Evidence map›Paper›PMID 35773329›Full record

ArticleNPJ digital medicine2022

The IDentif.AI-x pandemic readiness platform: Rapid prioritization of optimized COVID-19 combination therapy regimens.

Agata Blasiak, Anh T L Truong, Alexandria Remus, Lissa Hooi, Shirley Gek Kheng Seah, Peter Wang, De Hoe Chye, Angeline Pei Chiew Lim, Kim Tien Ng, Swee Teng Teo and 11 more

Abstract read
In one paragraph

Article in NPJ digital medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
–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

12 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
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  9. N-of-1 medicine.Singapore medical journal · 2024
    Article
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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

21 authors.

Agata Blasiak *The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore. agata.blasiak@nus.edu.sg.ORCID http://orcid.org/0000-0003-0727-7611
Anh T L Truong *The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore.ORCID http://orcid.org/0000-0003-1551-4437
Alexandria Remus *The Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore.
Lissa Hooi *Cancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore.
Shirley Gek Kheng Seah *Defence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore.
Peter WangThe Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore.ORCID http://orcid.org/0000-0002-4925-1738
De Hoe ChyeDefence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore.
Angeline Pei Chiew LimDefence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore.
Kim Tien NgDefence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore.
Swee Teng TeoInfectious Diseases Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117545, Singapore.
Yee-Joo TanInfectious Diseases Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117545, Singapore.ORCID http://orcid.org/0000-0002-2278-4497
David Michael AllenDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.ORCID http://orcid.org/0000-0001-5333-1258
Louis Yi Ann ChaiDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.
Wee Joo ChngCancer Science Institute of Singapore, National University of Singapore, Singapore, 117599, Singapore.
Raymond T P LinNational Centre for Infectious Diseases (NCID), Jalan Tan Tock Seng, Singapore, 308442, Singapore.
David C B LyeDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.
John Eu-Li WongDepartment of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.
Gek-Yen Gladys TanDefence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore.
Conrad En Zuo ChanDefence Medical and Environmental Research Institute, DSO National Laboratories, Singapore, 117510, Singapore. Conrad_EZ_CHAN@ncid.sg.
Edward Kai-Hua ChowThe Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore. csikce@nus.edu.sg.
Dean HoThe Institute for Digital Medicine (WisDM), Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 117456, Singapore. biedh@nus.edu.sg.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

IDentif.AI-x, a clinically actionable artificial intelligence platform, was used to rapidly pinpoint and prioritize optimal combination therapies against COVID-19 by pairing a prospective, experimental validation of multi-drug efficacy on a SARS-CoV-2 live virus and Vero E6 assay with a quadratic optimization workflow. A starting pool of 12 candidate drugs developed in collaboration with a community of infectious disease clinicians was first narrowed down to a six-drug pool and then interrogated in 50 combination regimens at three dosing levels per drug, representing 729 possible combinations. IDentif.AI-x revealed EIDD-1931 to be a strong candidate upon which multiple drug combinations can be derived, and pinpointed a number of clinically actionable drug interactions, which were further reconfirmed in SARS-CoV-2 variants B.1.351 (Beta) and B.1.617.2 (Delta). IDentif.AI-x prioritized promising drug combinations for clinical translation and can be immediately adjusted and re-executed with a new pool of promising therapies in an actionable path towards rapidly optimizing combination therapy following pandemic emergence.

Identifiers

PMID35773329
PMCPMC9244889

What OpenQuestion holds

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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.