PMID38622352
OpenAlexW4394808413

What Socratic 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 Socratic graph.