Evidence map›Paper›PMID 42306083›Full record

ArticleMolecular therapy. Nucleic acids2026

Multiscale modeling guided potency assessment of mRNA-lipid nanoparticles.

Yuling Yang, Yuchen Qiu, Keqi Wang, Yifang Liu, Gautam Sanyal, Paul C Whitford, Sara H Rouhanifard, Wei Xie

Abstract read
In one paragraph

Article in Molecular therapy. Nucleic acids, 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

8 authors.

Yuling YangDepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA.
Yuchen QiuDepartment of Bioengineering, Northeastern University, Boston, MA, USA.
Keqi WangDepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA.
Yifang LiuDepartment of Bioengineering, Northeastern University, Boston, MA, USA.
Gautam SanyalVaccine Analytics LLC, Kendall Park, NJ, USA.
Paul C WhitfordCenter for Theoretical Biological Physics, Department of Physics and Department of Chemical Engineering, Northeastern University, Boston, MA, USA.
Sara H RouhanifardDepartment of Bioengineering, Northeastern University, Boston, MA, USA.
Wei XieDepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

mRNA lipid nanoparticle (mRNA-LNP) technology has emerged as a cornerstone in vaccine development due to its high delivery efficiency, molecular stability, and favorable safety profile. However, rapid and reliable potency assessment remains challenging because of limited mechanistic understanding of delivery processes and sparse experimental data. To address these gaps, we introduce a mechanism-informed, multi-scale kinetic modularized modeling framework that quantitatively captures the coupled dynamics of mRNA delivery across nanoparticle, cellular, and macroscopic scales. The model incorporates variability in LNP-cell interactions and integrates key determinants, such as dosage, LNP and cell size distributions, cell proliferation, and membrane properties-factors that critically shape delivery efficiency and response heterogeneity. Its cell-based architecture and modular design enable adaptability to diverse delivery systems and physiological contexts. By leveraging advanced multi-omics assays, including single-molecule fluorescent

Indexed as

lipid nanoparticlesLNP-cell interactionsLNPsmRNA vaccinesMT: Delivery Strategiesmulti-omics assaysmulti-scale modelingpotency predictionsingle-molecule fluorescent in situ hybridization

Identifiers

PMID42306083
PMCPMC13267553

What OpenQuestion holds

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Registered trials

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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.