Evidence map›Paper›PMID 42626337›Full record

ReviewPNAS nexus2026

Addressing antimicrobial resistance: Current challenges, emerging strategies, and an AI-powered, community-driven approach.

Peter Wang, Alton Hsiung, Christiana Fraise, Gyula Seres, Li Ming Chong, Kui You, Angelina Moh, Chengxun Su, Yoann Sapanel, Isaiah Zhuang and 4 more

Abstract readReview
In one paragraph

Review in PNAS nexus, 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

14 authors.

Peter WangDepartment of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.ORCID https://orcid.org/0000-0002-4925-1738
Alton HsiungInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.
Christiana FraiseInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.ORCID https://orcid.org/0009-0001-6705-3655
Gyula SeresInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.
Li Ming ChongDepartment of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.
Kui YouDepartment of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.ORCID https://orcid.org/0000-0003-1450-4528
Angelina MohInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.
Chengxun SuInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.ORCID https://orcid.org/0000-0001-6723-693X
Yoann SapanelInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.ORCID https://orcid.org/0000-0001-6797-7850
Isaiah ZhuangInstitute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore 117456.
Lissa HooiDepartment of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.
Oon Tek NgNational Centre for Infectious Diseases (NCID), Singapore 308442.
Shawn VasooNational Centre for Infectious Diseases (NCID), Singapore 308442.
Dean HoDepartment of Biomedical Engineering, College of Design and Engineering, National University of Singapore, Singapore 117583.ORCID https://orcid.org/0000-0002-7337-296X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rising incidence of antimicrobial resistance (AMR) has threatened global public health with a high mortality rate. In parallel, the de-incentivization for further investment, regulatory constraints, and overuse/misuse of antibiotics have accelerated the progression of AMR. Together, these factors have contributed to the declining efficacy of a wide spectrum of antibiotics and the increasing prevalence of drug resistance that outpaced AMR-specific drug development. More importantly, even with substantial historical investments in antibiotic discovery over several decades, the development of clinically actionable, novel antibiotics has remained limited. In this article, we present the challenges of addressing AMR and outline emerging strategies that may reduce its burden. While advanced therapies, including bacteriophage therapy, have demonstrated promising results, complementary strategies that integrate emerging technologies and engage diverse stakeholders are needed. Building on this vision, we propose the potential role of AI-powered platforms in supporting and accelerating AMR-specific drug development alongside a community-driven approach that engages scientists, policymakers, health economists, clinicians, and patients to help address existing scientific and translational challenges. Furthermore, this article offers an inclusive strategy with key considerations, including educational and public health interventions, government-led programs, and health economics, which together could potentially tackle the threat of AMR along with AI-powered solutions.

Indexed as

antibioticsantimicrobial resistanceartificial intelligencegovernancepublic health

Identifiers

PMID42626337
PMCPMC13492212

What Socratic 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 Socratic graph.