Evidence map›Paper›PMID 36216772›Full record

ArticleSmall (Weinheim an der Bergstrasse, Germany)2022

Artificial Immune Cell, AI-cell, a New Tool to Predict Interferon Production by Peripheral Blood Monocytes in Response to Nucleic Acid Nanoparticles.

Morgan Chandler, Sankalp Jain, Justin Halman, Enping Hong, Marina A Dobrovolskaia, Alexey V Zakharov, Kirill A Afonin

Abstract read
In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing 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

38 citing papers in PubMed.

  1. Review
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  10. Review
  11. Article
  12. Article
  13. Q&A Translational Cancer Nanomedicine.Nature communications · 2025
    Article
  14. Review
  15. Machine Learning-Enhanced Nanoparticle Design for Precision Cancer Drug Delivery.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
  16. Article
  17. Article
  18. Article
  19. Review
  20. Review
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

7 authors.

Morgan ChandlerDepartment of Chemistry, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
Sankalp JainNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA.
Justin HalmanDepartment of Chemistry, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.
Enping HongNanotechnology Characterization Lab, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Marina A DobrovolskaiaNanotechnology Characterization Lab, Cancer Research Technology Program, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Alexey V ZakharovNational Center for Advancing Translational Sciences, National Institutes of Health, Rockville, MD, 20850, USA.
Kirill A AfoninDepartment of Chemistry, University of North Carolina at Charlotte, Charlotte, NC, 28223, USA.ORCID 0000-0002-6917-3183

Funding

WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · PI BRISCOE, LYNN · 2019 to 2025
$3932.6M
SMART NANPs: new molecular platform for communication with human immune system and modulation of therapeutic responsesR35GM139587 · NIGMS · UNIVERSITY OF NORTH CAROLINA CHARLOTTE · PI AFONIN, KIRILL A · 2021 to 2025
$1.8M
Characterization of various multifunctional nucleic acid nanoparticles and understanding their immunotoxicityR01GM120487 · NIGMS · UNIVERSITY OF NORTH CAROLINA CHARLOTTE · PI AFONIN, KIRILL A · 2017 to 2020
$1.5M
NCI NIH HHS 75N91019D00024NIGMS NIH HHS R01 GM120487NIGMS NIH HHS R35 GM139587
6 · The paper itself

Abstract

Nucleic acid nanoparticles, or NANPs, rationally designed to communicate with the human immune system, can offer innovative therapeutic strategies to overcome the limitations of traditional nucleic acid therapies. Each set of NANPs is unique in their architectural parameters and physicochemical properties, which together with the type of delivery vehicles determine the kind and the magnitude of their immune response. Currently, there are no predictive tools that would reliably guide the design of NANPs to the desired immunological outcome, a step crucial for the success of personalized therapies. Through a systematic approach investigating physicochemical and immunological profiles of a comprehensive panel of various NANPs, the research team developes and experimentally validates a computational model based on the transformer architecture able to predict the immune activities of NANPs. It is anticipated that the freely accessible computational tool that is called an "artificial immune cell," or AI-cell, will aid in addressing the current critical public health challenges related to safety criteria of nucleic acid therapies in a timely manner and promote the development of novel biomedical tools.

Indexed as

NanoparticlesNucleic AcidsArtificial IntelligenceHumansInterferonsMonocytesInterferonsNucleic Acidsartificial intelligenceimmunologyimmunorecognitionmachine learningnucleic acid nanoparticles (NANPs)RNA nanotechnology

Identifiers

PMID36216772
PMCPMC9671856

What Socratic 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 Socratic graph.